[P1] Performance Pattern Analysis - Detect Bottlenecks #222

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1. mrveiss

   added

   priority: high

   performance

   optimization

   on Nov 27, 2025
2. mrveiss commented on Nov 29, 2025

   

   mrveiss

   on Nov 29, 2025

   OwnerAuthor

   More actions

   Starting implementation of Performance Pattern Analysis.

   Implementation Plan

   1. Backend API (analytics_performance.py)

      • N+1 query pattern detection
      • Loop complexity analysis
      • Async/sync mismatch detection
      • Cache operation analysis
      • Memory leak pattern detection

   2. Vue Component (PerformanceAnalysisDashboard.vue)

      • Performance issue heatmap
      • Issue categorization
      • Impact severity indicators
      • Optimization suggestions
3. mrveiss commented on Nov 29, 2025

   

   mrveiss

   on Nov 29, 2025

   OwnerAuthor

   More actions

   Implementation Complete

   Backend API (analytics_performance.py)

   • 17 Performance Patterns across 6 categories
   • Pattern-based detection using regex + AST analysis
   • Categories: query, loop, async, cache, memory, I/O
   • Impact levels: critical, high, medium, low
   • Performance health score (0-100)
   • Hotspot detection (files with most issues)

   Vue Component (PerformanceAnalysisDashboard.vue)

   • Performance health score ring visualization
   • Summary stats (critical, high, medium, low counts)
   • Category-filtered issue list
   • Detailed issue view with code snippets
   • Hotspot panel showing problem files
   • Category distribution bar chart
   • Pattern configuration modal

   API Endpoints

   • GET /api/performance/analyze - Analyze code path
   • POST /api/performance/analyze-content - Analyze content
   • GET /api/performance/patterns - List patterns
   • POST /api/performance/patterns/{id}/toggle - Toggle pattern
   • GET /api/performance/history - Analysis history
   • GET /api/performance/summary - Statistics
   • GET /api/performance/categories - Category breakdown
   • GET /api/performance/hotspots - Problem files

   Built-in Patterns

   ID	Name	Category	Impact
   PERF-Q001	N+1 Query Pattern	Query	Critical
   PERF-Q002	Unbounded Query	Query	High
   PERF-Q003	SELECT * Usage	Query	Medium
   PERF-L001	Nested Loop O(n²)	Loop	High
   PERF-L002	List Concatenation in Loop	Loop	Medium
   PERF-L003	String Concatenation in Loop	Loop	Medium
   PERF-A001	Sync Call in Async Function	Async	Critical
   PERF-A002	Sequential Awaits	Async	High
   PERF-A003	Missing Await	Async	High
   PERF-C001	Repeated Redis GET in Loop	Cache	High
   PERF-C002	Missing Cache TTL	Cache	Medium
   PERF-C003	Cache Key Without Prefix	Cache	Low
   PERF-M001	Global Mutable Default	Memory	High
   PERF-M002	Large List Comprehension	Memory	Medium
   PERF-M003	Reading Entire File	Memory	Medium
   PERF-I001	Unbuffered File Write	I/O	Medium
   PERF-I002	Multiple File Opens	I/O	Low

   Router registered in routers.py ✅
4. mrveiss commented on Nov 29, 2025

   

   mrveiss

   on Nov 29, 2025

   OwnerAuthor

   More actions

   Starting implementation of Performance Pattern Analyzer.

   Planned Detection Capabilities:

   • N+1 query patterns (database queries in loops)
   • Nested loop complexity (O(n²) and higher)
   • Sync operations in async context (blocking I/O)
   • Memory leak patterns (unbounded growth)
   • Cache misuse (repeated lookups, missing invalidation)
   • Redis operation efficiency (pipeline opportunities)
   • LLM call optimization opportunities
5. mrveiss

   added a commit that references this issue on Nov 29, 2025

   feat(code-intelligence): Add Performance Pattern Analyzer (#222)

   ...

   3446f86
6. mrveiss commented on Nov 29, 2025

   

   mrveiss

   on Nov 29, 2025

   OwnerAuthor

   More actions

   Implemented in commit 3446f86

   Summary

   Performance Pattern Analyzer for detecting performance anti-patterns in Python code.

   Features Implemented

   • N+1 query detection: Database queries inside loops (HIGH severity)
   • Nested loop complexity: O(n²), O(n³) and higher complexity patterns
   • Sync in async detection: time.sleep() in async functions (CRITICAL)
   • Blocking I/O in async: File operations, requests in async context
   • Sequential awaits: Independent awaits that could run in parallel
   • String concatenation in loops: += with strings in loop bodies
   • List for lookup: Using list literals for membership checks
   • HTTP requests in loops: Unbatched API calls
   • Repeated computations: Same expensive call multiple times

   Key Files

   • src/code_intelligence/performance_analyzer.py - 935 lines core engine
   • tests/unit/test_performance_analyzer.py - 31 unit tests (all passing)
   • backend/api/code_intelligence.py - 5 REST API endpoints

   API Endpoints

   • POST /api/code-intelligence/performance/analyze - Analyze directory
   • POST /api/code-intelligence/performance/scan-file - Quick single file scan
   • GET /api/code-intelligence/performance/issue-types - List all issue types
   • POST /api/code-intelligence/performance/score - Get performance score
   • POST /api/code-intelligence/performance/report - Generate report

   Technical Details

   • AST-based analysis with regex fallback
   • Big-O complexity estimation
   • Performance scoring (0-100 scale)
   • JSON and Markdown report formats
   • Part of EPIC [EPIC] Implement Advanced Code Intelligence Methods - 30 Integrations #217 - Advanced Code Intelligence Methods
7. mrveiss

   closed this as completedon Nov 29, 2025
8. mrveiss

   added 2 commits that reference this issue on Nov 29, 2025

   feat(analytics): Add Performance Pattern Analyzer API and Dashboard (#…

   ...

   b757527

   feat(routers): Register all new analytics API routers

   ...

   b6f6ad0
9. mrveiss

   added 3 commits that reference this issue on Dec 31, 2025

   feat(code-intelligence): Add Performance Pattern Analyzer (#222)

   ...

   2740440

   feat(analytics): Add Performance Pattern Analyzer API and Dashboard (#…

   ...

   8328a49

   feat(routers): Register all new analytics API routers

   ...

   fdb5feb