{"case_id": "challenge-coding-001", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "parser", "state"], "scorer": "code_python_tests", "expected": {"tests": ["lines = ['# comment', '[db]', ' host = localhost ', 'port=5432', '', '[feature]', 'enabled=true', 'enabled = false']\nassert solution.solve(lines) == {'db': {'host': 'localhost', 'port': '5432'}, 'feature': {'enabled': 'false'}}", "assert solution.solve(['[x]', 'a=1', 'a=2', '[y]', 'b = hi']) == {'x': {'a': '2'}, 'y': {'b': 'hi'}}"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(lines: list[str]) -> dict。lines 是简化 INI：空行和以 # 开头的行忽略；[section] 开始新 section；key=value 写入当前 section；key/value 两侧空白要去掉；同一 section 内重复 key 后者覆盖前者。返回嵌套 dict。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "2ca132befd6923601a17f24e5efb427ea787e3ae63ae265dd45f0c700cd895d6", "started_at": "2026-06-16T12:01:16.834238+00:00", "latency_ms": 9255, "output": "```python\ndef solve(lines: list[str]) -> dict:\n result = {}\n current_section = None\n \n for line in lines:\n stripped = line.strip()\n if not stripped or stripped.startswith('#'):\n continue\n if stripped.startswith('[') and stripped.endswith(']'):\n current_section = stripped[1:-1].strip()\n if current_section not in result:\n result[current_section] = {}\n elif '=' in stripped and current_section is not None:\n key, value = stripped.split('=', 1)\n key = key.strip()\n value = value.strip()\n result[current_section][key] = value\n \n return result\n```", "usage": {"prompt_tokens": 105, "completion_tokens": 150, "total_tokens": 255, "cost": 0.0007047, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0007047, "upstream_inference_prompt_cost": 0.0001827, "upstream_inference_completions_cost": 0.000522}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611279-JAYTS7QdfBFZZSV3xUJL", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-002", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "ledger", "state"], "scorer": "code_python_tests", "expected": {"tests": ["events = ['a credit 100', 'b debit 40', 'a credit 999', 'rev b', 'c debit 10']\nassert solution.solve(events) == 90", "events = ['x debit 5', 'rev y', 'rev x', 'rev x', 'z credit 7']\nassert solution.solve(events) == 7"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(events: list[str]) -> int。事件格式：\" credit \" 增加余额，\" debit \" 减少余额，\"rev \" 撤销此前尚未撤销过的同 id 事件。重复交易 id 只保留第一次，未知撤销忽略。返回最终余额。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "3d2d5a46a600444476b5ddfd04634035ff394bcb76fcd230d785597c9cf295ae", "started_at": "2026-06-16T12:01:26.138396+00:00", "latency_ms": 29612, "output": "```python\ndef solve(events):\n balance = 0\n records = {}\n for ev in events:\n parts = ev.split()\n if not parts:\n continue\n if parts[0] == 'rev':\n if len(parts) != 2:\n continue\n eid = parts[1]\n if eid in records:\n typ, amt, revoked = records[eid]\n if not revoked:\n if typ == 'credit':\n balance -= amt\n else:\n balance += amt\n records[eid] = (typ, amt, True)\n else:\n if len(parts) != 3:\n continue\n eid, op, amt_str = parts\n if op not in ('credit', 'debit'):\n continue\n try:\n amt = int(amt_str)\n except ValueError:\n continue\n if eid in records:\n continue\n records[eid] = (op, amt, False)\n if op == 'credit':\n balance += amt\n else:\n balance -= amt\n return balance\n```", "usage": {"prompt_tokens": 105, "completion_tokens": 1389, "total_tokens": 1494, "cost": 0.0021925215, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0021925215, "upstream_inference_prompt_cost": 7.98525e-05, "upstream_inference_completions_cost": 0.002112669}, "completion_tokens_details": {"reasoning_tokens": 1145, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611288-1zDLpKDP4l8bhvrh8Jwq", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-003", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "topological-sort"], "scorer": "code_python_tests", "expected": {"tests": ["deps = {'build': ['lint', 'test'], 'test': ['install'], 'lint': ['install']}\nassert solution.solve(deps) == [['install'], ['lint', 'test'], ['build']]", "assert solution.solve({'a': ['b'], 'b': ['a']}) == []", "assert solution.solve({'deploy': ['build'], 'build': []}) == [['build'], ['deploy']]"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(deps: dict[str, list[str]]) -> list[list[str]]。deps 表示 task -> prerequisites。返回可并行执行的拓扑层，每层任务按字典序排序；如果存在环，返回空列表。所有只出现在 prerequisites 中的任务也要包含。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "413c5b602b0fd1ae1e9c3a49b09ecf03c61769fce4b34dbd96b5d8c6a2c68f90", "started_at": "2026-06-16T12:01:55.787325+00:00", "latency_ms": 32317, "output": "```python\ndef solve(deps: dict[str, list[str]]) -> list[list[str]]:\n all_nodes = set(deps.keys())\n for prereqs in deps.values():\n all_nodes.update(prereqs)\n\n in_degree = {node: 0 for node in all_nodes}\n adj = {node: [] for node in all_nodes}\n\n for task, prereqs in deps.items():\n in_degree[task] = len(prereqs)\n for prereq in prereqs:\n adj[prereq].append(task)\n\n queue = sorted([node for node in all_nodes if in_degree[node] == 0])\n layers = []\n processed = 0\n\n while queue:\n layer = queue[:]\n layers.append(layer)\n processed += len(layer)\n next_queue = []\n for u in layer:\n for v in adj[u]:\n in_degree[v] -= 1\n if in_degree[v] == 0:\n next_queue.append(v)\n queue = sorted(next_queue)\n\n if processed != len(all_nodes):\n return []\n\n return layers\n```", "usage": {"prompt_tokens": 97, "completion_tokens": 1560, "total_tokens": 1657, "cost": 0.0024465285, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0024465285, "upstream_inference_prompt_cost": 7.37685e-05, "upstream_inference_completions_cost": 0.00237276}, "completion_tokens_details": {"reasoning_tokens": 1316, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611318-wTUe8h6KgfnnHvrc9UrO", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-004", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "lru"], "scorer": "code_python_tests", "expected": {"tests": ["ops = ['put a 1', 'put b 2', 'get a', 'put c 3', 'get b', 'get a', 'get c']\nassert solution.solve(2, ops) == [1, -1, 1, 3]", "assert solution.solve(0, ['put a 1', 'get a']) == [-1]", "assert solution.solve(1, ['put a 1', 'put a 2', 'get a']) == [2]"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(capacity: int, ops: list[str]) -> list[int]，模拟 LRU cache。ops 包含 \"put key value\" 和 \"get key\"。get 返回 value，不存在返回 -1。put 已存在 key 要更新并变成最近使用。容量为 0 时所有 get 都返回 -1。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "840e7b4d0c404f3d7b34ebc9931e87612608d6339755d5f1066fda55bd957375", "started_at": "2026-06-16T12:02:28.150723+00:00", "latency_ms": 6170, "output": "```python\nfrom collections import OrderedDict\nfrom typing import List\n\ndef solve(capacity: int, ops: List[str]) -> List[int]:\n results = []\n cache = OrderedDict()\n \n for op in ops:\n parts = op.split()\n if parts[0] == \"get\":\n key = int(parts[1])\n if capacity == 0:\n results.append(-1)\n elif key in cache:\n cache.move_to_end(key)\n results.append(cache[key])\n else:\n results.append(-1)\n else: # put\n key = int(parts[1])\n value = int(parts[2])\n if capacity == 0:\n continue\n if key in cache:\n cache.move_to_end(key)\n cache[key] = value\n else:\n if len(cache) >= capacity:\n cache.popitem(last=False)\n cache[key] = value\n return results\n```", "usage": {"prompt_tokens": 110, "completion_tokens": 273, "total_tokens": 383, "cost": 0.000498888, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.000498888, "upstream_inference_prompt_cost": 8.3655e-05, "upstream_inference_completions_cost": 0.000415233}, "completion_tokens_details": {"reasoning_tokens": 71, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611350-ADEmuMB1AAuYef59jZi3", "finish_reason": "stop", "score": {"passed": false, "score": 0.0, "details": {"returncode": 1, "stdout": "", "stderr": "Traceback (most recent call last):\n File \"/var/folders/x_/4cht1kfj1_j31gdv5w01sgmw0000gn/T/dracobench-code-zbhmi4m3/test_solution.py\", line 4, in \n assert solution.solve(2, ops) == [1, -1, 1, 3]\n ^^^^^^^^^^^^^^^^^^^^^^\n File \"/private/var/folders/x_/4cht1kfj1_j31gdv5w01sgmw0000gn/T/dracobench-code-zbhmi4m3/solution.py\", line 20, in solve\n key = int(parts[1])\n ^^^^^^^^^^^^^\nValueError: invalid literal for int() with base 10: 'a'\n"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-005", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "json", "copy"], "scorer": "code_python_tests", "expected": {"tests": ["base = {'a': 1, 'b': {'x': 1, 'y': 2}, 'c': 3}\npatch = {'b': {'y': None, 'z': 4}, 'c': None}\nassert solution.solve(base, patch) == {'a': 1, 'b': {'x': 1, 'z': 4}}\nassert base == {'a': 1, 'b': {'x': 1, 'y': 2}, 'c': 3}", "assert solution.solve({'a': {'b': 1}}, {'a': 5}) == {'a': 5}"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(base: dict, patch: dict) -> dict，执行 JSON Merge Patch：patch 中值为 None 表示删除该 key；两个值都是 dict 时递归合并；其他值覆盖。不能修改输入对象。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "8dc22406b418d74ea74b50692fe086d4f80748258269dc93f82290e6c344b5a3", "started_at": "2026-06-16T12:02:34.377734+00:00", "latency_ms": 20766, "output": "```python\ndef solve(base: dict, patch: dict) -> dict:\n result = {k: v for k, v in base.items()}\n for key, value in patch.items():\n if value is None:\n result.pop(key, None)\n elif isinstance(value, dict) and isinstance(result.get(key), dict):\n result[key] = solve(result[key], value)\n else:\n result[key] = value\n return result\n```", "usage": {"prompt_tokens": 85, "completion_tokens": 96, "total_tokens": 181, "cost": 0.000385584, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.000385584, "upstream_inference_prompt_cost": 0.00011832, "upstream_inference_completions_cost": 0.000267264}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611356-H8o2R3LthirOiioI8sUF", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-006", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "regex", "duration"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('1h 30m 500ms') == 5400500", "assert solution.solve('2d 1h 2s') == 176402000", "assert solution.solve('100ms 2s 3ms') == 2103"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(text: str) -> int，把时长字符串转换成毫秒。支持整数单位 d、h、m、s、ms，可有空格，单位可重复，顺序任意。例如 \"1h 30m 500ms\"。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "ce87366a2f6f080a35c0fdd0872b6a8304a8233e0c5c9361c19fec614c0d1fcb", "started_at": "2026-06-16T12:02:55.191125+00:00", "latency_ms": 7183, "output": "```python\nimport re\n\ndef solve(text: str) -> int:\n total_ms = 0\n # 使用正则匹配数字和单位，单位可以是 ms, d, h, m, s\n pattern = re.compile(r'(\\d+)\\s*(ms|[dhms])')\n matches = pattern.findall(text)\n for num_str, unit in matches:\n val = int(num_str)\n if unit == 'd':\n total_ms += val * 86400000\n elif unit == 'h':\n total_ms += val * 3600000\n elif unit == 'm':\n total_ms += val * 60000\n elif unit == 's':\n total_ms += val * 1000\n elif unit == 'ms':\n total_ms += val\n return total_ms\n```", "usage": {"prompt_tokens": 88, "completion_tokens": 257, "total_tokens": 345, "cost": 0.000457821, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.000457821, "upstream_inference_prompt_cost": 6.6924e-05, "upstream_inference_completions_cost": 0.000390897}, "completion_tokens_details": {"reasoning_tokens": 79, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611377-QY9PzyAqzctFbweb42wE", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-007", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "parser", "quotes"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('{a:[(1)]}') is True", "assert solution.solve(\"{'x': '(]'}\") is True", "assert solution.solve(\"['unterminated]\") is False", "assert solution.solve('([)]') is False", "assert solution.solve(\"\\\"paren \\\\\\\" ) still quoted\\\"\") is True"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(s: str) -> bool，检查括号 ()[]{} 是否配对。单引号或双引号内部的括号忽略；反斜杠会转义引号。输入字符串可以包含普通字符。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "2f2e8f01533244c8104f74b3f9c9bc261154f2ff4c46c03a031258f6a5706f9f", "started_at": "2026-06-16T12:03:02.427097+00:00", "latency_ms": 33254, "output": "```python\ndef solve(s: str) -> bool:\n stack = []\n i = 0\n n = len(s)\n in_single = False\n in_double = False\n while i < n:\n c = s[i]\n if in_single:\n if c == '\\\\':\n i += 2 # skip escaped char\n continue\n elif c == \"'\":\n in_single = False\n i += 1\n elif in_double:\n if c == '\\\\':\n i += 2\n continue\n elif c == '\"':\n in_double = False\n i += 1\n else:\n if c == \"'\":\n in_single = True\n elif c == '\"':\n in_double = True\n elif c in '([{':\n stack.append(c)\n elif c in ')]}':\n if not stack:\n return False\n left = stack.pop()\n if (c == ')' and left != '(') or \\\n (c == ']' and left != '[') or \\\n (c == '}' and left != '{'):\n return False\n i += 1\n return not stack\n```", "usage": {"prompt_tokens": 83, "completion_tokens": 1139, "total_tokens": 1222, "cost": 0.00398926, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00398926, "upstream_inference_prompt_cost": 0.00013944, "upstream_inference_completions_cost": 0.00384982}, "completion_tokens_details": {"reasoning_tokens": 876, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611384-jCQrKAtdwtcX2ngAcD0o", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-008", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "dedupe", "sorting"], "scorer": "code_python_tests", "expected": {"tests": ["rows = [{'user':'b','ts':1,'value':'old'}, {'user':'a','ts':2,'value':'x'}, {'user':'b','ts':3,'value':'new'}]\nassert solution.solve(rows) == [{'user':'a','ts':2,'value':'x'}, {'user':'b','ts':3,'value':'new'}]", "rows = [{'user':'a','ts':1,'value':'first'}, {'user':'a','ts':1,'value':'second'}]\nassert solution.solve(rows) == [{'user':'a','ts':1,'value':'second'}]"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(rows: list[dict]) -> list[dict]。每行有 user、ts、value。对每个 user 保留 ts 最大的一行；若 ts 相同，保留在输入中更靠后的行。输出按 user 字典序排序。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "2a9a2d40a756627e38d28a8ac6afc98311acbafa718d7b3aaaecbedb9f020179", "started_at": "2026-06-16T12:03:35.727067+00:00", "latency_ms": 7709, "output": "```python\ndef solve(rows: list[dict]) -> list[dict]:\n best = {}\n for row in rows:\n user = row['user']\n ts = row['ts']\n if user not in best or ts >= best[user]['ts']:\n best[user] = row\n return [best[u] for u in sorted(best)]\n```", "usage": {"prompt_tokens": 94, "completion_tokens": 417, "total_tokens": 511, "cost": 0.001457695, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.001457695, "upstream_inference_prompt_cost": 0.0001504, "upstream_inference_completions_cost": 0.001307295}, "completion_tokens_details": {"reasoning_tokens": 337, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611417-F6vOw6sbeNYKncNsuaMH", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-001", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "iterator-default", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*def\\s+summarize\\(items=None\\)\\s*:", "flags": "is"}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面代码在 total 之后再次读取数据会变成空列表。请指出根因，并给出最小修复。最后单独一行写 FIX: <修复后的第一行函数定义>。\n\n```python\ndef summarize(items=iter([1, 2, 3])):\n return sum(items)\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "7b02a617eebe49b179cee84c9b8347c6bebe382f42a2b199d92b3aa9ed844102", "started_at": "2026-06-16T12:03:43.481629+00:00", "latency_ms": 25804, "output": "根本原因：`iter([1, 2, 3])` 作为默认参数只在函数定义时求值一次，返回的迭代器在第一次 `sum(items)` 调用时就被消耗完了。后续调用时迭代器已经耗尽，`sum()` 返回 0。\n\n最小修复：将默认值改为 `None`，在函数内部创建新的迭代器。\n\n```python\ndef summarize(items=None):\n if items is None:\n items = [1, 2, 3]\n return sum(items)\n```\n\nFIX: def summarize(items=None):", "usage": {"prompt_tokens": 93, "completion_tokens": 120, "total_tokens": 213, "cost": 0.0004329, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0004329, "upstream_inference_prompt_cost": 0.0001209, "upstream_inference_completions_cost": 0.000312}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611425-4aiZ7e7h9PC258igrlBI", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*def\\s+summarize\\(items=None\\)\\s*:"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-002", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "defaultdict", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*counts\\s*=\\s*defaultdict\\(lambda\\s*:\\s*\\{'seen'\\s*:\\s*\\[\\]\\}\\)\\s*`?", "flags": "is"}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面代码期望统计每个用户的事件数，但所有用户计数会互相影响。请指出根因，并给出最小修复。最后单独一行写 FIX: <修复后的 defaultdict 初始化行>。\n\n```python\nfrom collections import defaultdict\nshared = {'seen': []}\ncounts = defaultdict(lambda: shared)\n\ndef add(user, event):\n counts[user]['seen'].append(event)\n return counts[user]\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "fc1eb426cf811456432a61a306862f8bf804417edb8c8fca6dd3b86c1f9a9940", "started_at": "2026-06-16T12:04:09.297598+00:00", "latency_ms": 6280, "output": "根因是 `defaultdict` 的工厂函数 `lambda: shared` 始终返回同一个字典对象 `shared`，导致所有用户共享同一个 `'seen'` 列表。 \n最小修复：将工厂函数改为返回独立的新字典，即 `lambda: {'seen': []}`。\n\nFIX: counts = defaultdict(lambda: {'seen': []})", "usage": {"prompt_tokens": 118, "completion_tokens": 257, "total_tokens": 375, "cost": 0.00054984, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00054984, "upstream_inference_prompt_cost": 0.00010266, "upstream_inference_completions_cost": 0.00044718}, "completion_tokens_details": {"reasoning_tokens": 181, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611451-6ifv5sPAipz59HoKYPhW", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*counts\\s*=\\s*defaultdict\\(lambda\\s*:\\s*\\{'seen'\\s*:\\s*\\[\\]\\}\\)\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-003", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "off-by-one", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*for\\s+start\\s+in\\s+range\\(0,\\s*len\\(items\\),\\s*page_size\\)\\s*:", "flags": "is"}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面分页代码会漏掉最后不足 page_size 的一页。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 range 行>。\n\n```python\ndef pages(items, page_size):\n out = []\n for start in range(0, len(items) - page_size, page_size):\n out.append(items[start:start + page_size])\n return out\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "c6fe209d60968a3b2d253a065c8ce8255865f73575665a685d957cb52ce82011", "started_at": "2026-06-16T12:04:15.591732+00:00", "latency_ms": 2058, "output": "The bug is that `range(0, len(items) - page_size, page_size)` stops too early when `len(items)` is not a multiple of `page_size`. \nFor example, if `len(items) = 10` and `page_size = 3`, the range generates `0, 3, 6` and stops before `9`, missing the last page `[9:10]`.\n\n**Fix:** Change the stop value to `len(items)` so the last start index is included.\n\nFIX: `for start in range(0, len(items), page_size):`", "usage": {"prompt_tokens": 116, "completion_tokens": 125, "total_tokens": 241, "cost": 0.00063684, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00063684, "upstream_inference_prompt_cost": 0.00020184, "upstream_inference_completions_cost": 0.000435}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611458-iA7M0guhosMZEg9oSsoV", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*for\\s+start\\s+in\\s+range\\(0,\\s*len\\(items\\),\\s*page_size\\)\\s*:"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-004", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "sorting", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*return\\s+sorted\\(ids,\\s*key\\s*=\\s*int\\)\\s*`?", "flags": "is"}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面代码期望把数字字符串按数值排序，但结果是字典序。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 return 行>。\n\n```python\ndef order(ids):\n return sorted(ids)\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "b3f10943f43eaa04524058b0dd7fb30cbd21740003559e79de619ae210a697e4", "started_at": "2026-06-16T12:04:17.662846+00:00", "latency_ms": 5751, "output": "Bug: `sorted(ids)` 默认按字符串字典序排序，例如 `\"10\" < \"2\"`，导致结果不符合数值顺序。 \n最小修复：为 `sorted` 指定 `key=int`，使比较基于整数值。 \nFIX: return sorted(ids, key=int)", "usage": {"prompt_tokens": 83, "completion_tokens": 280, "total_tokens": 363, "cost": 0.001033944, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.001033944, "upstream_inference_prompt_cost": 0.000133464, "upstream_inference_completions_cost": 0.00090048}, "completion_tokens_details": {"reasoning_tokens": 213, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611459-b6lYxshsPN4CO07h4VbK", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*return\\s+sorted\\(ids,\\s*key\\s*=\\s*int\\)\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-005", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "memoization", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*key\\s*=\\s*\\(fn\\.__name__,\\s*args,\\s*(?:tuple\\(sorted\\(kwargs\\.items\\(\\)\\)\\)|frozenset\\(kwargs\\.items\\(\\)\\))\\)\\s*`?", "flags": "is"}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面缓存装饰器会把不同参数的调用混在一起。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 key 赋值行>。\n\n```python\ncache = {}\ndef memo(fn):\n def wrapper(*args, **kwargs):\n key = fn.__name__\n if key not in cache:\n cache[key] = fn(*args, **kwargs)\n return cache[key]\n return wrapper\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "fdaf2df9bffeacf442086f01d24eb1fce336e874cebec386f24acd9175c42fc6", "started_at": "2026-06-16T12:04:23.422772+00:00", "latency_ms": 9102, "output": "缓存装饰器的 bug 在于 `key = fn.__name__` 仅使用函数名作为缓存键，忽略了调用参数。这导致不同参数的调用共享同一个缓存结果，第一次调用后的所有调用（无论参数如何）都会返回第一次的结果。\n\n最小修复是将参数信息也纳入缓存键，例如：\n```python\nkey = (fn.__name__, args, tuple(sorted(kwargs.items())))\n```\nFIX: key = (fn.__name__, args, tuple(sorted(kwargs.items())))", "usage": {"prompt_tokens": 121, "completion_tokens": 607, "total_tokens": 728, "cost": 0.0023229, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0023229, "upstream_inference_prompt_cost": 0.00021054, "upstream_inference_completions_cost": 0.00211236}, "completion_tokens_details": {"reasoning_tokens": 618, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611465-tM4S48xu9UqykgOGdjcx", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*key\\s*=\\s*\\(fn\\.__name__,\\s*args,\\s*(?:tuple\\(sorted\\(kwargs\\.items\\(\\)\\)\\)|frozenset\\(kwargs\\.items\\(\\)\\))\\)\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-006", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "aliasing", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*copied\\s*=\\s*(?:items\\.copy\\(\\)|items\\[:\\]|list\\(items\\))\\s*`?", "flags": "is"}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面代码期望浅拷贝列表后独立追加，但原列表也被修改。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 copy 行>。\n\n```python\ndef append_copy(items, value):\n copied = items\n copied.append(value)\n return copied\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "d79d9daa2c034ff1badc1d0951de62e17f2421bac20433e520a48c2992cae000", "started_at": "2026-06-16T12:04:32.539037+00:00", "latency_ms": 5684, "output": "Bug: `copied = items` 只是别名引用，没有创建新列表，因此对 `copied` 的修改会影响原列表。最小修复：使用浅拷贝。\n\nFIX: copied = items.copy()", "usage": {"prompt_tokens": 94, "completion_tokens": 146, "total_tokens": 240, "cost": 0.00033582, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00033582, "upstream_inference_prompt_cost": 8.178e-05, "upstream_inference_completions_cost": 0.00025404}, "completion_tokens_details": {"reasoning_tokens": 99, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611474-pCY61zIDeMOLJEqICjsW", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*copied\\s*=\\s*(?:items\\.copy\\(\\)|items\\[:\\]|list\\(items\\))\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-007", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "json", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*data\\s*=\\s*(payload\\s+if\\s+isinstance\\(payload,\\s*dict\\)\\s+else\\s+json\\.loads\\(payload\\)|json\\.loads\\(payload\\)\\s+if\\s+isinstance\\(payload,\\s*\\(str,\\s*bytes,\\s*bytearray\\)\\)\\s+else\\s+payload|json\\.loads\\(payload\\)\\s+if\\s+isinstance\\(payload,\\s*str\\)\\s+else\\s+payload)\\s*`?", "flags": "is"}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面代码期望解析 JSON 字符串，但传入已经是 dict 时会报错。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 data 赋值行>。\n\n```python\nimport json\n\ndef load(payload):\n data = json.loads(payload)\n return data['id']\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "dae0481dbfca35623cf6eaf5f44910cc59204edc238411f6ec1221586215b6a3", "started_at": "2026-06-16T12:04:38.238415+00:00", "latency_ms": 10450, "output": "`json.loads` 只接受 `str`、`bytes` 或 `bytearray`，当 `payload` 已经是 `dict` 时会抛出 `TypeError`。 \n最小修复是在解析前加一个类型判断：若已是 `dict`，直接使用；否则再用 `json.loads`。\n\n```python\ndef load(payload):\n data = payload if isinstance(payload, dict) else json.loads(payload)\n return data['id']\n```\n\nFIX: `data = payload if isinstance(payload, dict) else json.loads(payload)`", "usage": {"prompt_tokens": 98, "completion_tokens": 496, "total_tokens": 594, "cost": 0.0009483, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0009483, "upstream_inference_prompt_cost": 8.526e-05, "upstream_inference_completions_cost": 0.00086304}, "completion_tokens_details": {"reasoning_tokens": 374, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611480-WgwE6IBeATzmwViPbwTl", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*data\\s*=\\s*(payload\\s+if\\s+isinstance\\(payload,\\s*dict\\)\\s+else\\s+json\\.loads\\(payload\\)|json\\.loads\\(payload\\)\\s+if\\s+isinstance\\(payload,\\s*\\(str,\\s*bytes,\\s*bytearray\\)\\)\\s+else\\s+payload|json\\.loads\\(payload\\)\\s+if\\s+isinstance\\(payload,\\s*str\\)\\s+else\\s+payload)\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-008", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "finally", "debugging"], "scorer": "contains_any", "expected": {"answers": ["删除 finally 中的 return None", "去掉 finally 的 return None", "不要在 finally 里 return None", "remove return None", "去掉 finally 中的 return None", "删除或替换 finally 中的 return None", "去掉 finally 中的 `return None`", "删除或替换 finally 中的 `return None`", "删除 finally 块中的 `return None`", "删除 finally 块中的 return None", "删除 finally 中的 `return None`", "删除 `finally` 块中的 `return None`", "删除 `finally` 中的 `return None`", "删除 `finally: return None`", "将 `finally:` 中的 `return None` 删除", "finally 中的 return None 删除", "finally: 中的 return None 删除", "删除 finally 块中的 'return None'", "删除 finally 子句中的 `return None`", "删除 finally 子句中的 return None", "delete the line `return None` inside the finally block", "delete the line return None inside the finally block", "finally 块不应包含 return 语句", "finally 块不应包含 return", "finally 不应包含 return"]}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面代码期望 finally 后仍保留 try 中返回值，但实际总是返回 None。请指出 bug，并给出最小修复。最后单独一行写 FIX: <要删除或替换的 finally 行说明>。\n\n```python\ndef read_value():\n try:\n return 42\n finally:\n return None\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "3cc6ae8fe4f15528225f040b759f5535e31e0ee3dab226c836ed3b9c19707a57", "started_at": "2026-06-16T12:04:48.701941+00:00", "latency_ms": 12218, "output": "The bug is that a `return` statement inside a `finally` block overrides any return value from the `try` or `except` blocks. Therefore `finally: return None` always causes the function to return `None` instead of `42`.\n\nMinimal fix: remove the `return` from the `finally` block so that the original return value is preserved. For example, change to `finally: pass` or simply delete the line.\n\nFIX: delete the line `return None` inside the finally block", "usage": {"prompt_tokens": 99, "completion_tokens": 597, "total_tokens": 696, "cost": 0.00112491, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00112491, "upstream_inference_prompt_cost": 8.613e-05, "upstream_inference_completions_cost": 0.00103878}, "completion_tokens_details": {"reasoning_tokens": 490, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611491-zlvzJpmSU0l2SnHjTvH8", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"matched": ["delete the line `return None` inside the finally block"]}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-reasoning-001", "suite": "reasoning", "case_version": "0.2.0", "tags": ["arithmetic", "multi-step"], "scorer": "exact", "expected": {"answer": "125", "normalize": true}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只回答最终数字：有 A、B、C、D 四个服务。A 每分钟处理 6 个请求，B 比 A 少 2 个，C 是 B 的 2 倍，D 是 A 和 C 的平均值。四个服务 5 分钟一共处理多少请求？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "06f9a3eb3666e5854b2b742553674373622a42e326be166231a39c67b5604810", "started_at": "2026-06-16T12:05:00.933523+00:00", "latency_ms": 8779, "output": "125", "usage": {"prompt_tokens": 100, "completion_tokens": 164, "total_tokens": 264, "cost": 0.00037236, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00037236, "upstream_inference_prompt_cost": 8.7e-05, "upstream_inference_completions_cost": 0.00028536}, "completion_tokens_details": {"reasoning_tokens": 162, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611503-te55JkuGtCmT66L7yMN4", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "125", "actual": "125"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-reasoning-002", "suite": "reasoning", "case_version": "0.2.0", "tags": ["constraint-solving"], "scorer": "exact", "expected": {"answer": "D", "normalize": true}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只回答一个字母：五个任务 A、B、C、D、E 排队。A 必须在 B 前，B 必须在 C 前；D 不能在两端；E 必须紧挨在 C 后面。在所有满足条件的队列中，按字典序最小的队列第三个任务是谁？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e273e5a0cd57aef19af9e4ccfcd445a7523180f5cab62526c14aa0e62d5c1cc9", "started_at": "2026-06-16T12:05:09.728444+00:00", "latency_ms": 26632, "output": "D", "usage": {"prompt_tokens": 92, "completion_tokens": 1180, "total_tokens": 1272, "cost": 0.001864746, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.001864746, "upstream_inference_prompt_cost": 6.9966e-05, "upstream_inference_completions_cost": 0.00179478}, "completion_tokens_details": {"reasoning_tokens": 1177, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611512-vJ3gmKVqlw7nlWvtS8bF", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "D", "actual": "D"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-reasoning-003", "suite": "reasoning", "case_version": "0.2.0", "tags": ["binary", "symbolic"], "scorer": "exact", "expected": {"answer": "0", "normalize": true}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只回答最终数字：一个 4 位二进制数从 1011 开始，先左移一位并只保留低 4 位，再与 0110 做异或，最后转成十进制。结果是多少？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "813f5aead205f4aa7a9d2a1e7b7085daae002a54592edd8d8aad2e7d7551897c", "started_at": "2026-06-16T12:05:36.378518+00:00", "latency_ms": 1724, "output": "9", "usage": {"prompt_tokens": 79, "completion_tokens": 2, "total_tokens": 81, "cost": 0.00014442, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00014442, "upstream_inference_prompt_cost": 0.00013746, "upstream_inference_completions_cost": 6.96e-06}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611538-IhDKwrulxu9u0GKLhcjZ", "finish_reason": "stop", "score": {"passed": false, "score": 0.0, "details": {"expected": "0", "actual": "9"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-reasoning-004", "suite": "reasoning", "case_version": "0.2.0", "tags": ["set", "operations"], "scorer": "exact", "expected": {"answer": "18", "normalize": true}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只回答最终数字：一个集合最初为 {1,2,3,4,5}。依次执行：删除所有偶数；加入 6 和 7；把每个元素乘以 2；删除大于 10 的元素。最终集合元素之和是多少？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "3077e41c160e4ebe361234b76e647f42583619ef446b73e7c1e25858312f328e", "started_at": "2026-06-16T12:05:38.114610+00:00", "latency_ms": 1622, "output": "18", "usage": {"prompt_tokens": 85, "completion_tokens": 2, "total_tokens": 87, "cost": 0.00015486, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00015486, "upstream_inference_prompt_cost": 0.0001479, "upstream_inference_completions_cost": 6.96e-06}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611540-DSs537PbAnQz5Y0PjLfE", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "18", "actual": "18"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-reasoning-005", "suite": "reasoning", "case_version": "0.2.0", "tags": ["logic", "sat"], "scorer": "exact", "expected": {"answer": "可满足", "normalize": true}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只回答“可满足”或“不可满足”：有三个布尔变量 x、y、z。约束为：x 或 y 为真；如果 x 为真则 z 为假；如果 y 为真则 z 为真；x 和 y 不能同时为真。是否存在赋值满足全部约束？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "1e534bd21af5e75f0c9fd61e3d5a3f660355d4555e34e16a06744234da47e006", "started_at": "2026-06-16T12:05:39.749099+00:00", "latency_ms": 6562, "output": "可满足", "usage": {"prompt_tokens": 98, "completion_tokens": 301, "total_tokens": 399, "cost": 0.000609, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.000609, "upstream_inference_prompt_cost": 8.526e-05, "upstream_inference_completions_cost": 0.00052374}, "completion_tokens_details": {"reasoning_tokens": 298, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611542-lRmztogmlaYavU79FjZf", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "可满足", "actual": "可满足"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-001", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "grounded"], "scorer": "text_rules", "expected": {"required": ["人工抽检"], "required_any": [["默认使用", "默认判分", "默认采用", "作为默认判分"]], "forbidden": ["因为成本太高", "因为不支持中文"], "max_chars": 160}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只根据资料回答。\n\n资料 A：DracoBench v0.2 的目标是提高区分度，优先增加 coding、debugging、RAG 和 instruction_following 题。\n资料 B：DracoBench v0.2 不会默认使用 LLM-as-judge；开放中文写作题只做少量规则校验和人工抽检。\n资料 C：v0.2 的 HTML 报告必须展示通过率、成本、reasoning tokens、失败样例和逐题明细。\n\n问题：v0.2 为什么没有把 LLM-as-judge 作为默认判分？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "7a40b395b42a59b621957d70755d39fca26dba23f4e0c46743018935350319d3", "started_at": "2026-06-16T12:05:46.325736+00:00", "latency_ms": 4539, "output": "资料未说明原因。", "usage": {"prompt_tokens": 154, "completion_tokens": 147, "total_tokens": 301, "cost": 0.00038976, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00038976, "upstream_inference_prompt_cost": 0.00013398, "upstream_inference_completions_cost": 0.00025578}, "completion_tokens_details": {"reasoning_tokens": 141, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611548-C2tdktBtEp7KC2Un5TC7", "finish_reason": "stop", "score": {"passed": false, "score": 0.0, "details": {"missing": ["人工抽检"], "missing_any": [["默认使用", "默认判分", "默认采用", "作为默认判分"]], "present_forbidden": [], "char_count": 8, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-002", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "tradeoff", "abstain"], "scorer": "text_rules", "expected": {"required": ["Beta", "成本", "延迟", "判断"], "forbidden": ["Alpha 更适合", "多模态更强"], "max_chars": 180}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只根据资料回答，不要自行补充。\n\n资料：模型 Alpha 在 30 道 challenge 题中通过 24 道，成本 0.08 美元，平均延迟 9 秒。模型 Beta 通过 22 道，成本 0.02 美元，平均延迟 3 秒。资料没有给出两者在多模态任务上的表现。\n\n问题：如果要写低成本高吞吐摘要服务，资料更支持选择哪个模型？另外，多模态表现能否判断？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "b25dfce277314b219ab8ccef6f02fb644e23cd169765867993ae58ccd7258c4a", "started_at": "2026-06-16T12:05:50.879087+00:00", "latency_ms": 4490, "output": "根据资料，模型 Beta 成本更低（0.02 美元）且平均延迟更短（3 秒），更适合低成本高吞吐的摘要服务。多模态表现无法判断，因为资料未提供相关信息。", "usage": {"prompt_tokens": 132, "completion_tokens": 160, "total_tokens": 292, "cost": 0.00039324, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00039324, "upstream_inference_prompt_cost": 0.00011484, "upstream_inference_completions_cost": 0.0002784}, "completion_tokens_details": {"reasoning_tokens": 114, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611553-mbTrNwECQoMn2AWOkTBj", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 76, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-003", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "nuance"], "scorer": "text_rules", "expected": {"required": ["题面歧义"], "required_any": [["47/50", "47 题", "47题"], ["空输出", "输出为空", "未输出"]], "forbidden": ["满分", "完全失败"], "max_chars": 240}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只根据资料回答。\n\n资料：一次评测中，K 模型在 smoke set 上 7/7，通过率 100%；在 hard set 上原始结果 47/50，其中 2 题后来被认定为题面歧义，单独复测通过。另有 1 题因 reasoning tokens 用尽而空输出。\n\n问题：更公平的文字结论应该如何描述 K 模型这次 hard set 表现？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "12db30955792c48368632f01aa0a9c06e9fc27004c4dbf12ce602cb8488494e6", "started_at": "2026-06-16T12:05:55.381421+00:00", "latency_ms": 16921, "output": "在排除两道存在题面歧义的题目后，K 模型在 hard set 剩余 48 道有效题中正确作答 47 题，仅 1 题因 reasoning tokens 耗尽导致空输出未能通过。", "usage": {"prompt_tokens": 120, "completion_tokens": 750, "total_tokens": 870, "cost": 0.0014094, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0014094, "upstream_inference_prompt_cost": 0.0001044, "upstream_inference_completions_cost": 0.001305}, "completion_tokens_details": {"reasoning_tokens": 700, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611557-ubob55dNS7AABcnXDQi3", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 88, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-004", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "abstain"], "scorer": "text_rules", "expected": {"required": ["不能", "不包含", "利润率"], "forbidden": ["可以判断", "训练数据"], "max_chars": 100}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只根据资料回答，不要使用资料外知识。\n\n资料：报告字段包括 pass_rate、avg_latency_ms、total_cost、prompt_tokens、completion_tokens、reasoning_tokens。报告不包含模型训练数据来源，也不包含供应商真实利润率。\n\n问题：根据资料，能否从报告判断供应商利润率？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "cb2d9baeb98b0b4836972058965359b461f03aaba6cd096f40ffc813ce331880", "started_at": "2026-06-16T12:06:12.317975+00:00", "latency_ms": 20605, "output": "不能。", "usage": {"prompt_tokens": 98, "completion_tokens": 56, "total_tokens": 154, "cost": 0.00035392, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00035392, "upstream_inference_prompt_cost": 0.00016464, "upstream_inference_completions_cost": 0.00018928}, "completion_tokens_details": {"reasoning_tokens": 53, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611574-XyVW9YfEvqdcMEkRD8Bx", "finish_reason": "stop", "score": {"passed": false, "score": 0.0, "details": {"missing": ["不包含", "利润率"], "missing_any": [], "present_forbidden": [], "char_count": 3, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-if-001", "suite": "instruction_following", "case_version": "0.2.0", "tags": ["json", "nested"], "scorer": "json_schema_lite", "expected": {"schema": {"type": "object", "required": ["status", "scores", "note"], "additionalProperties": false, "properties": {"status": {"type": "string", "const": "review"}, "scores": {"type": "object", "required": ["coding", "debugging", "rag"], "additionalProperties": false, "properties": {"coding": {"type": "integer"}, "debugging": {"type": "integer"}, "rag": {"type": "integer"}}}, "note": {"type": "string"}}}}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 JSON 对象，不要 Markdown。字段 status 必须是 \"review\"；字段 scores 必须是对象，包含 coding、debugging、rag 三个整数；字段 note 必须是不超过 12 个汉字的中文字符串。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "7f670ae329c67bf1957a977815256b403ae7965cb15f2d2db520256cc3f2eb77", "started_at": "2026-06-16T12:06:32.935827+00:00", "latency_ms": 7060, "output": "{\"status\": \"review\", \"scores\": {\"coding\": 8, \"debugging\": 7, \"rag\": 9}, \"note\": \"综合能力良好\"}", "usage": {"prompt_tokens": 80, "completion_tokens": 208, "total_tokens": 288, "cost": 0.000927968, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.000927968, "upstream_inference_prompt_cost": 0.0001384, "upstream_inference_completions_cost": 0.000789568}, "completion_tokens_details": 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"model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "写一段不超过 120 个汉字的公众号结论，主题是“模型在简单题满分不代表真实强”。必须包含“简单题”“真实能力”“失败样例”，不能出现“吊打”。", "parameters": {"temperature": 0.2, "max_tokens": 16384, "seed": null}, "prompt_hash": "f330d4a7913b830c15df0d2a36cf0a9e5c07628ef6fa52408cc1bd2e90074762", "started_at": "2026-06-16T12:06:51.084544+00:00", "latency_ms": 1527, "output": "模型在简单题拿满分，不代表真实能力强。许多系统能轻松应对基础问答，却在复杂推理中暴露短板。真正的考验来自失败样例——那些看似简单却暗藏逻辑陷阱的题目，才是衡量真实能力的试金石。", "usage": {"prompt_tokens": 71, "completion_tokens": 51, "total_tokens": 122, "cost": 0.00030102, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00030102, "upstream_inference_prompt_cost": 0.00012354, "upstream_inference_completions_cost": 0.00017748}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611613-cbkJXzUGZJ9kZ7wHh51y", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 88, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-zh-writing-002", "suite": "chinese_writing", "case_version": "0.2.0", "tags": ["rewrite", "zh"], "scorer": "text_rules", "expected": {"required": ["复杂调试", "稳定性"], "forbidden": ["猛", "掉链子"], "max_chars": 80}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "把下面口语句改写成专业表达，不超过 80 个汉字：这个模型看起来很猛，但一遇到复杂调试就开始掉链子。必须包含“复杂调试”和“稳定性”，不能包含“猛”“掉链子”。", "parameters": {"temperature": 0.2, "max_tokens": 16384, "seed": null}, "prompt_hash": "1628d5e9cbea22d0750b547f0818eafa82d503dcad8fdc41ef2f523f9fbb55a1", "started_at": "2026-06-16T12:06:52.617080+00:00", "latency_ms": 9149, "output": "模型表面性能强劲，复杂调试场景下稳定性显著不足。", "usage": {"prompt_tokens": 79, "completion_tokens": 116, "total_tokens": 195, "cost": 0.00039497, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00039497, "upstream_inference_prompt_cost": 0.00010033, "upstream_inference_completions_cost": 0.00029464}, "completion_tokens_details": {"reasoning_tokens": 102, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611614-csT98P5pZwYfBcCe8hGd", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 24, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-009", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "aggregation", "dirty-input"], "scorer": "code_python_tests", "expected": {"tests": ["events=[{'user':'b','type':'add','amount':'5'},{'user':'a','type':'add','amount':3},{'user':'b','type':'remove','amount':2},{'user':'a','type':'remove','amount':3}]\nassert solution.solve(events) == {'b': 3}", "assert solution.solve([]) == {}", "assert solution.solve([{'user':'x','type':'remove','amount':'2'}]) == {'x': -2}"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(events: list[dict]) -> dict[str, int]。每个事件包含 user、type、amount；type 为 \"add\" 或 \"remove\"。按 user 汇总 add 减 remove 后的库存，结果中去掉库存为 0 的用户，按 key 字典序返回普通 dict。amount 可能是字符串数字。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "9b81c7f8e34dbf12cfabd35ebb618802fe09200deca1d146558b4e1c12e6fd1e", "started_at": "2026-06-16T12:07:01.780110+00:00", "latency_ms": 6372, "output": "```python\ndef solve(events: list[dict]) -> dict[str, int]:\n stock = {}\n for e in events:\n user = e[\"user\"]\n amount = int(e[\"amount\"])\n if e[\"type\"] == \"add\":\n stock[user] = stock.get(user, 0) + amount\n else: # remove\n stock[user] = stock.get(user, 0) - amount\n # 去掉库存为0的用户\n result = {k: v for k, v in stock.items() if v != 0}\n # 按键字典序排序，返回普通dict\n return dict(sorted(result.items()))\n```", "usage": {"prompt_tokens": 110, "completion_tokens": 249, "total_tokens": 359, "cost": 0.0009728, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0009728, "upstream_inference_prompt_cost": 0.000176, "upstream_inference_completions_cost": 0.0007968}, "completion_tokens_details": {"reasoning_tokens": 105, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611624-s1T9BbXEJGAC8RjirwSK", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-010", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "parser", "expression"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('1 + 2 - 3') == 0", "assert solution.solve('10 - (2 + 3) + 4') == 9", "assert solution.solve('(1+(4+5+2)-3)+(6+8)') == 23"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(expr: str) -> int。expr 只包含非负整数、+、-、空格和括号，计算表达式结果。不要使用 eval。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "662cadd9b4e3fdcfdf38e1d7338201fe3049d948576c89303695cff58950b3b4", "started_at": "2026-06-16T12:07:08.203037+00:00", "latency_ms": 61705, "output": "```python\ndef solve(expr: str) -> int:\n s = expr.replace(' ', '')\n i = 0\n n = len(s)\n\n def helper():\n nonlocal i\n stack = []\n sign = 1\n while i < n and s[i] != ')':\n if s[i].isdigit():\n num = 0\n while i < n and s[i].isdigit():\n num = num * 10 + int(s[i])\n i += 1\n stack.append(sign * num)\n elif s[i] == '+':\n sign = 1\n i += 1\n elif s[i] == '-':\n sign = -1\n i += 1\n elif s[i] == '(':\n i += 1\n num = helper()\n stack.append(sign * num)\n i += 1 # skip ')'\n return sum(stack)\n\n return helper()\n```", "usage": {"prompt_tokens": 72, "completion_tokens": 2507, "total_tokens": 2579, "cost": 0.007974645, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.007974645, "upstream_inference_prompt_cost": 0.0001152, "upstream_inference_completions_cost": 0.007859445}, "completion_tokens_details": {"reasoning_tokens": 2301, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611630-W2iEep69fyp6RjVZqWha", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-011", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "sorting", "dedupe"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve(['alice 10','bob 12','alice 15','','bob 11']) == [('alice',15),('bob',12)]", "assert solution.solve(['x -1','a -1','b 0']) == [('b',0),('a',-1),('x',-1)]"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(rows: list[str]) -> list[tuple[str, int]]。每行格式为 \"name score\"，空白数量不定；同名保留最高分；输出按分数降序、同分按 name 升序。忽略空行。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "332bccf5652506856c633d7093431279279a22b2d3a99762f6cba55df7d884af", "started_at": "2026-06-16T12:08:09.957827+00:00", "latency_ms": 25158, "output": "```python\ndef solve(rows):\n max_scores = {}\n for line in rows:\n line = line.strip()\n if not line:\n continue\n parts = line.split()\n if len(parts) != 2:\n continue\n name, score_str = parts\n score = int(score_str)\n if name not in max_scores or score > max_scores[name]:\n max_scores[name] = score\n return sorted(max_scores.items(), key=lambda x: (-x[1], x[0]))\n```", "usage": {"prompt_tokens": 90, "completion_tokens": 555, "total_tokens": 645, "cost": 0.00226248, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00226248, "upstream_inference_prompt_cost": 0.0001557, "upstream_inference_completions_cost": 0.00210678}, "completion_tokens_details": {"reasoning_tokens": 437, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611692-mn2V2M4hbYvMq1RcCmek", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-012", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "wildcard", "dp"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('a*b?d', 'axxxbc d'.replace(' ','')) is True", "assert solution.solve('a*c', 'ab') is False", "assert solution.solve('*', '') is True", "assert solution.solve('file-??.txt', 'file-ab.txt') is True"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(pattern: str, text: str) -> bool。pattern 支持 ? 匹配任意单字符，* 匹配任意长度字符串。必须匹配完整 text。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "0ac24584e5856726a6e962c43819ac539910b115bdabb48f973f04258dd562d6", "started_at": "2026-06-16T12:08:35.160747+00:00", "latency_ms": 8273, "output": "```python\ndef solve(pattern: str, text: str) -> bool:\n m, n = len(pattern), len(text)\n dp = [[False] * (n + 1) for _ in range(m + 1)]\n dp[0][0] = True\n for i in range(1, m + 1):\n if pattern[i-1] == '*':\n dp[i][0] = dp[i-1][0]\n else:\n break\n for i in range(1, m + 1):\n for j in range(1, n + 1):\n if pattern[i-1] == '*':\n dp[i][j] = dp[i-1][j] or dp[i][j-1]\n elif pattern[i-1] == '?' or pattern[i-1] == text[j-1]:\n dp[i][j] = dp[i-1][j-1]\n return dp[m][n]\n```", "usage": {"prompt_tokens": 73, "completion_tokens": 272, "total_tokens": 345, "cost": 0.00096952, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00096952, "upstream_inference_prompt_cost": 0.0001168, "upstream_inference_completions_cost": 0.00085272}, "completion_tokens_details": {"reasoning_tokens": 64, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611717-gwZ5aneb1YRZ80fdiRcF", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-013", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "recursion", "flatten"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve({'a': {'b': 1, 'c': 'x'}, 'd': 2}) == ['a.b=1','a.c=x','d=2']", "assert solution.solve({'z': {'a': {'b': 3}}}) == ['z.a.b=3']", "assert solution.solve({}) == []"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(tree: dict) -> list[str]。tree 是嵌套字典，叶子是字符串或数字。返回所有叶子的路径，路径用点连接，按字典序排序。例如 {'a': {'b': 1}} -> ['a.b=1']。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e658784bcc7118c9f5e1375c7f1f92aa8147c38fb8790138603de7f2b3722c98", "started_at": "2026-06-16T12:08:43.479710+00:00", "latency_ms": 19463, "output": "```python\ndef solve(tree: dict) -> list[str]:\n result = []\n def dfs(node, path):\n if not isinstance(node, dict):\n result.append('.'.join(path) + '=' + str(node))\n return\n for key in sorted(node.keys()):\n path.append(key)\n dfs(node[key], path)\n path.pop()\n dfs(tree, [])\n result.sort()\n return result\n```", "usage": {"prompt_tokens": 94, "completion_tokens": 693, "total_tokens": 787, "cost": 0.00112554, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00112554, "upstream_inference_prompt_cost": 7.1487e-05, "upstream_inference_completions_cost": 0.001054053}, "completion_tokens_details": {"reasoning_tokens": 601, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611725-XAfIKIFptiKdYqvGneu9", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-014", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "dynamic-programming"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve([1,-2,0,3]) == 4", "assert solution.solve([1,-2,-2,3]) == 3", "assert solution.solve([-1,-1,-1]) == -1", "assert solution.solve([2,1,-2,3]) == 6"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(nums: list[int]) -> int。返回删除恰好一个元素后，剩余数组的最大连续子数组和。nums 长度至少为 2，可以全为负数。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "a7a5de11dacd1864c7d44a3ce983c2f127d1bcff88bec3b15f8727c513f56ea2", "started_at": "2026-06-16T12:09:02.989058+00:00", "latency_ms": 10173, "output": "```python\ndef solve(nums: list[int]) -> int:\n n = len(nums)\n if n == 2:\n return max(nums[0], nums[1])\n \n left = [0] * n\n left[0] = nums[0]\n for i in range(1, n):\n left[i] = max(nums[i], left[i-1] + nums[i])\n \n right = [0] * n\n right[-1] = nums[-1]\n for i in range(n-2, -1, -1):\n right[i] = max(nums[i], right[i+1] + nums[i])\n \n ans = max(left[-2], right[1])\n for i in range(1, n-1):\n ans = max(ans, left[i-1] + right[i+1])\n \n return ans\n```", "usage": {"prompt_tokens": 76, "completion_tokens": 187, "total_tokens": 263, "cost": 0.0005715, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0005715, "upstream_inference_prompt_cost": 9.652e-05, "upstream_inference_completions_cost": 0.00047498}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611745-aH14DBvhugBxMFVo7Km7", "finish_reason": "stop", "score": {"passed": false, "score": 0.0, "details": {"returncode": 1, "stdout": "", "stderr": "Traceback (most recent call last):\n File \"/var/folders/x_/4cht1kfj1_j31gdv5w01sgmw0000gn/T/dracobench-code-cmk_uboc/test_solution.py\", line 4, in \n assert solution.solve([1,-2,-2,3]) == 3\nAssertionError\n"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-009", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "parsing", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*return\\s+\\[part\\.strip\\(\\)\\s+for\\s+part\\s+in\\s+s\\.split\\('\\,'\\)\\s+if\\s+part\\.strip\\(\\)\\]\\s*`?", "flags": "is"}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面代码期望把输入按逗号拆分并去掉空白，但会把空字段也保留下来。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 return 行>。\n\n```python\ndef parse(s):\n return [part.strip() for part in s.split(',')]\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "fc78c43e70a6a2fe59904be00b93d579300af6ba72fe5a9629bfe5bd82fad3d6", "started_at": "2026-06-16T12:09:13.207933+00:00", "latency_ms": 9340, "output": "该代码的 bug 在于列表推导式没有过滤空字段：`s.split(',')` 会保留连续逗号产生的空字符串，`strip()` 无法去除这些空字段，因此最终结果中仍会包含空字符串。\n\n最小修复是增加一个条件，过滤掉 `strip()` 后为空的字段：\n\n```python\ndef parse(s):\n return [part.strip() for part in s.split(',') if part.strip()]\n```\n\nFIX: return [part.strip() for part in s.split(',') if part.strip()]", "usage": {"prompt_tokens": 96, "completion_tokens": 465, "total_tokens": 561, "cost": 0.0016416, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0016416, "upstream_inference_prompt_cost": 0.0001536, "upstream_inference_completions_cost": 0.001488}, "completion_tokens_details": {"reasoning_tokens": 351, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611755-YytBNC0V1D1hhf9cWhWk", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*return\\s+\\[part\\.strip\\(\\)\\s+for\\s+part\\s+in\\s+s\\.split\\('\\,'\\)\\s+if\\s+part\\.strip\\(\\)\\]\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-010", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "datetime", "debugging"], "scorer": "contains_any", "expected": {"answers": ["datetime.fromisoformat", "dateutil.parser", "解析 ts 后排序", "parse ts", "fromisoformat", "int(r['ts'])", "float(r['ts'])", "key=lambda r: int(r['ts'])", "key=lambda r: float(r['ts'])"]}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面代码期望用 UTC 时间戳排序，但字符串排序会错。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 sort 行>。\n\n```python\nrows.sort(key=lambda r: r['ts'])\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "c0d491a68f215902d8b314423a6ab9aea7ac0782e1a34e6d6997670c2ddb8458", "started_at": "2026-06-16T12:09:22.560220+00:00", "latency_ms": 31464, "output": "Bug：`r['ts']` 是字符串格式的时间戳，直接按字符串排序会使用字典序而非时序，导致跨长度（如 9 位与 10 位 Unix 时间戳）或非零填充日期时顺序错乱。 \n最小修复：将字符串转换为数值或日期时间对象再比较。若 `ts` 是 Unix 时间戳字符串，转 `float`；若是 ISO 格式，用 `datetime.fromisoformat` 解析。常见场景为数字字符串，修复如下：\n\nFIX: rows.sort(key=lambda r: float(r['ts']))", "usage": {"prompt_tokens": 83, "completion_tokens": 1378, "total_tokens": 1461, "cost": 0.00360553, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00360553, "upstream_inference_prompt_cost": 0.00010541, "upstream_inference_completions_cost": 0.00350012}, "completion_tokens_details": {"reasoning_tokens": 1252, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611764-V5eHOMhoAMNDLRbomUh8", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"matched": ["datetime.fromisoformat", "fromisoformat", "float(r['ts'])", "key=lambda r: float(r['ts'])"]}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-011", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "truthiness", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*(?:limit\\s*=\\s*10\\s+if\\s+limit\\s+is\\s+None\\s+else\\s+limit|limit\\s*=\\s*limit\\s+if\\s+limit\\s+is\\s+not\\s+None\\s+else\\s+10|if\\s+limit\\s+is\\s+None\\s*:\\s*limit\\s*=\\s*10)\\s*`?", "flags": "is"}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面代码在输入包含 0 时会误判为默认值 10。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 limit 赋值行>。\n\n```python\ndef query(limit=None):\n limit = limit or 10\n return list(range(limit))\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "81dfcde4613fe16d52b7386d005b50beaafcb9916e6cb6c0d326eab3c808a843", "started_at": "2026-06-16T12:09:54.038607+00:00", "latency_ms": 23374, "output": "问题在于 `limit = limit or 10` 使用了布尔短路运算：当 `limit` 为 `0`、空字符串等假值时，都会返回默认值 `10`，而不仅仅是 `None`。题目中 `limit=0` 是合法输入，却被误判成 `10`。\n\n最小修复：使用显式 `is None` 判断，只在参数未提供时才使用默认值。\n\n```python\ndef query(limit=None):\n limit = 10 if limit is None else limit\n return list(range(limit))\n```\n\nFIX: limit = 10 if limit is None else limit", "usage": {"prompt_tokens": 96, "completion_tokens": 518, "total_tokens": 614, "cost": 0.00191212, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00191212, "upstream_inference_prompt_cost": 0.00016128, "upstream_inference_completions_cost": 0.00175084}, "completion_tokens_details": {"reasoning_tokens": 387, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611796-gRVPOiHfvYz49zpExEfu", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*(?:limit\\s*=\\s*10\\s+if\\s+limit\\s+is\\s+None\\s+else\\s+limit|limit\\s*=\\s*limit\\s+if\\s+limit\\s+is\\s+not\\s+None\\s+else\\s+10|if\\s+limit\\s+is\\s+None\\s*:\\s*limit\\s*=\\s*10)\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-012", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "deepcopy", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*copied\\s*=\\s*(?:copy\\.deepcopy\\(config\\)|__import__\\(['\\\"]copy['\\\"]\\)\\.deepcopy\\(config\\))\\s*`?", "flags": "is"}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面代码期望复制嵌套配置后修改副本，但原配置也被修改。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 copied 赋值行>。\n\n```python\ndef update(config):\n copied = dict(config)\n copied['db']['host'] = 'localhost'\n return copied\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "b9ce1efc39e6db4861310a8b269b4f7a5f68b90016ca7ebbef71eb8b6b011913", "started_at": "2026-06-16T12:10:17.428869+00:00", "latency_ms": 18952, "output": "该 bug 是由于 `dict(config)` 只进行了浅拷贝：顶层字典是新的，但内部嵌套的可变对象（如 `db` 字典）仍与原配置共享同一个引用。因此修改 `copied['db']['host']` 会直接改动原配置的 `db` 对象。\n\n最小修复是对整个配置进行深拷贝。需要引入 `copy` 模块，并使用 `copy.deepcopy` 替代 `dict()`。\n\nFIX: copied = copy.deepcopy(config)", "usage": {"prompt_tokens": 99, "completion_tokens": 490, "total_tokens": 589, "cost": 0.00169455, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00169455, "upstream_inference_prompt_cost": 0.0001584, "upstream_inference_completions_cost": 0.00153615}, "completion_tokens_details": {"reasoning_tokens": 385, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611819-EJhGuYy1SfGXQCNrfqw5", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*copied\\s*=\\s*(?:copy\\.deepcopy\\(config\\)|__import__\\(['\\\"]copy['\\\"]\\)\\.deepcopy\\(config\\))\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-013", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "generator", "debugging"], "scorer": "regex", "expected": {"pattern": "\\*{0,2}FIX\\*{0,2}:\\*{0,2}\\s*`?\\s*return\\s+next\\(\\(u\\s+for\\s+u\\s+in\\s+users\\s+if\\s+u\\['name'\\]\\s*==\\s*name\\),\\s*None\\)\\s*`?", "flags": "is"}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面代码期望找到第一个匹配项，但找不到时会抛 StopIteration。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 return 行>。\n\n```python\ndef find_user(users, name):\n return next(u for u in users if u['name'] == name)\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "3f10be3c52149f96743fe37c0fb7327abfb5c8d4b9310088d76b04282b552f5b", "started_at": "2026-06-16T12:10:36.395813+00:00", "latency_ms": 11968, "output": "代码中的 `next()` 在生成器耗尽时会抛出 `StopIteration` 异常，而不是返回一个表示“未找到”的值。最小修复是为 `next()` 提供一个默认值（如 `None`），使其在找不到匹配项时返回该默认值。\n\nFIX: return next((u for u in users if u['name'] == name), None)", "usage": {"prompt_tokens": 97, "completion_tokens": 282, "total_tokens": 379, "cost": 0.00115014, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00115014, "upstream_inference_prompt_cost": 0.00016878, "upstream_inference_completions_cost": 0.00098136}, "completion_tokens_details": {"reasoning_tokens": 248, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611838-IwMmKW6eOFHXMGaAxVRg", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "\\*{0,2}FIX\\*{0,2}:\\*{0,2}\\s*`?\\s*return\\s+next\\(\\(u\\s+for\\s+u\\s+in\\s+users\\s+if\\s+u\\['name'\\]\\s*==\\s*name\\),\\s*None\\)\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-014", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "mutable-default", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*(?:```(?:python)?\\s*)?`?\\s*def\\s+log_request\\(req,\\s*logs=None\\)\\s*:", "flags": "is"}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面代码期望按请求顺序记录日志，但默认参数导致多次调用共用同一个列表。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的函数定义行>。\n\n```python\ndef log_request(req, logs=[]):\n logs.append(req['id'])\n return logs\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "2131fc867d62d7093265e77811a401805ff12d38e7bbdc5e8797b3d01b4c8c59", "started_at": "2026-06-16T12:10:48.379121+00:00", "latency_ms": 27857, "output": "代码的 bug 在于使用空列表 `[]` 作为默认参数。Python 只在函数定义时对默认参数求值一次，因此多次不带 `logs` 参数的调用会共享同一个列表对象，导致所有调用都往同一个列表追加，返回结果互相干扰。\n\n最小修复是将默认值改为 `None`，在函数体内再实例化新列表。修复后的函数定义行为：\n\nFIX: ```def log_request(req, logs=None):```", "usage": {"prompt_tokens": 96, "completion_tokens": 1036, "total_tokens": 1132, "cost": 0.0034688, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0034688, "upstream_inference_prompt_cost": 0.0001536, "upstream_inference_completions_cost": 0.0033152}, "completion_tokens_details": {"reasoning_tokens": 939, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611850-Lr8Af5K53YS8AB95SSzY", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*(?:```(?:python)?\\s*)?`?\\s*def\\s+log_request\\(req,\\s*logs=None\\)\\s*:"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-reasoning-006", "suite": "reasoning", "case_version": "0.2.0", "tags": ["symbolic", "sequence"], "scorer": "exact", "expected": {"answer": "3", "normalize": true}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只回答最终数字：一个队列从左到右是 A,B,C,D,E。依次执行：把第 2 个移到末尾；删除第 3 个；在最前面插入 X；把最后两个反转。最终队列中 C 的位置是第几位？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "0defd3c3114d287777b39b65961dfa6fd7469da02e6c49a8c170b4f1be17f971", "started_at": "2026-06-16T12:11:16.252751+00:00", "latency_ms": 7374, "output": "3", "usage": {"prompt_tokens": 85, "completion_tokens": 267, "total_tokens": 352, "cost": 0.00053853, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00053853, "upstream_inference_prompt_cost": 7.395e-05, "upstream_inference_completions_cost": 0.00046458}, "completion_tokens_details": {"reasoning_tokens": 264, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611878-mrj8IvCcZAl2UzG7qGnx", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "3", "actual": "3"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-reasoning-007", "suite": "reasoning", "case_version": "0.2.0", "tags": ["percentage", "metrics"], "scorer": "exact", "expected": {"answer": "120", "normalize": true}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只回答最终数字：某缓存命中率从 60% 提升到 75%。如果总请求数为 800，未命中请求减少了多少个？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "b5b568242a1b6c56d53db2d69addca2d25e472dcc9fb5aa8669dfa273609c0d4", "started_at": "2026-06-16T12:11:23.641699+00:00", "latency_ms": 6638, "output": "120", "usage": {"prompt_tokens": 61, "completion_tokens": 128, "total_tokens": 189, "cost": 0.00040259, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00040259, "upstream_inference_prompt_cost": 7.747e-05, "upstream_inference_completions_cost": 0.00032512}, "completion_tokens_details": {"reasoning_tokens": 126, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611885-HTVWafxTC1SHL4LALpvv", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "120", "actual": "120"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-005", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "mode-comparison"], "scorer": "text_rules", "expected": {"required": ["ability mode", "efficiency mode", "真实能力", "低预算"], "forbidden": ["只看一个模式"], "max_chars": 180}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只根据资料回答。\n\n资料：A 模型在 ability mode 中通过 46/50，成本 0.12 美元；在 efficiency mode 中通过 34/50，成本 0.04 美元。报告建议把 ability mode 用于能力判断，把 efficiency mode 用于成本和稳定性判断。\n\n问题：如果文章讨论“模型真实能力”，应该优先引用哪个模式？如果讨论“低预算可用性”，应该优先引用哪个模式？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "0265f7540e44005627e16c6995d2a9cb458be65bb560cd1d5646c0435265c4e3", "started_at": "2026-06-16T12:11:30.293174+00:00", "latency_ms": 3884, "output": "根据资料，如果讨论“模型真实能力”，应优先引用 ability mode；如果讨论“低预算可用性”，应优先引用 efficiency mode。", "usage": {"prompt_tokens": 126, "completion_tokens": 98, "total_tokens": 224, "cost": 0.000244881, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.000244881, "upstream_inference_prompt_cost": 9.5823e-05, "upstream_inference_completions_cost": 0.000149058}, "completion_tokens_details": {"reasoning_tokens": 66, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611892-zLfiqfShM4WR4Xq6hDvL", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 72, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-006", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "failure-analysis"], "scorer": "text_rules", "expected": {"required": ["key"], "required_any": [["字符串", "类型不匹配"], ["整数", "int"], ["类型假设", "假设 key 为整数", "假设 key 是整数", "key 为整数类型"]], "forbidden": [], "max_chars": 120}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只根据资料回答。\n\n资料：一次失败分析显示，模型输出了 key = int(parts[1])，但测试数据里的 key 是字符串 a、b、c。报告认为这是“擅自补类型假设”，不是 token 截断。\n\n问题：这次失败的根因是什么？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "a49a29fca4961af6e5e2b25c2e82cc0a7be110d48893fc55f7af30f6e1804362", "started_at": "2026-06-16T12:11:34.191461+00:00", "latency_ms": 3783, "output": "根因是模型擅自补充了类型假设（错误假设 key 为整数），而实际测试数据中的 key 是字符串。", "usage": {"prompt_tokens": 90, "completion_tokens": 141, "total_tokens": 231, "cost": 0.00032364, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00032364, "upstream_inference_prompt_cost": 7.83e-05, "upstream_inference_completions_cost": 0.00024534}, "completion_tokens_details": {"reasoning_tokens": 113, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611896-s85N0jq6v0cqSheoXxmB", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 48, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-007", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "abstain"], "scorer": "text_rules", "expected": {"required": ["图表", "资料"], "required_any": [["提到", "提及"]], "forbidden": ["已经支持", "折线图", "柱状图"], "max_chars": 100}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只根据资料回答，不要自行补充。\n\n资料：DracoBench 的 HTML 报告目前展示 Summary、By Suite、Failure Examples 和 Case Details。Failure Examples 中包括 Prompt、Mistake Analysis、Scorer Details 和 Output。资料没有提到图表功能。\n\n问题：报告是否已经支持图表？回答时说明依据。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "c47ee5e02396d5ba9d3852992bf82351aeea58cd22d81035d26a6bac283f07ba", "started_at": "2026-06-16T12:11:37.986164+00:00", "latency_ms": 3186, "output": "根据资料，报告目前**不支持**图表功能。依据是资料中明确指出“资料没有提到图表功能”，因此当前展示的内容仅包含 Summary、By Suite、Failure Examples 和 Case Details。", "usage": {"prompt_tokens": 100, "completion_tokens": 79, "total_tokens": 179, "cost": 0.000414864, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.000414864, "upstream_inference_prompt_cost": 0.0001608, "upstream_inference_completions_cost": 0.000254064}, "completion_tokens_details": {"reasoning_tokens": 36, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611900-7qNvJsPXuxOHOyPl4iRg", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 106, "length_ok": false, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-if-004", "suite": "instruction_following", "case_version": "0.2.0", "tags": ["json", "nested", "strict"], "scorer": "json_schema_lite", "expected": {"schema": {"type": "object", "required": ["mode", "limits", "warnings"], "additionalProperties": false, "properties": {"mode": {"type": "string", "const": "ability"}, "limits": {"type": "object", "required": ["max_tokens", "temperature"], "additionalProperties": false, "properties": {"max_tokens": {"type": "integer", "const": 4096}, "temperature": {"type": "integer", "const": 0}}}, "warnings": {"type": "array", "minItems": 2, "maxItems": 2, "items": {"type": "string"}}}}}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 JSON 对象。字段 mode 必须是 \"ability\"；字段 limits 必须是对象，包含 max_tokens:4096 和 temperature:0；字段 warnings 必须是正好两个字符串组成的数组。不要 Markdown。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "14a17039d4b99be719ac311a5d824ceb40affbf22079ddbcf8bf33af6f04fb0a", "started_at": "2026-06-16T12:11:41.185474+00:00", "latency_ms": 16950, "output": "{\"mode\":\"ability\",\"limits\":{\"max_tokens\":4096,\"temperature\":0},\"warnings\":[\"This is a simulated warning\",\"Another warning message\"]}", "usage": {"prompt_tokens": 76, "completion_tokens": 87, "total_tokens": 163, "cost": 0.00042174, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00042174, "upstream_inference_prompt_cost": 0.00012768, "upstream_inference_completions_cost": 0.00029406}, "completion_tokens_details": {"reasoning_tokens": 51, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611903-ySNomFPngizEnwEllbsb", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"errors": [], "value": {"mode": "ability", "limits": {"max_tokens": 4096, "temperature": 0}, "warnings": ["This is a simulated warning", "Another warning message"]}}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-if-005", "suite": "instruction_following", "case_version": "0.2.0", "tags": ["markdown", "table"], "scorer": "regex", "expected": {"pattern": "^\\s*\\|\\s*模式\\s*\\|\\s*用途\\s*\\|\\s*风险\\s*\\|\\s*\\n\\s*\\|\\s*-+\\s*\\|\\s*-+\\s*\\|\\s*-+\\s*\\|[\\s\\S]*ability mode[\\s\\S]*efficiency mode[\\s\\S]*$", "flags": "is"}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Markdown 表格，必须有 3 列：模式、用途、风险。必须包含 ability mode 和 efficiency mode 两行。不能添加表格外说明。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "0a28a65a8a714a5c613c2e01f5bf2b72b7b18cdd17059ad9d38cea38a6e1ff4f", "started_at": "2026-06-16T12:11:58.150122+00:00", "latency_ms": 5196, "output": "| 模式 | 用途 | 风险 |\n|------|------|------|\n| ability mode | 最大化模型能力，处理复杂任务 | 可能产生不可控输出，资源消耗高 |\n| efficiency mode | 优化资源使用，快速响应常规请求 | 能力受限，可能无法处理复杂需求 |", "usage": {"prompt_tokens": 66, "completion_tokens": 109, "total_tokens": 175, "cost": 0.00024708, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00024708, "upstream_inference_prompt_cost": 5.742e-05, "upstream_inference_completions_cost": 0.00018966}, "completion_tokens_details": {"reasoning_tokens": 42, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611920-SbJ7tJKZyIiY0Mi1lilz", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "^\\s*\\|\\s*模式\\s*\\|\\s*用途\\s*\\|\\s*风险\\s*\\|\\s*\\n\\s*\\|\\s*-+\\s*\\|\\s*-+\\s*\\|\\s*-+\\s*\\|[\\s\\S]*ability mode[\\s\\S]*efficiency mode[\\s\\S]*$"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-zh-writing-003", "suite": "chinese_writing", "case_version": "0.2.0", "tags": ["wechat", "explanation"], "scorer": "text_rules", "expected": {"required": ["原题", "错误解释", "可复查"], "forbidden": ["玄学"], "max_chars": 140}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "写一段不超过 140 个汉字的公众号小结，主题是“为什么要同时展示原题、模型输出和错误解释”。必须包含“原题”“错误解释”“可复查”，不能出现“玄学”。", "parameters": {"temperature": 0.2, "max_tokens": 16384, "seed": null}, "prompt_hash": "f0853803e81259a7bee0074883cc95566fe68e7e6f9ce84b4c3bda73b8c0e638", "started_at": "2026-06-16T12:12:03.360683+00:00", "latency_ms": 24395, "output": "同时展示原题、模型输出与错误解释，让判断有据可依。原题还原上下文，错误解释点明偏差，三者结合可复查，杜绝主观臆测。透明即信赖。", "usage": {"prompt_tokens": 74, "completion_tokens": 1686, "total_tokens": 1760, "cost": 0.00299802, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00299802, "upstream_inference_prompt_cost": 6.438e-05, "upstream_inference_completions_cost": 0.00293364}, "completion_tokens_details": {"reasoning_tokens": 1642, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781611925-hHfOvWhJzD8z8VXOFgIN", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 63, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-reasoning-008", "suite": "reasoning", "case_version": "0.3.0", "tags": ["state-tracking", "branching"], "scorer": "exact", "expected": {"answer": "15", "normalize": true}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只回答最终数字：变量初始为 x=2, y=5, z=1。若 x list[str]，解析一行简化 CSV：逗号分隔；字段可以用双引号包裹；引号内逗号保留；引号内两个连续双引号表示一个双引号；空字段保留；空格是普通字符，不要自动 trim。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "81b6be132a0538b92491e39887550c116b7f09684b97f8dd1ad7df5426e97adb", "started_at": "2026-06-16T12:14:12.198697+00:00", "latency_ms": 32800, "output": "```python\ndef solve(line: str) -> list[str]:\n fields = []\n current = []\n in_quotes = False\n i = 0\n n = len(line)\n while i < n:\n ch = line[i]\n if not in_quotes:\n if ch == '\"':\n if len(current) == 0:\n in_quotes = True\n else:\n current.append('\"')\n elif ch == ',':\n fields.append(''.join(current))\n current = []\n else:\n current.append(ch)\n else:\n if ch == '\"':\n if i + 1 < n and line[i + 1] == '\"':\n current.append('\"')\n i += 1\n else:\n in_quotes = False\n else:\n current.append(ch)\n i += 1\n fields.append(''.join(current))\n return fields\n```", "usage": {"prompt_tokens": 98, "completion_tokens": 1560, "total_tokens": 1658, "cost": 0.002447289, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.002447289, "upstream_inference_prompt_cost": 7.4529e-05, "upstream_inference_completions_cost": 0.00237276}, "completion_tokens_details": {"reasoning_tokens": 1362, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612054-YwvpU1u6xaW0zihdwjKX", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-016", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "intervals", "sorting"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve([(5,7),(1,2),(3,4),(10,10)]) == [(1,7),(10,10)]", "assert solution.solve([(1,1),(3,3)]) == [(1,1),(3,3)]", "assert solution.solve([]) == []"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(intervals: list[tuple[int, int]]) -> list[tuple[int, int]]。intervals 是整数闭区间，先按起点排序；重叠或端点相邻的区间要合并，例如 [1,2] 和 [3,4] 合并为 [1,4]。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "6dc22c1e6ae004a46c47dc11d5cc9ed5d57f09ec77549ff0ada57b459929d814", "started_at": "2026-06-16T12:14:45.047480+00:00", "latency_ms": 8258, "output": "```python\ndef solve(intervals: list[tuple[int, int]]) -> list[tuple[int, int]]:\n if not intervals:\n return []\n intervals.sort(key=lambda x: x[0])\n merged = []\n for start, end in intervals:\n if not merged:\n merged.append([start, end])\n else:\n prev_start, prev_end = merged[-1]\n if start <= prev_end + 1:\n merged[-1][1] = max(prev_end, end)\n else:\n merged.append([start, end])\n return [tuple(x) for x in merged]\n```", "usage": {"prompt_tokens": 103, "completion_tokens": 399, "total_tokens": 502, "cost": 0.0006852105, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0006852105, "upstream_inference_prompt_cost": 7.83315e-05, "upstream_inference_completions_cost": 0.000606879}, "completion_tokens_details": {"reasoning_tokens": 266, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612087-UE107oGGp4bJvuAqqYcB", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-017", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "rate-limit", "state"], "scorer": "code_python_tests", "expected": {"tests": ["events=[('a',1),('a',2),('a',3),('a',4),('a',8)]\nassert solution.solve(events, 5, 2) == [True, True, False, False, True]", "assert solution.solve([('x',10),('x',11),('x',16)], 5, 1) == [True, False, True]"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(events: list[tuple[str, int]], window: int, limit: int) -> list[bool]，模拟按用户限流。events 按时间非降序排列。某用户在当前事件时间 ts 的窗口 (ts-window, ts] 内，已放行事件数少于 limit 才放行；被拒绝的事件不计入窗口。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "1539217453d6af4bac3c7abfbd8df43ed131cd647e58a0ad2a5a670794a91f80", "started_at": "2026-06-16T12:14:53.350284+00:00", "latency_ms": 19679, "output": "```python\nfrom collections import defaultdict, deque\n\ndef solve(events, window, limit):\n user_queues = defaultdict(deque)\n result = []\n for user, ts in events:\n q = user_queues[user]\n while q and q[0] <= ts - window:\n q.popleft()\n if len(q) < limit:\n q.append(ts)\n result.append(True)\n else:\n result.append(False)\n return result\n```", "usage": {"prompt_tokens": 116, "completion_tokens": 488, "total_tokens": 604, "cost": 0.00190008, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00190008, "upstream_inference_prompt_cost": 0.00020184, "upstream_inference_completions_cost": 0.00169824}, "completion_tokens_details": {"reasoning_tokens": 517, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612095-B1hRtx1xZwVaVTMsnbY6", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-018", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "path", "stack"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('/a//b/./c/../') == '/a/b'", "assert solution.solve('/../../x') == '/x'", "assert solution.solve('/') == '/'"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(path: str) -> str，规范化绝对 Unix 路径：处理重复斜杠、.、..；.. 在根目录时仍留在根目录；返回结果必须以 / 开头且除根目录外不能以 / 结尾。不要使用 os.path。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "92e706f1062d7652c2f14c514c44602c6708e65d87771889d3aff7450e33e85d", "started_at": "2026-06-16T12:15:13.080444+00:00", "latency_ms": 11449, "output": "```python\ndef solve(path: str) -> str:\n parts = path.split('/')\n stack = []\n for part in parts:\n if part == '' or part == '.':\n continue\n elif part == '..':\n if stack:\n stack.pop()\n else:\n stack.append(part)\n return '/' + '/'.join(stack)\n```", "usage": {"prompt_tokens": 95, "completion_tokens": 521, "total_tokens": 616, "cost": 0.0008646885, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0008646885, "upstream_inference_prompt_cost": 7.22475e-05, "upstream_inference_completions_cost": 0.000792441}, "completion_tokens_details": {"reasoning_tokens": 443, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612115-F8wJsIWIfrp3N0gGBtXx", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-019", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "grouping", "stable-order"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve(['eat','tea','tan','ate','nat','bat']) == [['eat','tea','ate'], ['tan','nat'], ['bat']]", "assert solution.solve(['b','B','bb']) == [['b'], ['B'], ['bb']]"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(words: list[str]) -> list[list[str]]，按变位词分组。大小写敏感；组内保持输入顺序；组的顺序按该组第一个单词在输入中出现的位置。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "0a957bf71a0be6fa198a854347b2fe5d2c5d5f9b9a8bd5041dac9cdb46ae06ce", "started_at": "2026-06-16T12:15:24.559231+00:00", "latency_ms": 7630, "output": "```python\ndef solve(words):\n groups = {}\n for w in words:\n key = ''.join(sorted(w))\n if key not in groups:\n groups[key] = []\n groups[key].append(w)\n return list(groups.values())\n```", "usage": {"prompt_tokens": 80, "completion_tokens": 335, "total_tokens": 415, "cost": 0.0012, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0012, "upstream_inference_prompt_cost": 0.000128, "upstream_inference_completions_cost": 0.001072}, "completion_tokens_details": {"reasoning_tokens": 280, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612126-EAMijdc8Yehpr7Mp9OVu", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-020", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "parser", "front-matter"], "scorer": "code_python_tests", "expected": {"tests": ["text='---\\ntitle: Test\\ntags: [ai, bench, v0]\\ndraft: false\\n---\\nbody'\nassert solution.solve(text) == {'title':'Test','tags':['ai','bench','v0'],'draft':'false'}", "assert solution.solve('hello\\n---\\na: b') == {}", "assert solution.solve('---\\na: 1') == {}"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(text: str) -> dict，解析 Markdown front matter。只有第一行正好是 --- 时才解析，直到下一行 --- 结束；每行 key: value，key 和 value 两侧 trim；形如 [a, b] 的 value 返回字符串列表；其他 value 返回字符串。没有完整 front matter 返回 {}。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "4111f2228a7b621a743019a4cad1b5638c8a120765153c2d35f8db2aa136f79c", "started_at": "2026-06-16T12:15:32.234879+00:00", "latency_ms": 22798, "output": "```python\ndef solve(text: str) -> dict:\n lines = text.splitlines()\n if not lines or lines[0].strip() != '---':\n return {}\n \n end_index = -1\n for i in range(1, len(lines)):\n if lines[i].strip() == '---':\n end_index = i\n break\n if end_index == -1:\n return {}\n \n result = {}\n for i in range(1, end_index):\n line = lines[i].strip()\n if not line:\n continue\n if ':' not in line:\n continue\n key, _, value = line.partition(':')\n key = key.strip()\n value = value.strip()\n if value.startswith('[') and value.endswith(']'):\n inner = value[1:-1].strip()\n if inner == '':\n result[key] = []\n else:\n items = [item.strip() for item in inner.split(',')]\n result[key] = items\n else:\n result[key] = value\n return result\n```", "usage": {"prompt_tokens": 113, "completion_tokens": 1301, "total_tokens": 1414, "cost": 0.00436572, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00436572, "upstream_inference_prompt_cost": 0.000181704, "upstream_inference_completions_cost": 0.004184016}, "completion_tokens_details": {"reasoning_tokens": 1067, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612134-wyo7V9895wyfxHqPwr8s", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-021", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "frequency", "stable-order"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve(['b','a','b','c','a','b'], 2) == ['b','a']", "assert solution.solve(['x','y','z','y','z','x'], 2) == ['x','y']", "assert solution.solve(['a'], 5) == ['a']"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(items: list[str], k: int) -> list[str]，返回出现次数最高的前 k 个元素；次数相同按第一次出现的先后排序；k 大于不同元素数量时返回全部。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e73dccf0e991c296063c917fbe5a6b5f99f50fb3baed6d0820cfc35df858c663", "started_at": "2026-06-16T12:15:55.082525+00:00", "latency_ms": 11027, "output": "```python\nfrom collections import Counter\n\ndef solve(items: list[str], k: int) -> list[str]:\n freq = Counter(items)\n first_index = {}\n for idx, item in enumerate(items):\n if item not in first_index:\n first_index[item] = idx\n sorted_items = sorted(freq.keys(), key=lambda x: (-freq[x], first_index[x]))\n return sorted_items[:k]\n```", "usage": {"prompt_tokens": 81, "completion_tokens": 533, "total_tokens": 614, "cost": 0.00099789, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00099789, "upstream_inference_prompt_cost": 7.047e-05, "upstream_inference_completions_cost": 0.00092742}, "completion_tokens_details": {"reasoning_tokens": 442, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612157-d9JgqlmxTGcrkV3frr8h", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-022", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "nested-dict", "copy"], "scorer": "code_python_tests", "expected": {"tests": ["base={'db':{'host':'old','port':5432},'feature':{'x':1}}\noverrides={'db.host':'new','feature.x':None,'api.timeout':30}\nres=solution.solve(base, overrides)\nassert res == {'db':{'host':'new','port':5432},'feature':{},'api':{'timeout':30}}\nassert base == {'db':{'host':'old','port':5432},'feature':{'x':1}}", "assert solution.solve({'a':1}, {'a.b':2}) == {'a': {'b': 2}}"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(config: dict, overrides: dict[str, object]) -> dict。overrides 的 key 是点号路径；值为 None 表示删除该路径的叶子 key；其他值写入路径，必要时创建中间 dict；不能修改输入 config。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e21e5bbf42159ba49144d39d17824dcf011df026efab7a9bfb6179aed2bb558a", "started_at": "2026-06-16T12:16:06.159634+00:00", "latency_ms": 37570, "output": "```python\nimport copy\n\ndef solve(config: dict, overrides: dict[str, object]) -> dict:\n res = copy.deepcopy(config)\n for path, val in overrides.items():\n parts = path.split('.')\n if val is None:\n # 删除路径\n d = res\n for i, key in enumerate(parts):\n if not isinstance(d, dict):\n break\n if i == len(parts) - 1:\n if key in d:\n del d[key]\n break\n if key not in d:\n break\n d = d[key]\n else:\n # 写入路径\n d = res\n parent = None\n last_key = None\n for i, key in enumerate(parts):\n if not isinstance(d, dict):\n # 当前节点不是字典，用新字典替换父级中的引用\n new_dict = {}\n if parent is not None:\n parent[last_key] = new_dict\n d = new_dict\n if i == len(parts) - 1:\n d[key] = val\n else:\n if key not in d or not isinstance(d[key], dict):\n d[key] = {}\n parent = d\n last_key = key\n d = d[key]\n return res\n```", "usage": {"prompt_tokens": 92, "completion_tokens": 1872, "total_tokens": 1964, "cost": 0.00333732, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00333732, "upstream_inference_prompt_cost": 8.004e-05, "upstream_inference_completions_cost": 0.00325728}, "completion_tokens_details": {"reasoning_tokens": 1591, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612168-hY6LBUl7os83tB7gKBqU", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-023", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "url", "parser"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('a=1&b=two+words&a=3') == {'a':['1','3'], 'b':['two words']} ", "assert solution.solve('empty=&flag&x=a%2Bb') == {'empty':[''], 'flag':[''], 'x':['a+b']} ", "assert solution.solve('') == {}"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(query: str) -> dict[str, list[str]]，解析 URL query string。& 分隔参数；没有 = 的参数值为空字符串；+ 表示空格；%XX 需要按 UTF-8 百分号解码；同名 key 保留所有值的列表。可以使用标准库。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "cfe8be23444d346039a0740ab1568f54ed98bd44e5d63909779673da2207f393", "started_at": "2026-06-16T12:16:43.780128+00:00", "latency_ms": 25669, "output": "```python\ndef solve(query: str) -> dict[str, list[str]]:\n from urllib.parse import parse_qs\n return parse_qs(query, keep_blank_values=True)\n```", "usage": {"prompt_tokens": 100, "completion_tokens": 1184, "total_tokens": 1284, "cost": 0.003968544, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.003968544, "upstream_inference_prompt_cost": 0.0001608, "upstream_inference_completions_cost": 0.003807744}, "completion_tokens_details": {"reasoning_tokens": 1141, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612206-cyfZjBXVCg2KP6P8mHIb", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-024", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "parser", "stack"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('

x

') is True", "assert solution.solve('') is False", "assert solution.solve('text') is True"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(html: str) -> bool，校验简化 HTML 标签是否配对。标签形如 、、
，标签名只含小写字母；自闭合标签不入栈；普通文本忽略。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "088a9867c7f154cf1ee172830e13e8e49c53a8e572707d776f0cdea59f3555cb", "started_at": "2026-06-16T12:17:09.510859+00:00", "latency_ms": 20466, "output": "```python\ndef solve(html: str) -> bool:\n stack = []\n i = 0\n n = len(html)\n while i < n:\n if html[i] != '<':\n i += 1\n continue\n j = i + 1\n while j < n and html[j] != '>':\n j += 1\n if j == n:\n break\n tag = html[i+1:j]\n i = j + 1\n if tag.startswith('/'):\n name = tag[1:]\n if not name.islower():\n return False\n if not stack or stack.pop() != name:\n return False\n elif tag.endswith('/'):\n continue\n else:\n if not tag.islower():\n return False\n stack.append(tag)\n return len(stack) == 0\n```", "usage": {"prompt_tokens": 89, "completion_tokens": 1189, "total_tokens": 1278, "cost": 0.00214629, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00214629, "upstream_inference_prompt_cost": 7.743e-05, "upstream_inference_completions_cost": 0.00206886}, "completion_tokens_details": {"reasoning_tokens": 1001, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612231-U1t69VnXNvgGYyOc6xtN", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-025", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "bfs", "grid"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve(['S..','##.','..E']) == 4", "assert solution.solve(['S#','##','E.']) == -1", "assert solution.solve(['SE']) == 1"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(grid: list[str]) -> int。grid 中 S 是起点，E 是终点，# 是墙，. 可走。每步上下左右移动一格，返回从 S 到 E 的最短步数；不可达返回 -1。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "8c6dc47fe32c2eef1e05bed2e6bd50520bb606e6965fe6c18e354a50a1e65085", "started_at": "2026-06-16T12:17:30.024536+00:00", "latency_ms": 12179, "output": "```python\nfrom collections import deque\n\ndef solve(grid: list[str]) -> int:\n if not grid:\n return -1\n rows, cols = len(grid), len(grid[0])\n start = end = None\n for r in range(rows):\n for c in range(cols):\n if grid[r][c] == 'S':\n start = (r, c)\n elif grid[r][c] == 'E':\n end = (r, c)\n if not start or not end:\n return -1\n \n sr, sc = start\n er, ec = end\n visited = [[False] * cols for _ in range(rows)]\n q = deque()\n q.append((sr, sc, 0))\n visited[sr][sc] = True\n \n while q:\n r, c, d = q.popleft()\n if r == er and c == ec:\n return d\n for dr, dc in ((0, 1), (0, -1), (1, 0), (-1, 0)):\n nr, nc = r + dr, c + dc\n if 0 <= nr < rows and 0 <= nc < cols and not visited[nr][nc] and grid[nr][nc] != '#':\n visited[nr][nc] = True\n q.append((nr, nc, d + 1))\n return -1\n```", "usage": {"prompt_tokens": 95, "completion_tokens": 718, "total_tokens": 813, "cost": 0.0011643255, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0011643255, "upstream_inference_prompt_cost": 7.22475e-05, "upstream_inference_completions_cost": 0.001092078}, "completion_tokens_details": {"reasoning_tokens": 411, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612252-o3VpXRaBtD3ZAeI3rYtM", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-026", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "sliding-window", "median"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve([1,3,-1,-3,5,3,6,7], 3) == [1, -1, -1, 3, 5, 6]", "assert solution.solve([1,2,3,4], 2) == [1.5, 2.5, 3.5]"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(nums: list[int], k: int) -> list[float]，返回每个长度为 k 的滑动窗口中位数。k 为奇数时返回中间值；k 为偶数时返回两个中间值平均数。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "53547e8e9f25c840b8a6248c7be329b1779ddc5a47484208f5c434403bd8228c", "started_at": "2026-06-16T12:17:42.256901+00:00", "latency_ms": 67624, "output": "```python\nfrom heapq import heappush, heappop\nfrom collections import defaultdict\nfrom typing import List\n\ndef solve(nums: List[int], k: int) -> List[float]:\n max_heap = [] # 负数\n min_heap = [] # 正数\n delayed = defaultdict(int)\n balance = 0\n\n def prune():\n while max_heap and delayed.get(-max_heap[0], 0) > 0:\n delayed[-max_heap[0]] -= 1\n heappop(max_heap)\n while min_heap and delayed.get(min_heap[0], 0) > 0:\n delayed[min_heap[0]] -= 1\n heappop(min_heap)\n\n def rebalance():\n nonlocal balance\n prune()\n while balance > 1:\n val = -heappop(max_heap)\n heappush(min_heap, val)\n balance -= 2\n prune()\n while balance < 0:\n val = heappop(min_heap)\n heappush(max_heap, -val)\n balance += 2\n prune()\n\n def add(num: int):\n nonlocal balance\n if not max_heap or num <= -max_heap[0]:\n heappush(max_heap, -num)\n balance += 1\n else:\n heappush(min_heap, num)\n balance -= 1\n rebalance()\n\n def remove(num: int):\n nonlocal balance\n delayed[num] += 1\n if max_heap and num <= -max_heap[0]:\n balance -= 1\n else:\n balance += 1\n prune()\n rebalance()\n\n def get_median() -> float:\n prune()\n if k % 2 == 1:\n return float(-max_heap[0])\n else:\n return (-max_heap[0] + min_heap[0]) / 2.0\n\n res = []\n for i in range(k):\n add(nums[i])\n res.append(get_median())\n\n for i in range(k, len(nums)):\n remove(nums[i - k])\n add(nums[i])\n res.append(get_median())\n\n return res\n```", "usage": {"prompt_tokens": 84, "completion_tokens": 3302, "total_tokens": 3386, "cost": 0.005086224, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.005086224, "upstream_inference_prompt_cost": 6.3882e-05, "upstream_inference_completions_cost": 0.005022342}, "completion_tokens_details": {"reasoning_tokens": 2834, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612264-IkDdj3WFTH6xBYc8BHPH", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-027", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "sorting", "semver"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve(['1.0.0','1.0.0-alpha','1.0.1','1.0.0-beta','0.9.9']) == ['0.9.9','1.0.0-alpha','1.0.0-beta','1.0.0','1.0.1']", "assert solution.solve(['1.0.10','1.0.2']) == ['1.0.2','1.0.10']"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(versions: list[str]) -> list[str]，按简化语义版本排序。版本为 major.minor.patch 或 major.minor.patch-label；major/minor/patch 按数字比较；同一数字版本下，带 label 的预发布版本低于正式版本；label 按字典序比较。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "f9b7324425840beb574b30433a6e004d34a834ef548c9cfa579b9b9b6950377d", "started_at": "2026-06-16T12:18:49.940401+00:00", "latency_ms": 18914, "output": "```python\ndef solve(versions):\n def key(v):\n if '-' in v:\n base, label = v.split('-', 1)\n pre = 0\n else:\n base, label = v, ''\n pre = 1\n major, minor, patch = map(int, base.split('.'))\n return (major, minor, patch, pre, label)\n return sorted(versions, key=key)\n```", "usage": {"prompt_tokens": 105, "completion_tokens": 975, "total_tokens": 1080, "cost": 0.00178785, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00178785, "upstream_inference_prompt_cost": 9.135e-05, "upstream_inference_completions_cost": 0.0016965}, "completion_tokens_details": {"reasoning_tokens": 881, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612332-B56raPkjZGAPqBnBlDkG", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-028", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "graph", "reverse-deps"], "scorer": "code_python_tests", "expected": {"tests": ["deps={'app':['lib','ui'],'ui':['core'],'lib':['core'],'core':[],'docs':[]}\nassert solution.solve(deps, ['core']) == ['app','core','lib','ui']", "assert solution.solve({'a':['x']}, ['x']) == ['a','x']", "assert solution.solve({'a':['b'], 'b':[]}, ['a']) == ['a']"], "timeout_seconds": 3}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(deps: dict[str, list[str]], changed: list[str]) -> list[str]。deps 表示 package -> 直接依赖。返回所有 changed 包，以及直接或间接依赖 changed 包的包，按字典序排序；只出现在依赖列表中的包也要能作为 changed 包返回。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "2a0e51751556bc0e35f2a2a2aa4ed86810eacfc274bb9c5f48e8990611a9a473", "started_at": "2026-06-16T12:19:08.900311+00:00", "latency_ms": 19698, "output": "```python\nfrom collections import defaultdict, deque\n\ndef solve(deps: dict[str, list[str]], changed: list[str]) -> list[str]:\n rev_graph = defaultdict(list)\n all_packages = set(deps.keys())\n for p, deps_list in deps.items():\n for dep in deps_list:\n rev_graph[dep].append(p)\n all_packages.add(dep)\n \n result_set = set(changed)\n queue = deque(changed)\n while queue:\n current = queue.popleft()\n for dependent in rev_graph.get(current, []):\n if dependent not in result_set:\n result_set.add(dependent)\n queue.append(dependent)\n return sorted(result_set)\n```", "usage": {"prompt_tokens": 103, "completion_tokens": 865, "total_tokens": 968, "cost": 0.0013939965, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0013939965, "upstream_inference_prompt_cost": 7.83315e-05, "upstream_inference_completions_cost": 0.001315665}, "completion_tokens_details": {"reasoning_tokens": 712, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612351-DKOReItOhFiSdwRIUEEY", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-008", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "conflict", "workflow"], "scorer": "text_rules", "expected": {"required": ["50", "审题"], "required_any": [["不跑", "不要立刻", "先不跑", "不应立刻", "不应该立刻", "不应立即", "不应该立即", "不应立刻跑", "不应该立刻跑", "不应立即跑", "不应该立即跑"]], "forbidden": [], "max_chars": 160}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只根据资料回答。\n\n资料 A：早期草案说 v0.3 只新增 20 道题。\n资料 B：2026-06-16 的确认方案是 v0.3-challenge100，在现有 50 题基础上新增 50 道题。\n资料 C：新增题应先生成审题 HTML，确认后再跑模型，不要立即消耗 API。\n\n问题：下一步应该新增多少题？是否应该立刻跑模型？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "c99da78812f6f4ab7745f793b9e3dc087033b0cce0591db49bf8642829324a81", "started_at": "2026-06-16T12:19:28.642470+00:00", "latency_ms": 4698, "output": "根据资料B和资料C，下一步应新增50题，且不应立刻跑模型，应先生成审题HTML、确认后再跑模型。", "usage": {"prompt_tokens": 125, "completion_tokens": 173, "total_tokens": 298, "cost": 0.0003581955, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0003581955, "upstream_inference_prompt_cost": 9.50625e-05, "upstream_inference_completions_cost": 0.000263133}, "completion_tokens_details": {"reasoning_tokens": 140, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612370-B9L9STGJZ3SXWrjuMOs0", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 48, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-009", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "abstain"], "scorer": "text_rules", "expected": {"required": ["不能", "用户满意度"], "required_any": [["没有包含", "没有提供", "资料没有", "未包含"]], "forbidden": ["可以判断"], "max_chars": 120}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只根据资料回答，不要自行补充。\n\n资料：报告展示 pass_rate、avg_latency_ms、total_cost、reasoning_tokens、失败样例和逐题明细。资料没有包含用户满意度调查，也没有包含模型训练数据来源。\n\n问题：能否根据这份报告判断用户满意度？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "c072287ee5dbe1d477ab21e37485fb72f07cd11a57b57f199f071287443f404e", "started_at": "2026-06-16T12:19:33.354721+00:00", "latency_ms": 2756, "output": "不能。因为资料中没有包含用户满意度调查。", "usage": {"prompt_tokens": 90, "completion_tokens": 73, "total_tokens": 163, "cost": 0.000179478, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.000179478, "upstream_inference_prompt_cost": 6.8445e-05, "upstream_inference_completions_cost": 0.000111033}, "completion_tokens_details": {"reasoning_tokens": 61, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612375-rsOpnkfytHJq2FcIf7jN", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 20, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-010", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "tradeoff"], "scorer": "text_rules", "expected": {"required": ["B", "延迟"], "required_any": [["没有超时", "无超时"]], "forbidden": ["选择 A", "选择 C"], "max_chars": 160}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只根据资料回答。\n\n资料：模型 A 通过 48/50，平均延迟 20 秒，成本 0.20 美元，没有超时失败。模型 B 通过 44/50，平均延迟 4 秒，成本 0.05 美元，没有超时失败。模型 C 通过 46/50，平均延迟 9 秒，成本 0.04 美元，但有 3 次 API 超时。\n\n问题：如果要选低延迟且稳定的生产摘要模型，资料更支持选择哪个？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "a17bb8c56d524481eedc45557a1394b5b65b034af6847928cca16e2c8c2428c9", "started_at": "2026-06-16T12:19:36.124816+00:00", "latency_ms": 2591, "output": "根据资料，模型 B 更符合“低延迟且稳定”的要求。它的平均延迟最低（4 秒），没有超时失败，且成本较低。虽然模型 A 通过率更高且同样无超时，但延迟是模型 B 的 5 倍。模型 C 有 3 次超时，稳定性不足。", "usage": {"prompt_tokens": 146, "completion_tokens": 74, "total_tokens": 220, "cost": 0.0003822, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0003822, "upstream_inference_prompt_cost": 0.0001898, "upstream_inference_completions_cost": 0.0001924}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612378-4tDgcP10I0CtEhovLyFp", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 105, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-011", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "scoring-policy"], "scorer": "text_rules", "expected": {"required": ["诊断"], "required_any": [["不扣分", "不会", "不会因长度", "不会因此被扣分", "不会直接导致扣分", "不会导致扣分", "不会导致失败或扣分"], ["length_scored", "长度"]], "forbidden": ["直接失败", "必须重跑"], "max_chars": 140}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只根据资料回答。\n\n资料：DracoBench 当前 scoring policy 中，text_rules 的 max_chars/min_chars 只作为诊断信息记录，length_scored 为 false。缺少 required、required_any 或出现 forbidden 才会导致失败。\n\n问题：如果答案超过 max_chars，但 required 都满足且没有 forbidden，会因为长度直接扣分吗？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "1ff7f897fc3d3121f25358f9a8df2a2df2970bc5762ff1218dd63c3f42d7d598", "started_at": "2026-06-16T12:19:38.729760+00:00", "latency_ms": 3856, "output": "不会。根据资料，`max_chars/min_chars` 仅作为诊断信息记录，且 `length_scored` 为 `false`，只有缺少 `required`、`required_any` 或出现 `forbidden` 才会导致失败。因此答案超过 `max_chars` 但满足其他条件时，不会因长度而扣分。", "usage": {"prompt_tokens": 111, "completion_tokens": 185, "total_tokens": 296, "cost": 0.0007696, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0007696, "upstream_inference_prompt_cost": 0.0001776, "upstream_inference_completions_cost": 0.000592}, "completion_tokens_details": {"reasoning_tokens": 107, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612380-Sm0A8rtZjBTPN9w9qU97", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 159, "length_ok": false, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-012", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "rescoring"], "scorer": "text_rules", "expected": {"required": ["46/50"], "forbidden": ["45/50 更合适", "原始结果为准"], "max_chars": 140}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只根据资料回答。\n\n资料 A：某模型原始结果为 45/50。\n资料 B：修正一个同义表达评分规则后，rescored 结果为 46/50。\n资料 C：总览 index 使用 rescored JSONL 作为展示结果。\n\n问题：写文章引用总览结果时，应写 45/50 还是 46/50？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "274c0483d9fd5cae178e795e16add941178c14f5ae34a82f631655c000ff929a", "started_at": "2026-06-16T12:19:42.600827+00:00", "latency_ms": 1238, "output": "根据资料 C，总览 index 使用 rescored JSONL 作为展示结果，因此应写 **46/50**。", "usage": {"prompt_tokens": 107, "completion_tokens": 28, "total_tokens": 135, "cost": 0.0002119, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0002119, "upstream_inference_prompt_cost": 0.0001391, "upstream_inference_completions_cost": 7.28e-05}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612384-LinUZLRJXFyZ5bzuoSU6", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 56, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-013", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "reproducibility"], "scorer": "text_rules", "expected": {"required": ["model", "prompt_hash", "parameters", "scorer"], "forbidden": ["chain of thought", "训练数据"], "max_chars": 200}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只根据资料回答。\n\n资料：为了复现一次 benchmark，记录中包含 model、case_id、prompt_hash、parameters、scorer details、output、latency_ms 和 usage。记录不包含 chain of thought，也不包含训练数据。\n\n问题：复现评测主要应该依赖哪些记录字段？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "7455c8e21abbb53f7cb11c9db29ed66ad1dfcc7e60138f6dfccb7cbcacc958c3", "started_at": "2026-06-16T12:19:43.852690+00:00", "latency_ms": 11809, "output": "复现评测主要应该依赖以下记录字段：model、case_id、prompt_hash、parameters、scorer details、output、latency_ms 和 usage。", "usage": {"prompt_tokens": 92, "completion_tokens": 35, "total_tokens": 127, "cost": 0.0002106, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0002106, "upstream_inference_prompt_cost": 0.0001196, "upstream_inference_completions_cost": 9.1e-05}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612386-yI3LYbbDWyk2WBQi0jBN", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 95, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-014", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "mode"], "scorer": "text_rules", "expected": {"required": ["16384"], "forbidden": ["4096"], "max_chars": 100}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只根据资料回答。\n\n资料 A：早期 ability mode 使用 4096 max_tokens。\n资料 B：后来为了公平，ability mode 统一放宽到 16384 max_tokens。\n资料 C：当前总览页只展示 v0.2-challenge50 且 ability16384 的结果。\n\n问题：当前总览页对应的 token limit 是多少？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "1d5b45892f4d0509e7805976e9bb60b3893e68657b40fcfa934db89a27eccc7b", "started_at": "2026-06-16T12:19:55.676557+00:00", "latency_ms": 3139, "output": "16384", "usage": {"prompt_tokens": 105, "completion_tokens": 136, "total_tokens": 241, "cost": 0.000606216, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.000606216, "upstream_inference_prompt_cost": 0.00016884, "upstream_inference_completions_cost": 0.000437376}, "completion_tokens_details": {"reasoning_tokens": 132, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612397-Pv0G1tHjhlIWtHKzo3CA", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 5, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-015", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "failure-analysis", "scoring-policy"], "scorer": "text_rules", "expected": {"required": ["人工复查", "coding-004"], "required_any": [["rag-006", "规则", "评分规则", "同义表达"], ["不属于", "不是", "不需要"]], "max_chars": 180}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只根据资料回答。\n\n资料：coding-004 的失败是代码运行时 ValueError，根因是把字符串 key 强转 int。rag-006 的失败曾经是规则没有把 int 类型视作“整数”的同义表达，后来通过人工复查修正规则。\n\n问题：哪类失败更需要人工复查评分规则？回答时也说明 coding-004 是否属于这种情况。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "d4725ef21042620eab8231d5671ac8f778c2b71f85afb72d592c3da2278cc9c4", "started_at": "2026-06-16T12:19:58.830033+00:00", "latency_ms": 7181, "output": "根据资料，rag-006 这类失败更需要人工复查评分规则，因为其失败原因是规则未能识别“int 类型”与“整数”的同义表达，后来通过人工复查才修正了规则。coding-004 不属于这种情况，它的失败是代码运行时 ValueError，根因是强制类型转换，属于代码执行错误，不涉及评分规则。", "usage": {"prompt_tokens": 110, "completion_tokens": 238, "total_tokens": 348, "cost": 0.001093748, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.001093748, "upstream_inference_prompt_cost": 0.0001903, "upstream_inference_completions_cost": 0.000903448}, "completion_tokens_details": {"reasoning_tokens": 160, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612402-GvsXth9q4uGDVjiSN03N", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 145, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-016", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "abstain", "cost"], "scorer": "text_rules", "expected": {"required": ["不能", "利润率"], "required_any": [["不包含", "没有"]], "forbidden": ["可以判断"], "max_chars": 120}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只根据资料回答。\n\n资料：usage 字段包含 prompt_tokens、completion_tokens、reasoning_tokens 和 cost。报告没有供应商真实利润率，也没有供应商内部成本。\n\n问题：能否从 usage 字段判断供应商利润率？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "622c02bde50c8b232afe7bb574da76e2ed1e35d49a55a96f63b935dbbbb16175", "started_at": "2026-06-16T12:20:06.026550+00:00", "latency_ms": 6044, "output": "不能。资料明确指出，报告中没有供应商真实利润率和内部成本信息，仅凭 usage 字段中的 token 用量和费用数据无法判断利润率。", "usage": {"prompt_tokens": 79, "completion_tokens": 115, "total_tokens": 194, "cost": 0.000486925, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.000486925, "upstream_inference_prompt_cost": 0.0001264, "upstream_inference_completions_cost": 0.000360525}, "completion_tokens_details": {"reasoning_tokens": 82, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612408-DyxpRC2Zdd8jIpGoWd0R", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 66, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-017", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "index-scope"], "scorer": "text_rules", "expected": {"required": ["v0.2-challenge50", "ability16384"], "required_any": [["不应该", "不展示", "未展示", "不显示", "均不显示", "不应展示"], ["旧版本", "之前的版本"]], "max_chars": 160}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只根据资料回答。\n\n资料：当前 index 页只显示最后这版 50 道题的 v0.2-challenge50 结果，并且 token limit 都统一为 ability16384。之前的版本和 ability4096 结果不显示在 index 页。\n\n问题：index 页是否应该展示旧版本结果？当前展示范围是什么？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "84234aeba9875f705a8daae80d0f0a287d1cef74de57877dfe6fbd41e6d1e835", "started_at": "2026-06-16T12:20:12.087497+00:00", "latency_ms": 6072, "output": "根据资料，当前 index 页**只显示**最后这版 50 道题的 v0.2-challenge50 结果，token limit 统一为 ability16384。之前的版本和 ability4096 结果均**不显示**在 index 页。 \n\n资料未提及“是否应该展示旧版本结果”，仅说明了**当前展示范围**：仅限 v0.2-challenge50 版本的结果。", "usage": {"prompt_tokens": 103, "completion_tokens": 305, "total_tokens": 408, "cost": 0.0011408, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0011408, "upstream_inference_prompt_cost": 0.0001648, "upstream_inference_completions_cost": 0.000976}, "completion_tokens_details": {"reasoning_tokens": 215, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612414-vhpXK03hw3clKzUCxw2T", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 186, "length_ok": false, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-018", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "failure-analysis", "truncation"], "scorer": "text_rules", "expected": {"required": ["输出"], "required_any": [["截断", "length", "token"]], "forbidden": [], "max_chars": 140}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "只根据资料回答。\n\n资料：某 coding 题中，模型响应的 finish_reason 为 length，output 为空，测试报错为 module has no attribute solve。报告认为这不是算法逻辑错误，而是输出被截断后没有形成可执行函数。\n\n问题：这次失败应如何归因？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "f819b3ec516c1c77e6e0c1bbcece217d77fc5a4aaee6e7787be0b4cd5d97c9ff", "started_at": "2026-06-16T12:20:18.174275+00:00", "latency_ms": 2014, "output": "根据资料，这次失败应归因于**输出被截断**，导致没有形成可执行函数，而非算法逻辑错误。", "usage": {"prompt_tokens": 94, "completion_tokens": 29, "total_tokens": 123, "cost": 0.0001976, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0001976, "upstream_inference_prompt_cost": 0.0001222, "upstream_inference_completions_cost": 7.54e-05}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612420-phnzBfI7kgU0e9KmaN9B", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 44, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-015", "suite": "debugging", "case_version": "0.3.0", "tags": ["python", "closure", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*funcs\\.append\\(lambda\\s+i=i\\s*:\\s*i\\)\\s*`?", "flags": "is"}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面代码期望 funcs[0]()、funcs[1]()、funcs[2]() 分别返回 0、1、2，但实际都会返回 2。请指出根因，并给出最小修复。最后单独一行写 FIX: <修复后的 append 行>。\n\n```python\nfuncs = []\nfor i in range(3):\n funcs.append(lambda: i)\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e90d1ddfafd6f041b7be435f823b34b7ad74ddf85bb4dbb228db8e1183cd8843", "started_at": "2026-06-16T12:20:20.204404+00:00", "latency_ms": 5974, "output": "根本原因是 Python 的闭包延迟绑定：lambda 中的 `i` 捕获的是变量本身而非其值，循环结束后 `i` 为 2，所有 lambda 都引用同一个 `i`。\n\n最小修复是让 lambda 在定义时立即捕获当前值，可通过默认参数实现：\n\n```python\nfuncs.append(lambda i=i: i)\n```\n\nFIX: funcs.append(lambda i=i: i)", "usage": {"prompt_tokens": 117, "completion_tokens": 90, "total_tokens": 207, "cost": 0.00037719, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00037719, "upstream_inference_prompt_cost": 0.00014859, "upstream_inference_completions_cost": 0.0002286}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612422-UCK7z9TjsHiyMa2DIp9G", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*funcs\\.append\\(lambda\\s+i=i\\s*:\\s*i\\)\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-016", "suite": "debugging", "case_version": "0.3.0", "tags": ["python", "context-manager", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*return(?:\\s+False|\\s+None)?\\s*`?", "flags": "is"}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面 context manager 期望异常继续向外抛出，但实际异常被吞掉。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 return 行>。\n\n```python\nclass Span:\n def __enter__(self):\n return self\n def __exit__(self, exc_type, exc, tb):\n return True\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e7cbf0d9b2df76954e4b3aacf7d21f0a22c40f64ccc2432b115896cdb5a3f123", "started_at": "2026-06-16T12:20:26.195055+00:00", "latency_ms": 11588, "output": "在 `context manager` 中，`__exit__` 返回 `True` 会吞掉异常，阻止其向外抛出；若期望异常继续传播，应返回 `False`（或 `None`）。 \n最小修复：将 `return True` 改为 `return False`。\n\nFIX: return False", "usage": {"prompt_tokens": 106, "completion_tokens": 434, "total_tokens": 540, "cost": 0.00123698, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00123698, "upstream_inference_prompt_cost": 0.00013462, "upstream_inference_completions_cost": 0.00110236}, "completion_tokens_details": {"reasoning_tokens": 366, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612428-gtCnTzPR3whS7aCo0hbm", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*return(?:\\s+False|\\s+None)?\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-017", "suite": "debugging", "case_version": "0.3.0", "tags": ["python", "class-variable", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*self\\.items\\s*=\\s*\\[\\]\\s*`?", "flags": "is"}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面代码期望每个 Bag 实例都有独立列表，但不同实例会共享 items。请指出 bug，并给出最小修复。最后单独一行写 FIX: <新增到 __init__ 中的赋值行>。\n\n```python\nclass Bag:\n items = []\n def add(self, x):\n self.items.append(x)\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "c2b320a4b54c57505deb9a6f14ebb63217e6c351a61dbfeed24131e848fe7553", "started_at": "2026-06-16T12:20:37.798425+00:00", "latency_ms": 1678, "output": "Bug: `items = []` 是类属性，所有实例共享同一个列表。 \n最小修复：在 `__init__` 中为每个实例创建独立的列表。\n\nFIX: `self.items = []`", "usage": {"prompt_tokens": 99, "completion_tokens": 47, "total_tokens": 146, "cost": 0.0002509, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0002509, "upstream_inference_prompt_cost": 0.0001287, "upstream_inference_completions_cost": 0.0001222}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612440-5ULMSJ3hB4WWUnoDU6T7", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*self\\.items\\s*=\\s*\\[\\]\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-018", "suite": "debugging", "case_version": "0.3.0", "tags": ["python", "default-argument", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*def\\s+mark\\(ts=None\\)\\s*:", "flags": "is"}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面代码期望每次不传 ts 时使用当前时间，但默认时间只会在函数定义时计算一次。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的函数定义行>。\n\n```python\nfrom datetime import datetime\n\ndef mark(ts=datetime.utcnow()):\n return ts.isoformat()\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "96674f1c8091e56110c21b7b057178e05bd5225812543e3101e86fc6c5d2dba7", "started_at": "2026-06-16T12:20:39.491707+00:00", "latency_ms": 10736, "output": "默认参数值在函数定义时被求值并固化，因此 `ts=datetime.utcnow()` 仅在 `def` 语句执行时调用一次，之后每次无参调用 `mark()` 都会得到定义时刻的时间，而不是调用时的当前时间。\n\n最小修复：将默认值改为 `None`，并在函数体内重新获取当前时间。\n\n修复后的函数定义行：\n\nFIX: def mark(ts=None):", "usage": {"prompt_tokens": 105, "completion_tokens": 538, "total_tokens": 643, "cost": 0.0018896, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0018896, "upstream_inference_prompt_cost": 0.000168, "upstream_inference_completions_cost": 0.0017216}, "completion_tokens_details": {"reasoning_tokens": 447, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612441-lG3sWUVwoWKmjo2aRVPD", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*def\\s+mark\\(ts=None\\)\\s*:"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-019", "suite": "debugging", "case_version": "0.3.0", "tags": ["python", "method-call", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*return\\s+s\\.strip\\(\\)\\.lower\\(\\)\\s*`?", "flags": "is"}, "model": "deepseek/deepseek-v4-pro", "provider": null, "prompt": "下面代码期望返回小写字符串，但实际返回的是方法对象。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 return 行>。\n\n```python\ndef normalize(s):\n return s.strip().lower\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e9d483dafd7852b396cee6b27c6c25c888983460dba83c871f7f9a239dd601ef", "started_at": "2026-06-16T12:20:50.242232+00:00", "latency_ms": 4703, "output": "代码中 `lower` 后面缺少了调用括号 `()`，所以返回的是方法对象而不是调用结果。\n\n修复方法是为 `lower` 添加括号。\n\nFIX: return s.strip().lower()", "usage": {"prompt_tokens": 83, "completion_tokens": 43, "total_tokens": 126, "cost": 0.000235248, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.000235248, "upstream_inference_prompt_cost": 0.000115536, "upstream_inference_completions_cost": 0.000119712}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781612452-CRuC6gkVhtUqUfnd6q0A", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*return\\s+s\\.strip\\(\\)\\.lower\\(\\)\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-deepseek-deepseek-v4-pro-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-if-006", "suite": "instruction_following", "case_version": "0.3.0", "tags": ["json", "nested", "strict"], "scorer": "json_schema_lite", "expected": {"schema": {"type": "object", "required": ["version", "ready", "cases"], "additionalProperties": false, "properties": {"version": {"type": "string", "const": "v0.3"}, "ready": {"type": "boolean", "const": true}, "cases": {"type": "array", "minItems": 2, "maxItems": 2, "items": {"type": "object", 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