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Automatic Error Correction
Applies corrections to fixable errors in solution steps
Tracks correction success rates
"""
import re
from typing import List, Dict, Any
from sympy import sympify, simplify, N
def correct_solution(steps: List[str], errors: List[Dict[str, Any]]) -> Dict[str, Any]:
"""
Automatically correct fixable errors in solution steps.
Args:
steps: Original solution steps list
errors: List of error dictionaries
Returns:
Dictionary with corrected steps, correction log, and success rate
"""
corrected_steps = steps.copy()
correction_log = []
manual_review_needed = []
fixed_count = 0
for error in errors:
step_number = error.get("step_number", 0) - 1 # Convert to 0-based index
if step_number < 0 or step_number >= len(corrected_steps):
continue
error_type = error.get("type", "")
fixable = error.get("fixable", False)
if not fixable:
manual_review_needed.append(error)
continue
# Attempt correction based on error type
if error_type == "calculation_error":
success = _correct_arithmetic_error(corrected_steps, step_number, error)
if success:
fixed_count += 1
correction_log.append({
"step": step_number + 1,
"type": "arithmetic",
"original": steps[step_number],
"corrected": corrected_steps[step_number],
"reason": "Arithmetic calculation corrected"
})
else:
manual_review_needed.append(error)
elif error_type == "operation_mismatch":
success = _correct_operation_mismatch(corrected_steps, step_number, error)
if success:
fixed_count += 1
correction_log.append({
"step": step_number + 1,
"type": "operation_mismatch",
"original": steps[step_number],
"corrected": corrected_steps[step_number],
"reason": "Operation mismatch corrected"
})
else:
manual_review_needed.append(error)
else:
# Other error types need manual review
manual_review_needed.append(error)
# Calculate success rate
total_fixable = len([e for e in errors if e.get("fixable", False)])
if total_fixable > 0:
success_rate = fixed_count / total_fixable
else:
success_rate = 0.0
return {
"corrected_steps": corrected_steps,
"correction_log": correction_log,
"success_rate": success_rate,
"manual_review_needed": manual_review_needed,
"fixed_count": fixed_count,
"total_fixable": total_fixable
}
def _correct_arithmetic_error(steps: List[str], step_index: int, error: Dict[str, Any]) -> bool:
"""Correct arithmetic calculation error."""
try:
found = error.get("found", "")
correct = error.get("correct", "")
# Extract the incorrect result from found
found_nums = re.findall(r'\d+\.?\d*', found)
correct_nums = re.findall(r'\d+\.?\d*', correct)
if not found_nums or not correct_nums:
return False
incorrect_result = found_nums[-1]
correct_result = correct_nums[-1]
# Replace incorrect result with correct result in the step
step = steps[step_index]
# Replace the last occurrence of the incorrect result
corrected_step = step.replace(incorrect_result, correct_result, 1)
# If that didn't work, try more sophisticated replacement
if corrected_step == step:
# Try replacing the full expression
corrected_step = step.replace(found, correct)
steps[step_index] = corrected_step
return True
except Exception as e:
return False
def _correct_operation_mismatch(steps: List[str], step_index: int, error: Dict[str, Any]) -> bool:
"""Correct operation mismatch error."""
try:
description = error.get("description", "")
step = steps[step_index]
# Extract operation from description
# This is simplified - in production would use more sophisticated NLP
if "subtract" in description.lower() and "+" in step:
# Replace + with -
corrected_step = step.replace("+", "-", 1)
steps[step_index] = corrected_step
return True
elif "add" in description.lower() and "-" in step:
# Replace - with +
corrected_step = step.replace("-", "+", 1)
steps[step_index] = corrected_step
return True
return False
except Exception as e:
return False
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