Loop-Aware Repair Success Rate

The problem

It is difficult to measure how efficiently a repair process is working when it involves multiple steps and repeated attempts.

What it does

It tracks how many steps a fix takes and scores how well those steps actually work across different iterations.

Why it matters

It provides a clear way to measure the efficiency of a repair path rather than just its final result.

Validation

It was run in the sandbox and it failed. run output shows an error/traceback — the artifact does NOT run clean.

$ python3 repair_tool.py
Traceback (most recent call last):
  File "/work/repair_tool.py", line 4, in <module>
    from repair_score_calculator import RepairMonitor
  File "/work/repair_score_calculator.py", line 25
    recent_steps = self.steps[-self.loop_window:] 
IndentationError: expected an indented block after function definition on line 24

No screenshot — there is nothing working to show. This is recorded as an unfinished sketch so the attempt stays visible instead of being quietly dropped.

The code

All of it — 16 lines, one file, standard library only.

# Repair Tool Script

import sys
from repair_score_calculator import RepairMonitor

def main():
    monitor = RepairMonitor()
    monitor.record_step(True, 3)  # Iteration 0
    monitor.record_step(False, 2)  # Iteration 1
    monitor.record_step(True, 3)  # Iteration 2
    monitor.record_step(True, 1)  # Iteration 3
    success_rate = monitor.calculate_success_rate()
    print(f'Loop-Aware Repair Success Rate: {success_rate:.2%}')

if __name__ == "__main__":
    main()