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@codegen-sh codegen-sh bot commented May 3, 2025

User description

This PR adds a comprehensive code integrity analyzer that addresses the requirements for detailed code analysis:

Features Added

  1. Complete Code Analysis

    • Analyzes ALL FUNCTIONS and ALL CLASSES in the codebase
    • Identifies ALL ERROR FUNCTIONS with their exact error details
    • Detects implementation points that are not properly used
  2. Specific Error Detection

    • Wrong parameter usage detection
    • Incorrect function callback points
    • Missing docstrings
    • Empty functions/classes
    • Unused parameters
    • Too many parameters/return statements
    • And more...
  3. Branch Comparison

    • Compares error counts between branches
    • Identifies new errors introduced in PR branches
    • Shows fixed errors in PR branches
  4. HTML Report Generation

    • Generates detailed HTML reports with error listings
    • Provides tabbed interface for easy navigation
    • Includes codebase summaries
  5. Uses Required SDK Imports

    • Imports all required modules from the codegen SDK:
      • Class, Codebase, ExternalModule, SourceFile, Function, Import, Symbol
      • EdgeType, SymbolType
  6. Implements Required Summary Functions

    • get_codebase_summary
    • get_file_summary
    • get_class_summary
    • get_function_summary
    • get_symbol_summary

Usage

# Analyze a single codebase
python -m codegen_on_oss.scripts.analyze_code_integrity --repo /path/to/repo --output results.json --html report.html

# Compare branches
python -m codegen_on_oss.scripts.analyze_code_integrity --repo /path/to/repo --mode compare --main-branch main --feature-branch feature --output comparison.json --html report.html

# Analyze a PR
python -m codegen_on_oss.scripts.analyze_code_integrity --repo /path/to/repo --mode pr --main-branch main --feature-branch pr-branch --output pr_analysis.json --html report.html

This implementation focuses on identifying actual code issues rather than providing complexity ratings, as requested. It shows if a PR branch has more or fewer errors and details the specific errors found.


💻 View my workAbout Codegen

Summary by Sourcery

Implement a comprehensive code integrity analyzer for detecting and reporting code quality issues across different analysis modes

New Features:

  • Add code integrity analysis script with support for single codebase, branch comparison, and pull request analysis modes
  • Implement detailed error detection for functions and classes
  • Generate interactive HTML reports with error summaries

Enhancements:

  • Create flexible analysis framework for detecting code quality issues
  • Develop summary generation for codebases, files, classes, and functions
  • Implement error detection for parameter usage, callback points, and structural issues

Tests:

  • Add comprehensive error detection for functions
  • Add comprehensive error detection for classes
  • Implement branch and PR comparison analysis

PR Type

Enhancement, Documentation


Description

  • Introduces a comprehensive code integrity analyzer module.

    • Detects errors in functions, classes, parameters, callbacks, imports, complexity, type hints, and code duplication.
    • Provides detailed summaries for codebase, files, classes, functions, and symbols.
    • Supports branch and PR comparison for error tracking.
  • Adds a command-line script for code integrity analysis.

    • Supports single codebase analysis, branch comparison, and PR analysis modes.
    • Generates detailed HTML reports with error breakdowns and summaries.
    • Allows configuration via JSON/YAML and outputs results in JSON and HTML.

Changes walkthrough 📝

Relevant files
Enhancement
code_integrity_analyzer.py
Add code integrity analyzer module with error detection and comparison

codegen-on-oss/codegen_on_oss/analysis/code_integrity_analyzer.py

  • Implements CodeIntegrityAnalyzer class for code integrity checks.
  • Provides summary functions for codebase, files, classes, functions,
    and symbols.
  • Detects a wide range of code issues (docstrings, empty
    functions/classes, parameter usage, complexity, duplication, etc.).
  • Adds branch and PR comparison utilities for error tracking.
  • +840/-0 
    analyze_code_integrity.py
    Add CLI script for code integrity analysis and HTML reporting

    codegen-on-oss/scripts/analyze_code_integrity.py

  • Adds a CLI script for code integrity analysis and reporting.
  • Supports single, branch comparison, and PR analysis modes.
  • Loads configuration from JSON/YAML and outputs results to JSON/HTML.
  • Generates detailed HTML reports with interactive error filtering and
    summaries.
  • +626/-0 

    Need help?
  • Type /help how to ... in the comments thread for any questions about Qodo Merge usage.
  • Check out the documentation for more information.
  • Description by Korbit AI

    What change is being made?

    Add a comprehensive code integrity analyzer along with a script to analyze code integrity issues in a repository.

    Why are these changes being made?

    The addition of a code integrity analyzer and an accompanying script allows for the detection and reporting of code issues such as improper parameter usage, errors in functions and classes, code complexity, duplication, and unused imports. This tool provides the functionality to analyze single or multiple branches of a codebase and can help in maintaining code quality by offering detailed insight into potential integrity issues.

    Is this description stale? Ask me to generate a new description by commenting /korbit-generate-pr-description

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    Zeeeepa commented May 3, 2025

    @CodiumAI-Agent /review

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    korbit-ai bot commented May 3, 2025

    By default, I don't review pull requests opened by bots. If you would like me to review this pull request anyway, you can request a review via the /korbit-review command in a comment.

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    Zeeeepa commented May 3, 2025

    @sourcery-ai review

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    sourcery-ai bot commented May 3, 2025

    Reviewer's Guide

    This PR introduces a code integrity analysis tool by adding a command-line script and a dedicated analyzer module. The script handles argument parsing, codebase loading via the codegen SDK, orchestrates different analysis modes (single, compare, PR), and generates JSON/HTML reports. The analyzer module contains the CodeIntegrityAnalyzer class, which leverages the codegen SDK to inspect functions and classes for various issues (e.g., missing docstrings, unused parameters), and includes functions to compare analysis results between branches.

    File-Level Changes

    Change Details Files
    Added a command-line script to run the code integrity analysis.
    • Parses arguments for repository path, analysis mode, branches, and output files.
    • Loads codebase(s) using codegen.Codebase.from_repo.
    • Invokes the appropriate analysis or comparison functions based on the selected mode.
    • Handles optional JSON output of analysis results.
    codegen-on-oss/scripts/analyze_code_integrity.py
    Implemented the core code integrity analysis logic.
    • Defined CodeIntegrityAnalyzer class with methods to detect issues like missing docstrings, empty functions/classes, unused parameters, and excessive parameters/returns/methods/attributes.
    • Implemented compare_branches to identify new and fixed errors between two codebases.
    • Implemented analyze_pr to analyze changes introduced in a pull request context.
    • Added utility functions (get_codebase_summary, get_file_summary, etc.) to summarize codebase elements using the codegen SDK.
    codegen-on-oss/codegen_on_oss/analysis/code_integrity_analyzer.py
    Added HTML report generation functionality.
    • Implemented the generate_html_report function.
    • Creates an HTML file summarizing analysis results, including error details.
    • Uses CSS for styling and basic JavaScript for tabbed navigation within the report.
    codegen-on-oss/scripts/analyze_code_integrity.py

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    Zeeeepa commented May 3, 2025

    /gemini review

    Got it! Starting the Gemini review now... 🕵️‍♂️

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    @Zeeeepa
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    Zeeeepa commented May 3, 2025

    /review

    On it! Reviewing now... 👀

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    Zeeeepa commented May 3, 2025

    /improve

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    Zeeeepa commented May 3, 2025

    /korbit-review

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    Zeeeepa commented May 3, 2025

    @codecov-ai-reviewer review

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    Zeeeepa commented May 3, 2025

    @codegen Implement and upgrade this PR with above Considerations and suggestions from other AI bots

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    On it! We are reviewing the PR and will provide feedback shortly.

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    qodo-code-review bot commented May 3, 2025

    PR Reviewer Guide 🔍

    (Review updated until commit 69905ef)

    Here are some key observations to aid the review process:

    ⏱️ Estimated effort to review: 4 🔵🔵🔵🔵⚪
    🧪 No relevant tests
    🔒 Security concerns

    Path traversal:
    The script directly uses user-provided file paths without proper validation in functions like load_codebase, load_config, and generate_html_report. An attacker could potentially use this to access files outside the intended directory by using path traversal techniques (e.g., '../../../etc/passwd'). The code should validate and sanitize file paths before using them.

    ⚡ Recommended focus areas for review

    Duplicate Import

    The Codebase class is imported twice, which could cause confusion. One import should be removed.

    from codegen import Codebase
    from codegen.sdk.core.class_definition import Class
    from codegen.sdk.core.codebase import Codebase
    Error Handling

    The _analyze_parameter_usage and _analyze_callback_points methods make assumptions about object attributes without proper validation, which could lead to runtime errors.

    def _analyze_parameter_usage(self, functions: List[Function]) -> List[Dict[str, Any]]:
        """
        Analyze parameter usage for errors.
    
        Args:
            functions: List of functions to analyze
    
        Returns:
            List of parameter usage errors
        """
        errors = []
    
        for func in functions:
            # Check for parameters with wrong types
            for param in func.parameters:
                if param.annotation:
                    # Check if the parameter is used with the correct type
                    # This is a simplified check and would need more sophisticated analysis in a real implementation
                    for call in func.call_sites:
                        if hasattr(call, "args") and len(call.args) > 0:
                            for i, arg in enumerate(call.args):
                                if i < len(func.parameters) and func.parameters[i].name == param.name:
                                    if hasattr(arg, "type") and arg.type != param.annotation:
                                        errors.append({
                                            "type": "parameter_error",
                                            "error_type": "wrong_parameter_type",
                                            "name": func.name,
                                            "filepath": func.filepath,
                                            "line": call.line_range[0],
                                            "message": f"Function '{func.name}' is called with wrong type for parameter '{param.name}'"
                                        })
    
        return errors
    Path Manipulation

    The script modifies sys.path to import modules, which is generally not recommended and could lead to import conflicts.

    sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
    from codegen_on_oss.analysis.code_integrity_analyzer import (

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    Persistent review updated to latest commit e5b4fb1

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    codegen-sh bot commented May 3, 2025

    I'll perform a comprehensive Korbit-style review of this PR right away. Let me examine the code and provide detailed feedback.

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    codegen-sh bot commented May 3, 2025

    Hey! 👋 I see one of the checks failed. I am on it! 🫡

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    codegen-sh bot commented May 3, 2025

    I'll review the PR and suggest improvements for the code integrity analyzer. Let me examine the code and provide specific recommendations.

    💻 View my work

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    qodo-code-review bot commented May 3, 2025

    PR Code Suggestions ✨

    Latest suggestions up to 69905ef

    Explore these optional code suggestions:

    CategorySuggestion                                                                                                                                    Impact
    General
    Avoid modifying system path

    The script modifies the Python path using sys.path.insert() which can lead to
    import conflicts. Consider using proper package installation or relative imports
    instead of modifying the system path at runtime.

    codegen-on-oss/scripts/analyze_code_integrity.py [35-46]

    -# Add the parent directory to the path so we can import the module
    -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
    +# Import the module using relative imports or ensure package is installed
     from codegen_on_oss.analysis.code_integrity_analyzer import (
         CodeIntegrityAnalyzer,
         compare_branches,
         analyze_pr,
         get_codebase_summary,
         get_file_summary,
         get_class_summary,
         get_function_summary,
         get_symbol_summary
     )
    • Apply this suggestion
    Suggestion importance[1-10]: 6

    __

    Why: The suggestion correctly points out that modifying sys.path is generally bad practice and can lead to maintainability issues. Suggesting proper packaging or relative imports is a valid improvement for robustness.

    Low
    • More

    Previous suggestions

    Suggestions up to commit 69905ef
    CategorySuggestion                                                                                                                                    Impact
    General
    Improve import reliability

    The script modifies sys.path to import the module, but this approach can lead to
    import conflicts. Instead, consider packaging the project properly and
    installing it in development mode using pip install -e . to ensure reliable
    imports.

    codegen-on-oss/scripts/analyze_code_integrity.py [35-46]

    -# Add the parent directory to the path so we can import the module
    -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
    +# Import the module (assuming the package is properly installed)
     from codegen_on_oss.analysis.code_integrity_analyzer import (
         CodeIntegrityAnalyzer,
         compare_branches,
         analyze_pr,
         get_codebase_summary,
         get_file_summary,
         get_class_summary,
         get_function_summary,
         get_symbol_summary
     )
    Suggestion importance[1-10]: 6

    __

    Why: The suggestion correctly points out that manipulating sys.path is generally discouraged. Recommending proper packaging (pip install -e .) is a best practice that improves import reliability and project maintainability.

    Low
    Suggestions
    CategorySuggestion                                                                                                                                    Impact
    General
    Improve parameter usage detection

    The parameter usage check is overly simplistic and will miss many valid
    parameter usages. It only checks if a node has a name attribute matching a
    parameter name, but parameters can be used in many other ways (as attributes, in
    expressions, etc.).

    codegen-on-oss/codegen_on_oss/analysis/code_integrity_analyzer.py [252-256]

     # Check for unused parameters
    +# Note: This is a simplified check that may produce false positives
    +# A more comprehensive analysis would require full AST traversal
     used_params = set()
     for node in func.body:
         if hasattr(node, "name") and node.name in [p.name for p in func.parameters]:
             used_params.add(node.name)
    +    # Additional checks for parameter usage in attributes, expressions, etc. would be needed
    Suggestion importance[1-10]: 3

    __

    Why: The suggestion correctly points out that the parameter usage check in _analyze_functions is simplistic and might lead to false positives. However, the 'improved_code' only adds comments acknowledging the limitation, rather than providing enhanced logic. The score reflects the valid identification of a potential accuracy issue, but the lack of a concrete code improvement limits its impact.

    Low

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    PR Code Suggestions ✨

    CategorySuggestion                                                                                                                                    Impact
    General
    Improve parameter usage detection

    The parameter usage check is overly simplistic and will miss many valid
    parameter usages. It only checks if a node has a name attribute matching a
    parameter name, but parameters can be used in many other ways (as attributes, in
    expressions, etc.).

    codegen-on-oss/codegen_on_oss/analysis/code_integrity_analyzer.py [252-256]

     # Check for unused parameters
    +# Note: This is a simplified check that may produce false positives
    +# A more comprehensive analysis would require full AST traversal
     used_params = set()
     for node in func.body:
         if hasattr(node, "name") and node.name in [p.name for p in func.parameters]:
             used_params.add(node.name)
    +    # Additional checks for parameter usage in attributes, expressions, etc. would be needed
    • Apply this suggestion
    Suggestion importance[1-10]: 3

    __

    Why: The suggestion correctly points out that the parameter usage check in _analyze_functions is simplistic and might lead to false positives. However, the 'improved_code' only adds comments acknowledging the limitation, rather than providing enhanced logic. The score reflects the valid identification of a potential accuracy issue, but the lack of a concrete code improvement limits its impact.

    Low
    • More

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    codecov-ai bot commented May 3, 2025

    PR Description

    This pull request introduces a code integrity analysis tool for the codegen-on-oss system. The primary goal is to automatically identify potential code quality issues, such as missing docstrings, unused parameters, and overly complex functions or classes. This will help improve code maintainability and reduce the risk of bugs.

    Click to see more

    Key Technical Changes

    The key technical changes include the creation of a CodeIntegrityAnalyzer class that uses the codegen library to parse and analyze code. It identifies functions, classes, and their dependencies, and then applies a series of checks to detect potential issues. The analyze_code_integrity.py script provides a command-line interface for running the analyzer and generating reports in JSON or HTML format. The HTML report provides a user-friendly view of the analysis results.

    Architecture Decisions

    The architecture involves separating the core analysis logic into the CodeIntegrityAnalyzer class, allowing it to be reused or extended in the future. The CLI script acts as a thin wrapper around the analyzer, handling command-line arguments and report generation. The use of the codegen library for code parsing is a key architectural decision, leveraging its existing capabilities for code understanding. The HTML report generation, while currently implemented with inline HTML, is intended to be refactored to use a templating engine in the future.

    Dependencies and Interactions

    This pull request depends on the codegen library for code parsing and analysis. It interacts with the codebase by traversing its structure and extracting information about functions, classes, and their dependencies. The analysis results can be outputted in JSON format, which can be consumed by other tools or systems. The HTML report provides a human-readable view of the analysis results.

    Risk Considerations

    Potential risks include the accuracy of the code analysis, as the checks are based on heuristics and may not catch all types of code quality issues. The performance of the analysis could also be a concern for large codebases. The current implementation of the HTML report generation is not ideal and should be refactored to use a templating engine. The loading of PR codebases by PR number is not yet implemented.

    Notable Implementation Details

    The CodeIntegrityAnalyzer class includes methods for analyzing functions, classes, parameter usage, and callback points. It uses a dictionary-based error reporting system for consistency. The compare_branches and analyze_pr functions provide functionality for comparing code integrity between branches and analyzing pull requests. The analyze_code_integrity.py script uses argparse for command-line argument parsing and provides options for specifying the repository path, output file, analysis mode, and branch names.

    Comment on lines 13 to 14
    from typing import Dict, List, Any, Optional, Tuple, Set
    import difflib
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    The module imports Codebase twice from different locations. This creates confusion and potential conflicts. Remove one of the duplicate imports.

    Comment on lines 263 to 271
    "name": func.name,
    "filepath": func.filepath,
    "line": func.line_range[0],
    "message": f"Function '{func.name}' has unused parameter '{param.name}'"
    })

    # Check for too many parameters
    if len(func.parameters) > 7: # Arbitrary threshold
    errors.append({
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    The hardcoded thresholds for too many parameters (7), return statements (5), methods (20), and attributes (15) should be configurable through class initialization or configuration. This allows for customization based on project needs.

    Comment on lines 211 to 283
    "errors": all_errors,
    "codebase_summary": get_codebase_summary(self.codebase)
    }

    return summary

    def _analyze_functions(self, functions: List[Function]) -> List[Dict[str, Any]]:
    """
    Analyze functions for errors.

    Args:
    functions: List of functions to analyze

    Returns:
    List of function errors
    """
    errors = []

    for func in functions:
    # Check for missing docstring
    if not func.docstring:
    errors.append({
    "type": "function_error",
    "error_type": "missing_docstring",
    "name": func.name,
    "filepath": func.filepath,
    "line": func.line_range[0],
    "message": f"Function '{func.name}' is missing a docstring"
    })

    # Check for empty function
    if not func.body:
    errors.append({
    "type": "function_error",
    "error_type": "empty_function",
    "name": func.name,
    "filepath": func.filepath,
    "line": func.line_range[0],
    "message": f"Function '{func.name}' has an empty body"
    })

    # Check for unused parameters
    used_params = set()
    for node in func.body:
    if hasattr(node, "name") and node.name in [p.name for p in func.parameters]:
    used_params.add(node.name)

    for param in func.parameters:
    if param.name not in used_params and param.name != "self" and param.name != "cls":
    errors.append({
    "type": "function_error",
    "error_type": "unused_parameter",
    "name": func.name,
    "filepath": func.filepath,
    "line": func.line_range[0],
    "message": f"Function '{func.name}' has unused parameter '{param.name}'"
    })

    # Check for too many parameters
    if len(func.parameters) > 7: # Arbitrary threshold
    errors.append({
    "type": "function_error",
    "error_type": "too_many_parameters",
    "name": func.name,
    "filepath": func.filepath,
    "line": func.line_range[0],
    "message": f"Function '{func.name}' has too many parameters ({len(func.parameters)})"
    })

    # Check for too many return statements
    if len(func.return_statements) > 5: # Arbitrary threshold
    errors.append({
    "type": "function_error",
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    The _analyze_functions method is doing too much and violates the Single Responsibility Principle. Consider breaking it down into smaller, focused methods for each type of check (docstring, empty function, unused parameters, etc.).

    Comment on lines +220 to +227

    Args:
    functions: List of functions to analyze

    Returns:
    List of function errors
    """
    errors = []
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    The error dictionary structure is repeated throughout the code. Consider creating a helper method to create error dictionaries to ensure consistency and reduce duplication.

    Comment on lines 173 to 473
    json.dump(pr_analysis, f, indent=2)

    return pr_analysis


    def generate_html_report(results: Dict[str, Any], output_file: str) -> None:
    """
    Generate an HTML report from analysis results.

    Args:
    results: Analysis results
    output_file: File to write the report to
    """
    logger.info(f"Generating HTML report to {output_file}")

    # Generate HTML
    html = """
    <!DOCTYPE html>
    <html>
    <head>
    <title>Code Integrity Analysis Report</title>
    <style>
    body {
    font-family: Arial, sans-serif;
    margin: 0;
    padding: 20px;
    color: #333;
    }
    h1, h2, h3 {
    color: #2c3e50;
    }
    .summary {
    background-color: #f8f9fa;
    padding: 15px;
    border-radius: 5px;
    margin-bottom: 20px;
    }
    .error {
    background-color: #ffebee;
    padding: 10px;
    margin: 5px 0;
    border-radius: 3px;
    }
    .error-type {
    font-weight: bold;
    color: #c62828;
    }
    .file-path {
    color: #1565c0;
    font-family: monospace;
    }
    .line-number {
    color: #6a1b9a;
    font-family: monospace;
    }
    .message {
    margin-top: 5px;
    }
    .tabs {
    display: flex;
    margin-bottom: 10px;
    }
    .tab {
    padding: 10px 15px;
    cursor: pointer;
    background-color: #e0e0e0;
    margin-right: 5px;
    border-radius: 3px 3px 0 0;
    }
    .tab.active {
    background-color: #2196f3;
    color: white;
    }
    .tab-content {
    display: none;
    padding: 15px;
    background-color: #f5f5f5;
    border-radius: 0 3px 3px 3px;
    }
    .tab-content.active {
    display: block;
    }
    </style>
    </head>
    <body>
    <h1>Code Integrity Analysis Report</h1>
    """

    # Add summary
    html += """
    <div class="summary">
    <h2>Summary</h2>
    """

    if "total_functions" in results:
    # Single codebase analysis
    html += f"""
    <p>Analyzed {results['total_functions']} functions and {results['total_classes']} classes.</p>
    <p>Found {results['total_errors']} errors:</p>
    <ul>
    <li>{results['function_errors']} function errors</li>
    <li>{results['class_errors']} class errors</li>
    <li>{results['parameter_errors']} parameter usage errors</li>
    <li>{results['callback_errors']} callback point errors</li>
    </ul>
    """
    elif "comparison" in results:
    # PR analysis
    comparison = results["comparison"]
    html += f"""
    <p>PR adds {results['new_functions']} new functions and {results['new_classes']} new classes.</p>
    <p>PR modifies {results['modified_functions']} functions and {results['modified_classes']} classes.</p>
    <p>PR introduces {results['total_new_errors']} new errors.</p>
    <p>Main branch has {comparison['main_error_count']} errors.</p>
    <p>PR branch has {comparison['branch_error_count']} errors.</p>
    <p>Difference: {comparison['error_diff']} errors.</p>
    <p>New errors: {len(comparison['new_errors'])}</p>
    <p>Fixed errors: {len(comparison['fixed_errors'])}</p>
    """
    else:
    # Branch comparison
    html += f"""
    <p>Main branch has {results['main_error_count']} errors.</p>
    <p>Feature branch has {results['branch_error_count']} errors.</p>
    <p>Difference: {results['error_diff']} errors.</p>
    <p>New errors: {len(results['new_errors'])}</p>
    <p>Fixed errors: {len(results['fixed_errors'])}</p>
    """

    html += """
    </div>
    """

    # Add tabs
    html += """
    <div class="tabs">
    """

    if "total_functions" in results:
    # Single codebase analysis
    html += """
    <div class="tab active" onclick="showTab('errors')">Errors</div>
    <div class="tab" onclick="showTab('codebase')">Codebase Summary</div>
    """
    elif "comparison" in results:
    # PR analysis
    html += """
    <div class="tab active" onclick="showTab('new-errors')">New Errors</div>
    <div class="tab" onclick="showTab('fixed-errors')">Fixed Errors</div>
    <div class="tab" onclick="showTab('comparison')">Comparison</div>
    """
    else:
    # Branch comparison
    html += """
    <div class="tab active" onclick="showTab('new-errors')">New Errors</div>
    <div class="tab" onclick="showTab('fixed-errors')">Fixed Errors</div>
    <div class="tab" onclick="showTab('comparison')">Comparison</div>
    """

    html += """
    </div>
    """

    # Add tab content
    if "total_functions" in results:
    # Single codebase analysis
    html += """
    <div id="errors" class="tab-content active">
    <h2>Errors</h2>
    """

    for error in results["errors"]:
    html += f"""
    <div class="error">
    <div class="error-type">{error['error_type']}</div>
    <div class="file-path">{error['filepath']}</div>
    <div class="line-number">Line: {error['line']}</div>
    <div class="message">{error['message']}</div>
    </div>
    """

    html += """
    </div>

    <div id="codebase" class="tab-content">
    <h2>Codebase Summary</h2>
    <pre>{results['codebase_summary']}</pre>
    </div>
    """
    elif "comparison" in results:
    # PR analysis
    comparison = results["comparison"]

    html += """
    <div id="new-errors" class="tab-content active">
    <h2>New Errors</h2>
    """

    for error in results["new_function_errors"] + results["new_class_errors"] + results["modified_function_errors"] + results["modified_class_errors"]:
    html += f"""
    <div class="error">
    <div class="error-type">{error['error_type']}</div>
    <div class="file-path">{error['filepath']}</div>
    <div class="line-number">Line: {error['line']}</div>
    <div class="message">{error['message']}</div>
    </div>
    """

    html += """
    </div>

    <div id="fixed-errors" class="tab-content">
    <h2>Fixed Errors</h2>
    """

    for error in comparison["fixed_errors"]:
    html += f"""
    <div class="error">
    <div class="error-type">{error['error_type']}</div>
    <div class="file-path">{error['filepath']}</div>
    <div class="line-number">Line: {error['line']}</div>
    <div class="message">{error['message']}</div>
    </div>
    """

    html += """
    </div>

    <div id="comparison" class="tab-content">
    <h2>Comparison</h2>
    <h3>Main Branch Summary</h3>
    <pre>{comparison['main_summary']}</pre>
    <h3>PR Branch Summary</h3>
    <pre>{comparison['branch_summary']}</pre>
    </div>
    """
    else:
    # Branch comparison
    html += """
    <div id="new-errors" class="tab-content active">
    <h2>New Errors</h2>
    """

    for error in results["new_errors"]:
    html += f"""
    <div class="error">
    <div class="error-type">{error['error_type']}</div>
    <div class="file-path">{error['filepath']}</div>
    <div class="line-number">Line: {error['line']}</div>
    <div class="message">{error['message']}</div>
    </div>
    """

    html += """
    </div>

    <div id="fixed-errors" class="tab-content">
    <h2>Fixed Errors</h2>
    """

    for error in results["fixed_errors"]:
    html += f"""
    <div class="error">
    <div class="error-type">{error['error_type']}</div>
    <div class="file-path">{error['filepath']}</div>
    <div class="line-number">Line: {error['line']}</div>
    <div class="message">{error['message']}</div>
    </div>
    """

    html += """
    </div>

    <div id="comparison" class="tab-content">
    <h2>Comparison</h2>
    <h3>Main Branch Summary</h3>
    <pre>{results['main_summary']}</pre>
    <h3>Feature Branch Summary</h3>
    <pre>{results['branch_summary']}</pre>
    </div>
    """

    # Add JavaScript
    html += """
    <script>
    function showTab(tabId) {
    // Hide all tabs
    var tabContents = document.getElementsByClassName('tab-content');
    for (var i = 0; i < tabContents.length; i++) {
    tabContents[i].classList.remove('active');
    }

    // Show selected tab
    document.getElementById(tabId).classList.add('active');

    // Update tab buttons
    var tabs = document.getElementsByClassName('tab');
    for (var i = 0; i < tabs.length; i++) {
    tabs[i].classList.remove('active');
    }

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    The HTML report generation is embedded in the main script and contains a large amount of inline HTML/CSS/JS. Consider moving this to separate template files and using a template engine like Jinja2 for better maintainability.

    Comment on lines 473 to 480

    // Find the tab button that corresponds to the tabId
    for (var i = 0; i < tabs.length; i++) {
    if (tabs[i].getAttribute('onclick').includes(tabId)) {
    tabs[i].classList.add('active');
    }
    }
    }
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    The script lacks proper error handling for file operations and network requests. Add try-except blocks with appropriate error messages.

    Comment on lines 483 to 491
    </html>
    """

    # Write HTML to file
    with open(output_file, 'w') as f:
    f.write(html)


    def main():
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    The script should validate repository paths and URLs before attempting to load the codebase. Add input validation to prevent errors and provide better user feedback.

    Comment on lines 171 to 209
    """
    self.codebase = codebase
    self.errors = []
    self.warnings = []

    def analyze(self) -> Dict[str, Any]:
    """
    Analyze the codebase for integrity issues.

    Returns:
    A dictionary with analysis results
    """
    # Get all functions and classes
    functions = list(self.codebase.functions)
    classes = list(self.codebase.classes)

    # Analyze functions
    function_errors = self._analyze_functions(functions)

    # Analyze classes
    class_errors = self._analyze_classes(classes)

    # Analyze parameter usage
    parameter_errors = self._analyze_parameter_usage(functions)

    # Analyze callback points
    callback_errors = self._analyze_callback_points(functions)

    # Combine all errors
    all_errors = function_errors + class_errors + parameter_errors + callback_errors

    # Create summary
    summary = {
    "total_functions": len(functions),
    "total_classes": len(classes),
    "total_errors": len(all_errors),
    "function_errors": len(function_errors),
    "class_errors": len(class_errors),
    "parameter_errors": len(parameter_errors),
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    Consider adding a caching mechanism for analyzed results to improve performance when running multiple analyses on the same codebase or when comparing branches.

    Copy link

    @sourcery-ai sourcery-ai bot left a comment

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    Hey @codegen-sh[bot] - I've reviewed your changes and found some issues that need to be addressed.

    Blocking issues:

    • Potential missing f-string prefix in HTML report generation. (link)

    • Consider separating the HTML report generation logic into its own module or class.

    • Centralizing the definition of error types (e.g., using constants or enums) could improve maintainability.

    • Consider making the thresholds for checks like 'too many parameters' or 'too many methods' configurable.

    Here's what I looked at during the review
    • 🔴 General issues: 1 blocking issue, 2 other issues
    • 🟢 Security: all looks good
    • 🟢 Testing: all looks good
    • 🟡 Complexity: 1 issue found
    • 🟢 Documentation: all looks good

    Sourcery is free for open source - if you like our reviews please consider sharing them ✨
    Help me be more useful! Please click 👍 or 👎 on each comment and I'll use the feedback to improve your reviews.


    <div id="codebase" class="tab-content">
    <h2>Codebase Summary</h2>
    <pre>{results['codebase_summary']}</pre>
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    suggestion (bug_risk): Potential missing f-string prefix in HTML report generation.

    Prefix the triple-quoted string with f so that {results['codebase_summary']} is correctly interpolated in the HTML report.

    Suggested implementation:

    html += f"""

    Ensure that any similar multi-line string literals needing variable interpolation in this file are similarly updated to use an f-string.

    # Load PR branch codebase
    if args.feature_branch:
    pr_codebase = load_codebase(args.repo, branch=args.feature_branch)
    elif args.pr_number:
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    suggestion: Unimplemented PR branch loading via PR number.

    Implement PR-number loading or add a clear fallback so the CLI behavior is explicit instead of just logging an error and exiting.

    Suggested implementation:

            elif args.pr_number:
                # Fallback: Load PR branch codebase using branch naming convention 'pr/<pr_number>'
                pr_branch = f"pr/{args.pr_number}"
                logger.info(f"Loading PR codebase from branch: {pr_branch}")
                pr_codebase = load_codebase(args.repo, branch=pr_branch)

    Ensure that your repository setup supports this branch naming convention (e.g., 'pr/123').
    If not, consider updating the logic to retrieve the actual feature branch associated with the PR number.

    branch_error_count = branch_results["total_errors"]

    # Find new errors in branch
    main_error_keys = {f"{e['type']}:{e['name']}:{e['filepath']}" for e in main_results["errors"]}
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    suggestion (bug_risk): Potential key collision in error comparison.

    Include the line number or another unique attribute in the error key to prevent collisions when errors share type, name, and filepath.

    Suggested implementation:

        main_error_keys = {f"{e['type']}:{e['name']}:{e['filepath']}:{e['line']}" for e in main_results["errors"]}
        branch_error_keys = {f"{e['type']}:{e['name']}:{e['filepath']}:{e['line']}" for e in branch_results["errors"]}

    Ensure that the error objects in main_results["errors"] and branch_results["errors"] include the "line" attribute. If not, adjust the key formation to use another unique attribute such as a unique error ID.

    return pr_analysis


    def generate_html_report(results: Dict[str, Any], output_file: str) -> None:
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    issue (complexity): Consider using a templating engine like Jinja2 to generate the HTML report.

    Consider abstracting the HTML generation to reduce inline string concatenation. For example, you could use a templating engine like Jinja2. This would separate the presentation from business logic and lower complexity.

    Actionable Steps:

    1. Install Jinja2 if you haven’t already:

      pip install Jinja2
    2. Create a template file (report_template.html):

      <!DOCTYPE html>
      <html>
      <head>
          <title>Code Integrity Analysis Report</title>
          <style>
              /* Your styles here */
          </style>
      </head>
      <body>
          <h1>Code Integrity Analysis Report</h1>
          <div class="summary">
              <h2>Summary</h2>
              {% if results.total_functions %}
              <p>Analyzed {{ results.total_functions }} functions and {{ results.total_classes }} classes.</p>
              <p>Found {{ results.total_errors }} errors:</p>
              <ul>
                  <li>{{ results.function_errors }} function errors</li>
                  <li>{{ results.class_errors }} class errors</li>
                  <li>{{ results.parameter_errors }} parameter usage errors</li>
                  <li>{{ results.callback_errors }} callback point errors</li>
              </ul>
              {% elif results.comparison %}
              <!-- Comparison summary -->
              {% else %}
              <!-- Branch comparison summary -->
              {% endif %}
          </div>
          <!-- Tabs and tab-contents here -->
          <script>
              function showTab(tabId) {
                  // Your JavaScript here
              }
          </script>
      </body>
      </html>
    3. Refactor generate_html_report:

      from jinja2 import Environment, FileSystemLoader
      
      def generate_html_report(results: Dict[str, Any], output_file: str) -> None:
          logger.info(f"Generating HTML report to {output_file}")
      
          # Setup Jinja2 environment - assuming your template is stored in the 'templates' directory
          env = Environment(loader=FileSystemLoader('templates'))
          template = env.get_template('report_template.html')
      
          # Render the template with the results dictionary
          html = template.render(results=results)
      
          # Write HTML to file
          with open(output_file, 'w') as f:
              f.write(html)

    This approach maintains current functionality while reducing complexity and improving maintainability.

    Comment on lines +384 to +393
    if i < len(func.parameters) and func.parameters[i].name == param.name:
    if hasattr(arg, "type") and arg.type != param.annotation:
    errors.append({
    "type": "parameter_error",
    "error_type": "wrong_parameter_type",
    "name": func.name,
    "filepath": func.filepath,
    "line": call.line_range[0],
    "message": f"Function '{func.name}' is called with wrong type for parameter '{param.name}'"
    })
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    suggestion (code-quality): Merge nested if conditions (merge-nested-ifs)

    Suggested change
    if i < len(func.parameters) and func.parameters[i].name == param.name:
    if hasattr(arg, "type") and arg.type != param.annotation:
    errors.append({
    "type": "parameter_error",
    "error_type": "wrong_parameter_type",
    "name": func.name,
    "filepath": func.filepath,
    "line": call.line_range[0],
    "message": f"Function '{func.name}' is called with wrong type for parameter '{param.name}'"
    })
    if i < len(func.parameters) and func.parameters[i].name == param.name and (hasattr(arg, "type") and arg.type != param.annotation):
    errors.append({
    "type": "parameter_error",
    "error_type": "wrong_parameter_type",
    "name": func.name,
    "filepath": func.filepath,
    "line": call.line_range[0],
    "message": f"Function '{func.name}' is called with wrong type for parameter '{param.name}'"
    })


    ExplanationToo much nesting can make code difficult to understand, and this is especially
    true in Python, where there are no brackets to help out with the delineation of
    different nesting levels.

    Reading deeply nested code is confusing, since you have to keep track of which
    conditions relate to which levels. We therefore strive to reduce nesting where
    possible, and the situation where two if conditions can be combined using
    and is an easy win.

    Comment on lines +351 to +359
    if not any(method.name == "__init__" for method in cls.methods):
    errors.append({
    "type": "class_error",
    "error_type": "missing_init",
    "name": cls.name,
    "filepath": cls.filepath,
    "line": cls.line_range[0],
    "message": f"Class '{cls.name}' is missing an __init__ method"
    })
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    issue (code-quality): Invert any/all to simplify comparisons (invert-any-all)

    for arg in call.args:
    if hasattr(arg, "name") and arg.name in [f.name for f in functions]:
    # This is a function being passed as a callback
    callback_func = next((f for f in functions if f.name == arg.name), None)
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    issue (code-quality): Use named expression to simplify assignment and conditional (use-named-expression)

    Comment on lines +467 to +475
    comparison = {
    "main_error_count": main_error_count,
    "branch_error_count": branch_error_count,
    "error_diff": branch_error_count - main_error_count,
    "new_errors": new_errors,
    "fixed_errors": fixed_errors,
    "main_summary": main_results["codebase_summary"],
    "branch_summary": branch_results["codebase_summary"]
    }
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    issue (code-quality): Inline variable that is immediately returned (inline-immediately-returned-variable)

    modified_class_errors = analyzer._analyze_classes(modified_classes)

    # Create PR analysis summary
    pr_analysis = {
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    issue (code-quality): Inline variable that is immediately returned (inline-immediately-returned-variable)

    return pr_analysis


    def generate_html_report(results: Dict[str, Any], output_file: str) -> None:
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    issue (code-quality): We've found these issues:


    Explanation
    The quality score for this function is below the quality threshold of 25%.
    This score is a combination of the method length, cognitive complexity and working memory.

    How can you solve this?

    It might be worth refactoring this function to make it shorter and more readable.

    • Reduce the function length by extracting pieces of functionality out into
      their own functions. This is the most important thing you can do - ideally a
      function should be less than 10 lines.
    • Reduce nesting, perhaps by introducing guard clauses to return early.
    • Ensure that variables are tightly scoped, so that code using related concepts
      sits together within the function rather than being scattered.

    @codegen-sh
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    Author

    codegen-sh bot commented May 3, 2025

    Korbit Code Review: Code Integrity Analyzer

    I've performed a comprehensive review of this PR which adds a code integrity analyzer to the codebase. Here's my assessment:

    Overall Assessment

    This PR introduces a well-structured code integrity analyzer that provides valuable functionality for detecting code quality issues. The implementation is thorough and aligns well with the requirements specified in the PR description.

    Strengths

    1. Comprehensive Analysis: The analyzer covers a wide range of code quality issues, from basic checks (missing docstrings) to more complex ones (incorrect callback signatures).

    2. Well-Structured Code: The code is organized logically with clear separation between the core analyzer and the command-line interface.

    3. Good Documentation: Functions and classes have clear docstrings explaining their purpose and parameters.

    4. Flexible Output Options: Support for both JSON output and HTML reports provides good flexibility for different use cases.

    5. Branch Comparison: The ability to compare branches and analyze PRs is a valuable feature for tracking code quality over time.

    Areas for Improvement

    1. Configurability: The analyzer uses hardcoded thresholds (e.g., max 7 parameters, max 5 return statements). Consider making these configurable through command-line arguments or a configuration file.

    2. Error Handling: The error handling in the script could be more robust, particularly when loading codebases or generating reports.

    3. Test Coverage: There don't appear to be any tests for the analyzer itself. Adding unit tests would help ensure reliability.

    4. Performance Considerations: For large codebases, the analyzer might be slow. Consider adding options for incremental analysis or limiting the scope.

    5. False Positive Handling: There's no mechanism to suppress warnings or handle false positives (e.g., through inline comments or a configuration file).

    Specific Code Feedback

    1. Simplified Parameter Usage Analysis: The _analyze_parameter_usage method uses a simplified approach that might miss many real-world cases. Consider adding a comment acknowledging this limitation.

    2. Callback Analysis Limitations: Similarly, the callback analysis is quite simplified and might not catch all issues. This should be documented.

    3. HTML Report Generation: The HTML report generation is embedded directly in the script. Consider moving this to a separate module for better separation of concerns.

    4. PR Analysis by Number: The script has a TODO for implementing PR analysis by number. Consider either implementing this feature or removing the option to avoid confusion.

    Conclusion

    This PR adds a valuable tool to the codebase that will help maintain code quality. With some minor improvements to configurability and error handling, it will be even more useful. I recommend merging this PR after addressing the areas for improvement mentioned above.

    Great work on implementing this comprehensive analyzer!

    # Analyze parameter usage
    parameter_errors = self._analyze_parameter_usage(functions)

    # Analyze callback points
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    The thresholds for "too many parameters" (7), "too many return statements" (5), "too many methods" (20), and "too many attributes" (15) are hardcoded. Consider making these configurable through command-line arguments or a configuration file to allow users to adjust them based on their project's specific needs and coding standards.

    "line": func.line_range[0],
    "message": f"Function '{func.name}' has too many return statements ({len(func.return_statements)})"
    })

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    This parameter usage analysis is quite simplified and might miss many real-world cases. For example, it doesn't handle keyword arguments, default values, or *args/**kwargs. Consider adding a comment acknowledging these limitations or enhancing the implementation to handle more complex cases.


    # Check for too many methods
    if len(cls.methods) > 20: # Arbitrary threshold
    errors.append({
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    The callback analysis is also quite simplified and might not catch all issues in real-world code. It only checks if a callback function has parameters, but doesn't verify if the parameters match what the caller expects. Consider documenting this limitation or enhancing the implementation to perform more thorough checks.

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    Review by Korbit AI

    Korbit automatically attempts to detect when you fix issues in new commits.
    Category Issue Status
    Functionality Insufficient class modification detection ▹ view
    Readability Runtime Path Modification for Imports ▹ view
    Performance Inefficient Parameter List Creation in Loop ▹ view ✅ Fix detected
    Functionality Unimplemented PR number functionality ▹ view
    Error Handling Abrupt program termination ▹ view
    Security Unescaped HTML Output ▹ view
    Files scanned
    File Path Reviewed
    codegen-on-oss/scripts/analyze_code_integrity.py
    codegen-on-oss/codegen_on_oss/analysis/code_integrity_analyzer.py

    Explore our documentation to understand the languages and file types we support and the files we ignore.

    Check out our docs on how you can make Korbit work best for you and your team.

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    for pr_class in pr_classes:
    if pr_class.name in main_class_names:
    main_class = next((c for c in main_classes if c.name == pr_class.name), None)
    if main_class and (pr_class.methods != main_class.methods or pr_class.attributes != main_class.attributes):
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    Insufficient class modification detection category Functionality

    Tell me more
    What is the issue?

    Direct comparison of methods and attributes lists may not correctly identify modified classes

    Why this matters

    List comparison will fail to detect changes in method implementations if only the method body changed but the method name remained the same

    Suggested change ∙ Feature Preview

    Implement deep comparison of methods and attributes:

    def has_class_changed(pr_class, main_class):
        if pr_class.methods.keys() != main_class.methods.keys():
            return True
        if pr_class.attributes.keys() != main_class.attributes.keys():
            return True
        for method_name, pr_method in pr_class.methods.items():
            if pr_method.body != main_class.methods[method_name].body:
                return True
        return False
    
    # In the code:
    if main_class and has_class_changed(pr_class, main_class):
    Provide feedback to improve future suggestions

    Nice Catch Incorrect Not in Scope Not in coding standard Other

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    Comment on lines +253 to +256
    used_params = set()
    for node in func.body:
    if hasattr(node, "name") and node.name in [p.name for p in func.parameters]:
    used_params.add(node.name)

    This comment was marked as resolved.

    Comment on lines 534 to 540
    # Load PR branch codebase
    if args.feature_branch:
    pr_codebase = load_codebase(args.repo, branch=args.feature_branch)
    elif args.pr_number:
    # TODO: Implement loading PR codebase by PR number
    logger.error("Loading PR by number is not implemented yet")
    sys.exit(1)
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    Abrupt program termination category Error Handling

    Tell me more
    What is the issue?

    The error path abruptly terminates the program with sys.exit(1) without proper error handling or cleanup.

    Why this matters

    Abrupt termination can leave resources in an inconsistent state and makes it difficult for calling code to handle the error gracefully.

    Suggested change ∙ Feature Preview
    # Load PR branch codebase
    if args.feature_branch:
        pr_codebase = load_codebase(args.repo, branch=args.feature_branch)
    elif args.pr_number:
        # TODO: Implement loading PR codebase by PR number
        logger.error("Loading PR by number is not implemented yet")
        raise NotImplementedError("Loading PR by number is not implemented yet")
    Provide feedback to improve future suggestions

    Nice Catch Incorrect Not in Scope Not in coding standard Other

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    Comment on lines 345 to 352
    html += f"""
    <div class="error">
    <div class="error-type">{error['error_type']}</div>
    <div class="file-path">{error['filepath']}</div>
    <div class="line-number">Line: {error['line']}</div>
    <div class="message">{error['message']}</div>
    </div>
    """
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    Unescaped HTML Output category Security

    Tell me more
    What is the issue?

    The code directly embeds untrusted data into HTML output without proper escaping, creating potential XSS vulnerabilities.

    Why this matters

    Malicious input containing HTML/JavaScript could be executed in users' browsers when viewing the report.

    Suggested change ∙ Feature Preview

    Use HTML escaping for untrusted data:

    from html import escape
    
    html += f"""
        <div class="error">
            <div class="error-type">{escape(error['error_type'])}</div>
            <div class="file-path">{escape(error['filepath'])}</div>
            <div class="line-number">Line: {escape(str(error['line']))}</div>
            <div class="message">{escape(error['message'])}</div>
        </div>
        """
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    Nice Catch Incorrect Not in Scope Not in coding standard Other

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    Comment on lines 537 to 540
    elif args.pr_number:
    # TODO: Implement loading PR codebase by PR number
    logger.error("Loading PR by number is not implemented yet")
    sys.exit(1)
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    Unimplemented PR number functionality category Functionality

    Tell me more
    What is the issue?

    The code accepts a PR number as input but fails to implement the functionality, causing an immediate exit.

    Why this matters

    Users will experience unexpected termination when using the --pr-number option, making this advertised feature unusable.

    Suggested change ∙ Feature Preview

    Either implement the PR number functionality or remove the --pr-number option from the argument parser until it's implemented:

    parser.add_argument('--mode', choices=['analyze', 'compare', 'pr'], default='analyze', help='Analysis mode')
    parser.add_argument('--main-branch', default='main', help='Main branch name (for compare and pr modes)')
    parser.add_argument('--feature-branch', help='Feature branch name (for compare and pr modes)')
    # Remove --pr-number argument until implemented
    parser.add_argument('--verbose', '-v', action='store_true', help='Enable verbose logging')
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    Comment on lines +30 to +41
    # Add the parent directory to the path so we can import the module
    sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
    from codegen_on_oss.analysis.code_integrity_analyzer import (
    CodeIntegrityAnalyzer,
    compare_branches,
    analyze_pr,
    get_codebase_summary,
    get_file_summary,
    get_class_summary,
    get_function_summary,
    get_symbol_summary
    )
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    Runtime Path Modification for Imports category Readability

    Tell me more
    What is the issue?

    The script modifies sys.path to import a module, which makes the import dependencies unclear and can lead to confusion about the project structure.

    Why this matters

    Modifying the Python path at runtime makes it harder to understand where imports are coming from and can cause import conflicts. It also suggests the project structure might need reorganization.

    Suggested change ∙ Feature Preview

    Properly structure the project as a package and use relative imports or install the package in development mode:

    from ..codegen_on_oss.analysis.code_integrity_analyzer import (
        CodeIntegrityAnalyzer,
        compare_branches,
        analyze_pr,
        get_codebase_summary,
        get_file_summary,
        get_class_summary,
        get_function_summary,
        get_symbol_summary
    )
    Provide feedback to improve future suggestions

    Nice Catch Incorrect Not in Scope Not in coding standard Other

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    margin: 0;
    padding: 20px;
    color: #333;
    }
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    The HTML report generation is embedded directly in the script. Consider moving this to a separate module or function in the code_integrity_analyzer.py file for better separation of concerns. This would make the code more maintainable and allow for easier customization of the report format.


    # Compare codebases
    results = compare_codebases(main_codebase, feature_codebase, args.output)
    elif args.mode == 'pr':
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    There's a TODO here for implementing PR analysis by number. Consider either implementing this feature or removing the option to avoid confusion. If it's planned for a future update, it might be better to document this limitation in the help text or README.

    branch: Optional branch to load
    commit: Optional commit to load

    Returns:
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    The error handling here could be more robust. Consider adding try/except blocks to handle potential errors when loading codebases, especially for remote repositories or branches that don't exist. This would provide better user feedback and prevent the script from crashing unexpectedly.


    return f"""==== [ `{symbol.name}` ({type(symbol).__name__}) Usage Summary ] ====
    - {len(usages)} usages
    \t- {len([x for x in usages if isinstance(x, Symbol) and x.symbol_type == SymbolType.Function])} functions
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    There's no mechanism to suppress warnings or handle false positives. Consider adding support for ignoring specific errors or files, either through inline comments (like # noqa in flake8) or a configuration file. This would make the tool more practical for real-world use where some exceptions to the rules are necessary.

    @codegen-sh
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    codegen-sh bot commented May 3, 2025

    Korbit Code Review: Code Integrity Analyzer

    I've completed a comprehensive review of PR #39 which adds a code integrity analyzer to the codebase. Here's my assessment:

    Overall Assessment

    This PR introduces a well-structured code integrity analyzer that provides valuable functionality for detecting code quality issues. The implementation is thorough and aligns well with the requirements specified in the PR description.

    Key Strengths

    • Comprehensive analysis covering a wide range of code quality issues
    • Well-structured code with clear separation of concerns
    • Good documentation with clear docstrings
    • Flexible output options (JSON and HTML reports)
    • Valuable branch comparison functionality

    Areas for Improvement

    • Configurability: Consider making thresholds configurable
    • Error handling: Add more robust error handling
    • Test coverage: Add unit tests for the analyzer
    • Performance considerations for large codebases
    • Add mechanism to handle false positives

    I've left detailed comments on the PR with specific suggestions for improvements. Overall, this is a valuable addition to the codebase that will help maintain code quality.

    Great work on implementing this comprehensive analyzer!

    💻 View my work • React 👍 or 👎

    @codegen-sh
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    codegen-sh bot commented May 3, 2025

    ✅ Fixed failing mypy check in this commit. The issue was missing type annotations for the errors and warnings lists in the CodeIntegrityAnalyzer class.

    @codegen-sh
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    codegen-sh bot commented May 3, 2025

    Code Integrity Analyzer Improvements

    I've enhanced the code integrity analyzer with several significant improvements:

    1. Advanced Analysis Capabilities

    • Code Complexity Analysis: Added detection of high cyclomatic complexity and mutable default arguments
    • Import Analysis: Now identifies unused imports across the codebase
    • Type Hint Checking: Verifies proper use of type hints in function parameters and return values
    • Code Duplication Detection: Identifies similar code blocks that might need refactoring

    2. Configurable Analysis

    • Added a comprehensive configuration system with sensible defaults
    • Customizable thresholds for all metrics (function parameters, returns, class methods, etc.)
    • Configurable severity levels (warning vs. error) for different issue types
    • Support for ignoring specific patterns (e.g., __pycache__, .git)

    3. Enhanced Reporting

    • Improved HTML report with interactive filtering and sorting
    • Visual statistics dashboard showing error distribution
    • Severity-based color coding for better issue prioritization
    • Search functionality to quickly find specific issues

    4. Better CLI Experience

    • Added support for YAML configuration files
    • More detailed logging with error breakdowns
    • Progress indicators for long-running analyses

    These improvements make the analyzer much more powerful while keeping it easy to use. The configuration system allows teams to adapt it to their specific coding standards.

    Would you like me to explain any specific part of the implementation in more detail?

    💻 View my work • React 👍 or 👎

    @Zeeeepa Zeeeepa marked this pull request as ready for review May 3, 2025 21:06
    @korbit-ai
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    korbit-ai bot commented May 3, 2025

    By default, I don't review pull requests opened by bots. If you would like me to review this pull request anyway, you can request a review via the /korbit-review command in a comment.

    @Zeeeepa Zeeeepa merged commit 7f670e1 into develop May 3, 2025
    11 of 17 checks passed
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