# PMAT Quality Analysis Report - 2025-08-21

## Executive Summary

Comprehensive PMAT analysis of the refactored `src/runtime/repl.rs` after v0.7.22 complexity reduction sprint.

## Complexity Analysis

### Overall Metrics
- **Total Functions**: 85
- **Median Cyclomatic Complexity**: 6.0 ✅
- **Median Cognitive Complexity**: 5.0 ✅
- **Max Cyclomatic**: 69 ❌
- **Max Cognitive**: 113 ❌
- **Estimated Refactoring Time**: 308 hours

### Top Complexity Hotspots

1. **`Value::format_dataframe`** - Cyclomatic: 69, Cognitive: 113
2. **`Value::fmt`** - Cyclomatic: 66, Cognitive: 104
3. **`Repl::evaluate_expr`** - Cyclomatic: 55, Cognitive: 60
4. **`Repl::evaluate_binary`** - Cyclomatic: 46, Cognitive: 45
5. **`Repl::save_session`** - Cyclomatic: 45, Cognitive: 48

### Discrepancy Note
PMAT reports `evaluate_expr` at 55 cyclomatic complexity, while our manual count showed 50. This is likely due to different counting methodologies (PMAT may count nested conditions differently).

## Big O Complexity Analysis

### Performance Issues Found
Multiple functions with O(n²) time complexity:

1. **`format_dataframe`** - O(n²) time, O(n) space
   - Issue: Nested loops for DataFrame formatting
   - Impact: Performance degrades quadratically with row/column count

2. **`get_completions`** - O(n²) time, O(n) space
   - Issue: Nested matching for completion suggestions
   - Impact: Slow autocompletion for large codebases

3. **`highlight_ruchy_syntax`** - O(n²) time, O(n) space
   - Issue: Token-by-token syntax highlighting
   - Impact: Slow rendering for large files

## Provability Analysis

### Function Provability Score
- **`evaluate_expr`**: 42.5% provability
  - Low score indicates high complexity and difficulty in formal verification
  - Many runtime-dependent branches and error paths
  - Dynamic typing makes static analysis challenging

### Score Distribution
- High (≥80%): 0 functions
- Medium (50-79%): 0 functions
- Low (<50%): 1 function analyzed

## Dead Code Analysis

### Results
✅ **No dead code detected**
- Files analyzed: 1
- Dead code percentage: 0.00%
- Total dead lines: 0

This confirms our refactoring didn't introduce any unreachable code paths.

## Recommendations

### Immediate Priority (P0)
1. **`Value::format_dataframe`** - Reduce from 69 to <30 complexity
   - Extract column width calculation
   - Separate header/row formatting logic
   - Use builder pattern for output construction

2. **`Value::fmt`** - Reduce from 66 to <30 complexity
   - Extract type-specific formatters
   - Use visitor pattern for recursive structures
   - Implement Display trait for sub-components

### Medium Priority (P1)
1. **Optimize O(n²) algorithms**
   - Use caching for `get_completions`
   - Implement incremental highlighting for `highlight_ruchy_syntax`
   - Stream-based formatting for `format_dataframe`

2. **Improve provability**
   - Add more type annotations
   - Reduce dynamic dispatch
   - Extract pure functions from side-effecting code

### Long-term (P2)
1. **Architectural improvements**
   - Consider state machine for REPL loop
   - Implement command pattern for REPL commands
   - Use async streams for large data processing

## Success Metrics

### Achieved in v0.7.22
- ✅ Reduced `evaluate_expr` from 209 → 55 (73% reduction)
- ✅ Extracted 22 helper methods
- ✅ Zero dead code
- ✅ All tests passing

### Remaining for v0.8.0
- ❌ `Value::fmt` still at 66 (target: <30)
- ❌ `Value::format_dataframe` still at 69 (target: <30)
- ❌ O(n²) algorithms need optimization
- ❌ Provability score needs improvement (target: >70%)

## Conclusion

The v0.7.22 refactoring successfully reduced the primary target (`evaluate_expr`) complexity by 73%, exceeding our goal. However, PMAT analysis reveals additional optimization opportunities in display formatting and algorithmic complexity that should be addressed in v0.8.0.

The zero dead code result validates our refactoring approach - we successfully extracted functionality without leaving orphaned code paths.