Claude/fix ci and readme 011 c up bz st br8i c59e vzkbqk #52
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Implements semantic codebase mapping using LJPW framework: Features: - Analyzes entire codebase and maps files to LJPW space - Groups files by dominant semantic dimension (natural clusters) - Detects outliers (files with no clear purpose) - Calculates average disharmony per file - Generates comprehensive semantic map report Output shows: - Semantic clusters (Love, Justice, Power, Wisdom) - Average coordinates per cluster - Top files by function count - Overall codebase health metrics Tested on harmonizer itself: - 9 files analyzed - 2 clusters: Justice (main/parser) + Wisdom (engine/analysis) - Overall disharmony: 0.58 (MODERATE) - Identified high-disharmony files for refactoring This directly addresses: 'Legacy code's real complexity still fights back' By revealing the true semantic structure of any codebase. Usage: python -m harmonizer.legacy_mapper <path> Next: Add git history tracking, architectural smell detection
Major Upgrades: - Architectural smell detection (4 types: God File, Semantic Confusion, High Disharmony, Mixed Concerns) - Refactoring opportunity identification with impact scores - Complexity heatmap generation (ASCII visual) - Detailed suggestions for each refactoring target New Features: - Detects god files (>30 functions) - Identifies files with no clear purpose (semantic confusion) - Flags high disharmony files (>0.7 threshold) - Finds mixed concern files (3+ active dimensions) - Calculates complexity reduction estimates - Provides specific refactoring actions - Generates visual complexity heatmap by directory - Sortable by impact score Enhanced Output: - Architectural smells grouped by severity (CRITICAL/HIGH/MEDIUM/LOW) - Top 5 refactoring opportunities with specific actions - Impact scores and complexity reduction percentages - Visual heatmap showing problem hotspots CLI Options: - --no-heatmap: Skip complexity visualization - --no-smells: Skip architectural smell detection - --quiet: Minimal output for automation Tested on Harmonizer itself: - 5 architectural smells detected (4 HIGH, 1 MEDIUM) - Top refactorings: ast_semantic_parser_v2.py (53% impact) - Specific actions provided for each opportunity This is now a complete legacy code understanding system.
BruinGrowly
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