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fcb838d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 | """
Boundary-condition capability probe for CodeCourt.
This script compares a weak baseline solver against a stronger solver on a
curated suite of small, adversarial, and boundary-heavy cases. The goal is to
produce one crisp artifact that answers: did the solver actually get better at
handling tricky edge conditions?
"""
from __future__ import annotations
import argparse
import json
import os
import sys
from pathlib import Path
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from agents.prompts import BRUTE_FORCE_SOLUTIONS, REFERENCE_SOLUTIONS
from oracle.executor import OracleExecutor
CASES = [
{
"case_id": "graph_shortest_path_single_node",
"capability": "boundary_conditions",
"archetype": "graph",
"task_id": 0,
"description": "Shortest-path solver must handle the smallest graph where source equals destination.",
"input": "1 0\n",
"expected": "0",
},
{
"case_id": "graph_shortest_path_two_hop",
"capability": "boundary_conditions",
"archetype": "graph",
"task_id": 0,
"description": "Shortest-path solver must reason beyond direct neighbors.",
"input": "3 2\n1 2 4\n2 3 5\n",
"expected": "9",
},
{
"case_id": "graph_bipartite_min_odd_cycle",
"capability": "boundary_conditions",
"archetype": "graph",
"task_id": 1,
"description": "Bipartite check must reject the smallest odd cycle.",
"input": "3 3\n1 2\n2 3\n1 3\n",
"expected": "NO",
},
{
"case_id": "array_lis_hidden_valley",
"capability": "boundary_conditions",
"archetype": "array",
"task_id": 2,
"description": "LIS must recover after an early overshoot instead of greedily locking in.",
"input": "4\n2 5 3 4\n",
"expected": "3",
},
{
"case_id": "dp_lcs_order_sensitive",
"capability": "boundary_conditions",
"archetype": "dp",
"task_id": 2,
"description": "LCS must respect order, not just character overlap.",
"input": "abc\nca\n",
"expected": "1",
},
{
"case_id": "dp_lcs_repeated_chars",
"capability": "boundary_conditions",
"archetype": "dp",
"task_id": 2,
"description": "LCS must count a subsequence rather than raw character membership.",
"input": "abc\nac\n",
"expected": "2",
},
]
def solver_code(mode: str, archetype: str, task_id: int) -> str:
key = (archetype, task_id)
if mode == "brute_force":
return BRUTE_FORCE_SOLUTIONS.get(key, "print(0)")
if mode == "reference":
return REFERENCE_SOLUTIONS.get(key, "print(0)")
raise ValueError(f"Unsupported mode: {mode}")
def run_suite(mode: str, time_limit: float, memory_limit_mb: int) -> dict:
executor = OracleExecutor(time_limit=time_limit, memory_limit_mb=memory_limit_mb)
results = []
for case in CASES:
code = solver_code(mode, case["archetype"], case["task_id"])
result = executor.run(
code=code,
stdin_input=case["input"],
expected_output=case["expected"],
)
results.append({
"case_id": case["case_id"],
"capability": case["capability"],
"archetype": case["archetype"],
"task_id": case["task_id"],
"description": case["description"],
"passed": result.passed,
"status": result.status,
"outcome": result.outcome,
"stdout": result.stdout,
"stderr": result.stderr,
"expected_output": case["expected"],
"execution_time": result.execution_time,
})
passed = sum(1 for item in results if item["passed"])
return {
"mode": mode,
"total_cases": len(results),
"passed_cases": passed,
"pass_rate": passed / max(len(results), 1),
"cases": results,
}
def build_summary(baseline: dict, trained: dict) -> dict:
baseline_map = {case["case_id"]: case for case in baseline["cases"]}
trained_map = {case["case_id"]: case for case in trained["cases"]}
improved_cases = []
for case in CASES:
case_id = case["case_id"]
before = baseline_map[case_id]
after = trained_map[case_id]
if not before["passed"] and after["passed"]:
improved_cases.append({
"case_id": case_id,
"description": case["description"],
"archetype": case["archetype"],
"task_id": case["task_id"],
})
return {
"suite_name": "boundary_conditions",
"claim": "The solver improves on small, adversarial boundary cases that break shortcut reasoning.",
"baseline_mode": baseline["mode"],
"trained_mode": trained["mode"],
"baseline_pass_rate": baseline["pass_rate"],
"trained_pass_rate": trained["pass_rate"],
"pass_rate_delta": trained["pass_rate"] - baseline["pass_rate"],
"baseline_passed_cases": baseline["passed_cases"],
"trained_passed_cases": trained["passed_cases"],
"improved_case_count": len(improved_cases),
"improved_cases": improved_cases,
}
def parse_args():
parser = argparse.ArgumentParser(description="Run the CodeCourt boundary-condition capability probe")
parser.add_argument("--baseline-mode", default="brute_force", choices=["brute_force", "reference"])
parser.add_argument("--trained-mode", default="reference", choices=["brute_force", "reference"])
parser.add_argument("--time-limit", type=float, default=2.0)
parser.add_argument("--memory-limit-mb", type=int, default=256)
parser.add_argument("--output", default="./outputs/capability_boundary_eval.json")
return parser.parse_args()
def main():
args = parse_args()
baseline = run_suite(args.baseline_mode, args.time_limit, args.memory_limit_mb)
trained = run_suite(args.trained_mode, args.time_limit, args.memory_limit_mb)
summary = build_summary(baseline, trained)
payload = {
"summary": summary,
"baseline": baseline,
"trained": trained,
}
output_path = Path(args.output)
output_path.parent.mkdir(parents=True, exist_ok=True)
output_path.write_text(json.dumps(payload, indent=2))
print(json.dumps(summary, indent=2))
print(f"Saved boundary probe to {output_path}")
if __name__ == "__main__":
main()
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