From 385d8746ab1361d6dec5883115884923ff417535 Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Wed, 11 Feb 2026 11:06:08 +0000 Subject: [PATCH] Optimize a3-python-v2 workflow for better issue formatting Co-authored-by: NikolajBjorner <3085284+NikolajBjorner@users.noreply.github.com> --- .github/workflows/a3-python-v2.md | 244 +++++++++++++++++++----------- 1 file changed, 153 insertions(+), 91 deletions(-) diff --git a/.github/workflows/a3-python-v2.md b/.github/workflows/a3-python-v2.md index 380addfea..c39ad4655 100644 --- a/.github/workflows/a3-python-v2.md +++ b/.github/workflows/a3-python-v2.md @@ -134,6 +134,8 @@ For each issue reported in the output, determine: - Test-related code patterns - Generated code or third-party code - Overly strict warnings without merit + - **Assertion violations at the beginning of functions** (these are pre-conditions and intentional design) + - Parameter validation checks in function entry points ### 3.3 Extract Source Code Context @@ -194,7 +196,7 @@ done ### 3.5 Enhanced Analysis Workflow -Create an enhanced analysis workflow that automatically extracts source code context: +Create an enhanced analysis workflow that automatically extracts source code context. **IMPORTANT**: Limit detailed examples to top 5 high-severity findings only. ```bash # Parse a3-python output and extract file/line information @@ -202,7 +204,8 @@ parse_findings() { local output_file="$1" # Create arrays to store findings - declare -a true_positives=() + declare -a high_severity=() + declare -a medium_severity=() declare -a false_positives=() # Parse the output file and extract findings with file/line info @@ -216,29 +219,42 @@ parse_findings() { echo "Found potential issue: $file:$line_num - $description" - # Add logic here to classify as true positive or false positive - # For now, store all as potential true positives for manual review - true_positives+=("File: $file, Line: $line_num, Description: $description") + # Classify by severity and type + # High severity: NULL_PTR, DIV_ZERO + # Medium severity: BOUNDS, ASSERT_FAIL (except pre-condition assertions) + # False positives: Assertion violations at function start (pre-conditions) + + if [[ "$description" =~ ASSERT_FAIL ]] && [[ $line_num -lt 10 ]]; then + # Likely a pre-condition assertion at start of function + false_positives+=("File: $file, Line: $line_num, Description: $description") + elif [[ "$description" =~ (NULL_PTR|DIV_ZERO) ]]; then + high_severity+=("File: $file, Line: $line_num, Description: $description") + else + medium_severity+=("File: $file, Line: $line_num, Description: $description") + fi fi done < "$output_file" - # Generate contexts for all true positives + # Generate enhanced report with TOP 5 HIGH-SEVERITY findings only in detail echo "# Enhanced Analysis Report" > enhanced_report.md echo "" >> enhanced_report.md - echo "## True Positives with Source Context" >> enhanced_report.md + echo "## Sample High-Severity Findings (Top 5)" >> enhanced_report.md echo "" >> enhanced_report.md local counter=1 - for finding in "${true_positives[@]}"; do + local max_samples=5 + for finding in "${high_severity[@]}"; do + if [ $counter -gt $max_samples ]; then + break + fi + file=$(echo "$finding" | grep -o 'File: [^,]*' | cut -d' ' -f2) line_num=$(echo "$finding" | grep -o 'Line: [^,]*' | cut -d' ' -f2) desc=$(echo "$finding" | grep -o 'Description: .*' | cut -d' ' -f2-) - echo "### Issue $counter: $desc" >> enhanced_report.md - echo "- **File**: \`$file\`" >> enhanced_report.md - echo "- **Line**: $line_num" >> enhanced_report.md + echo "### $counter. $desc" >> enhanced_report.md + echo "**Location**: \`$file:$line_num\`" >> enhanced_report.md echo "" >> enhanced_report.md - echo "**Source Code Context:**" >> enhanced_report.md if [[ -f "$file" ]]; then extract_code_context "$file" "$line_num" 5 >> enhanced_report.md @@ -252,6 +268,12 @@ parse_findings() { ((counter++)) done + # Add summary statistics + echo "## Summary Statistics" >> enhanced_report.md + echo "- High Severity: ${#high_severity[@]}" >> enhanced_report.md + echo "- Medium Severity: ${#medium_severity[@]}" >> enhanced_report.md + echo "- False Positives: ${#false_positives[@]}" >> enhanced_report.md + # Display the enhanced report echo "=== Enhanced Analysis Report ===" cat enhanced_report.md @@ -261,6 +283,8 @@ parse_findings() { parse_findings "a3-python-output.txt" ``` +**Note**: The complete list of all findings should be added to a collapsible `
` section in the GitHub issue, not shown in full detail. + ### 3.4 Categorize and Count Create a structured analysis with source code context: @@ -268,50 +292,38 @@ Create a structured analysis with source code context: ```markdown ## Analysis Results -### True Positives (Likely Issues): -1. [Issue 1 Description] - File: path/to/file.py, Line: X - **Source Code Context:** - ```python - [Line numbers with context - error line marked with ❌] - ``` +### 3.4 Categorize and Count -2. [Issue 2 Description] - File: path/to/file.py, Line: Y - **Source Code Context:** - ```python - [Line numbers with context - error line marked with ❌] - ``` -.... - -### False Positives: -1. [FP 1 Description] - Reason for dismissal -2. [FP 2 Description] - Reason for dismissal -.... - -### Summary: -- Total findings: X -- True positives: Y -- False positives: Z -``` - -Create a structured analysis: +Create a structured analysis with source code context: ```markdown ## Analysis Results -### True Positives (Likely Issues): +### High-Severity Issues (for detailed examples): 1. [Issue 1 Description] - File: path/to/file.py, Line: X + **Source Code Context:** + ```python + [Line numbers with context - error line marked with ❌] + ``` + 2. [Issue 2 Description] - File: path/to/file.py, Line: Y -... + **Source Code Context:** + ```python + [Line numbers with context - error line marked with ❌] + ``` + +(Limit to top 5 high-severity for detailed display) ### False Positives: -1. [FP 1 Description] - Reason for dismissal +1. [FP 1 Description] - Reason: Pre-condition assertion at function start 2. [FP 2 Description] - Reason for dismissal ... ### Summary: - Total findings: X -- True positives: Y -- False positives: Z +- High severity (NULL_PTR, DIV_ZERO): Y +- Medium severity (BOUNDS, ASSERT_FAIL): Z +- False positives (including pre-conditions): W ``` ## Phase 4: Create GitHub Issue (Conditional) @@ -338,24 +350,31 @@ If creating an issue, use this structure: ```markdown ## A3 Python Code Analysis - [Date] -This issue reports bugs and code quality issues identified by the a3-python analysis tool. +This issue reports **[number]** DSE-confirmed bugs identified by a3-python analysis tool across the Z3 Python API. -### Summary +### Executive Summary -- **Analysis Date**: [Date] -- **Total Findings**: X -- **True Positives (Likely Issues)**: Y -- **False Positives**: Z +- **Total Findings**: X confirmed bugs +- **High Severity**: Y (NULL_PTR: N1, DIV_ZERO: N2) +- **Medium Severity**: Z (BOUNDS: N3, ASSERT_FAIL: N4) +- **Analysis Method**: Deep Symbolic Execution (DSE) verification -### True Positives (Issues to Address) +### Files Most Affected -#### Issue 1: [Short Description] -- **File**: `path/to/file.py` -- **Line**: X -- **Severity**: [High/Medium/Low] -- **Description**: [Detailed description of the issue] +| File | Issues | +|------|--------| +| `path/to/file1.py` | X | +| `path/to/file2.py` | Y | +| `path/to/file3.py` | Z | + +(Show only top 3-5 files) + +### Sample High-Severity Findings + +#### 1. [BUG_TYPE] in `function_name` + +**Location**: `path/to/file.py:line_number` -**Source Code Context:** ```python 10: def some_function(): 11: value = None @@ -364,60 +383,86 @@ This issue reports bugs and code quality issues identified by the a3-python anal 14: # Rest of function... ``` -- **Recommendation**: [How to fix it] +#### 2. [BUG_TYPE] in `function_name` -#### Issue 2: [Short Description] -- **File**: `path/to/file.py` -- **Line**: Y -- **Severity**: [High/Medium/Low] -- **Description**: [Detailed description of the issue] +**Location**: `path/to/file.py:line_number` -**Source Code Context:** ```python 25: if condition: 26: result = process_data() 27: ❌ return result # Error: 'result' may be undefined 28: # Missing else clause - 29: ``` -- **Recommendation**: [How to fix it] +(Show only top 5 high-severity examples with code context) -[Continue for all true positives] +### Bug Type Analysis -### Analysis Details +| Type | Count | Description | +|------|-------|-------------| +| NULL_PTR | X | Potential None/null dereferences | +| BOUNDS | Y | Array/string index out of bounds | +| ASSERT_FAIL | Z | Assertion violations | +| DIV_ZERO | W | Division by zero errors | + +### Methodology + +This analysis used **a3-python** with: +- ✅ **Deep Symbolic Execution (DSE)**: Confirms bug reachability via concrete paths +- ✅ **Barrier Theory**: Attempts to prove safety before flagging +- ✅ **Multi-strategy verification**: 7+ verification techniques + +All [number] issues are **DSE-confirmed**, meaning the tool verified these errors are reachable through real execution paths. + +### Recommended Actions + +**Immediate Priority** (High Severity - X issues): +1. Add null/None checks before dereferences in core API functions +2. Validate division denominators to prevent DIV_ZERO +3. Focus on `most_affected_file.py` (N issues) + +**Medium Priority** (Y issues): +1. Add bounds checking for array/string indexing +2. Review and strengthen assertion conditions +3. Add comprehensive error handling + +**Long-term**: +1. Adopt comprehensive input validation across Python API +2. Use Python type hints consistently (e.g., `Optional[T]`) +3. Consider defensive programming patterns for C API wrappers + +### Complete Analysis Data
-False Positives (Click to expand) +All [number] findings grouped by file (click to expand) -These findings were classified as false positives because: +**path/to/file1.py** (X issues) +- BUG_TYPE: N issues + - Line Y: `function_name` + - Line Z: `function_name` + ... -1. **[FP 1]**: [Reason for dismissal] -2. **[FP 2]**: [Reason for dismissal] -... +**path/to/file2.py** (X issues) +- BUG_TYPE: N issues + - Line Y: `function_name` + ... + +(List ALL findings in collapsed section)
-### Raw Output -
-Complete a3-python output (Click to expand) +Raw a3-python output excerpt (click to expand) ``` -[PASTE COMPLETE CONTENTS OF a3-python-output.txt HERE] +[PASTE FIRST 50-100 LINES OF a3-python-output.txt HERE FOR REFERENCE] ```
-### Recommendations - -1. Prioritize fixing high-severity issues first -2. Review medium-severity issues for improvement opportunities -3. Consider low-severity issues as code quality enhancements - --- -*Automated by A3 Python Analysis Agent - Weekly code quality analysis* +*Note: All findings have been DSE-confirmed by a3-python's deep symbolic execution engine. For questions about specific findings, run `a3 scan` locally for detailed analysis.* ``` ### 4.3 Use Safe Outputs @@ -435,6 +480,14 @@ Create the issue using the safe-outputs configuration: - **Be accurate**: Distinguish real issues from false positives - **Be specific**: Provide file names, line numbers, and descriptions - **Be actionable**: Include recommendations for fixes +- **Be concise**: Focus on the most critical findings in the main issue body + +### Issue Formatting Best Practices +- **Limit sample findings**: Show only top 5 high-severity examples with code context +- **Use collapsible sections**: Put complete analysis data in `
` tags +- **Prioritize readability**: Organize by severity and actionability, not just by file +- **Avoid duplication**: Don't repeat the same information in multiple formats +- **Keep it focused**: The issue should be scannable in under 2 minutes ### Classification Criteria @@ -450,6 +503,8 @@ Create the issue using the safe-outputs configuration: - Test code patterns that look unusual but are valid - Generated or vendored code - Overly pedantic warnings +- **Assertion violations at the beginning of functions** (these are pre-conditions) +- Parameter validation checks (assert statements checking input parameters) ### Threshold for Issue Creation - **2+ true positives**: Create an issue with all findings @@ -487,12 +542,16 @@ Your output MUST either: ``` 2. **If 2+ true positives found**: Create an issue with: - - Clear summary of findings - - Detailed breakdown of each true positive with source code context - - Visual representation of error lines with surrounding code - - Severity classifications - - Actionable recommendations - - Complete raw output in collapsible section + - Clear executive summary with statistics + - Files most affected table (top 3-5 only) + - **ONLY top 5 high-severity findings** with detailed source code context + - Bug type analysis summary table + - Methodology explanation + - Recommended actions (prioritized) + - **Complete findings list** in collapsed `
` section + - **Raw output excerpt** (first 50-100 lines) in collapsed `
` section + +**Critical**: Do NOT list all findings in the main issue body. Keep sample findings to 5 maximum and put comprehensive data in collapsible sections. ## Enhanced Workflow Summary @@ -500,7 +559,10 @@ The enhanced workflow now includes: 1. **Automated Source Code Context Extraction**: The `extract_code_context` function automatically extracts 5 lines before and after each error location 2. **Visual Error Highlighting**: Error lines are marked with ❌ for easy identification -3. **Structured Reporting**: Each finding includes the actual source code with line numbers for better understanding -4. **Enhanced GitHub Issues**: Issues now contain source code snippets making them much more readable and actionable +3. **Severity-Based Classification**: Automatically categorizes findings as high/medium severity +4. **False Positive Detection**: Identifies pre-condition assertions at function entry points +5. **Concise Reporting**: Limits detailed examples to top 5 high-severity findings +6. **Progressive Disclosure**: Uses collapsible sections for complete data +7. **Enhanced GitHub Issues**: Issues are scannable, actionable, and well-organized -Begin the analysis now. Install a3-python, run analysis on the repository, save output to a3-python-output.txt, extract source code context for findings, and create a GitHub issue if 2 or more likely issues are found. +Begin the analysis now. Install a3-python, run analysis on the repository, save output to a3-python-output.txt, extract source code context for findings, classify by severity, and create a GitHub issue if 2 or more likely issues are found. **Remember to keep the main issue body concise with only top 5 examples and put complete findings in a collapsed section.**