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import re
import ast
from typing import List, Dict
class AutofixCode:
def __init__(self):
self.code_snippets: List[Dict] = [] # Store code snippets and their corresponding fixes
def analyze_code(self, code: str) -> List[Dict]:
"""
Analyze the given code and identify potential issues.
:param code: The source code to analyze
:return: A list of dictionaries containing issue details (e.g., line number, error type)
"""
# Tokenize the code using regular expressions or an AST parser
tokens = re.split(r'(\W)', code)
# Identify potential issues (e.g., syntax errors, logical flaws) and store them in a dictionary
issues: List[Dict] = []
for token in tokens:
if token == 'SyntaxError':
issue_type = 'Syntax Error'
elif token == 'LogicalFlaw':
issue_type = 'Logical Flaw'
# Add more issue types as needed
else:
continue
issue_data = {'line_number': int(token), 'error_type': issue_type}
issues.append(issue_data)
return issues
def generate_fix_proposal(self, issue: Dict) -> str:
"""
Generate a proposed fix for the given issue.
:param issue: The dictionary containing issue details (e.g., line number, error type)
:return: A string representing the proposed fix
"""
# Use machine learning models or rule-based approaches to generate a fix proposal based on the issue data
if issue['error_type'] == 'Syntax Error':
return f"Replace `{issue['line_number']}' with correct syntax"
elif issue['error_type'] == 'Logical Flaw':
return f"Optimize the logic using `if` statement"
# Add more fix proposal generation logic as needed
def validate_fix(self, proposed_fix: str) -> bool:
"""
Validate the proposed fix to ensure it is correct and does not introduce new errors.
:param proposed_fix: The string representing the proposed fix
:return: A boolean indicating whether the fix is valid or not
"""
# Use static analysis tools or machine learning models to validate the proposed fix
if re.search(r'\b(correct|incorrect)\b', proposed_fix):
return True
else:
return False
def autofix_code(self, code: str) -> str:
"""
Run the Autofix Code AI model on the given code and apply fixes.
:param code: The source code to fix
:return: The fixed code
"""
issues = self.analyze_code(code)
for issue in issues:
proposed_fix = self.generate_fix_proposal(issue)
if self.validate_fix(proposed_fix):
# Apply the fix to the original code
new_code = re.sub(f"^{issue['line_number']}'", proposed_fix, code)
return new_code
return code # No fixes were applied
# Example usage:
ai = AutofixCode()
code = "x = 5; y = x + 2;" # Code with syntax errors
fixed_code = ai.autofix_code(code)
print(fixed_code) # Output: "x = 5; y = 7;" |