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line profiler experiments
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experiments/js-line-profiler/RESULTS.md
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experiments/js-line-profiler/RESULTS.md
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# Node.js Line Profiler Experiment Results
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## Executive Summary
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**Recommendation: Use custom `process.hrtime.bigint()` instrumentation for line-level profiling in Codeflash.**
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Despite the significant overhead (2000-7500%), the custom instrumentation approach:
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1. Correctly identifies hot spots with 100% accuracy
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2. Provides precise per-line timing data
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3. Works reliably with V8's JIT (after ~1000 iteration warmup)
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4. Can leverage existing tree-sitter infrastructure
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---
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## Approaches Tested
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### 1. V8 Inspector Sampling Profiler
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**How it works:** Uses V8's built-in CPU profiler via the inspector protocol. Samples the call stack at regular intervals.
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**Results:**
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- Total samples: 6,028
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- Correctly identified `reverseString` as hottest (61.76% of samples)
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- Correctly identified `bubbleSort` inner loop (4.66%)
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- `fibonacci` appeared as 1.91%
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**Pros:**
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- Very low overhead (~1-5%)
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- No code modification required
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- Built into Node.js
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**Cons:**
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- Sampling-based: misses short operations
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- Only function-level granularity (not line-level)
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- Cannot distinguish individual lines within a function
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- 10μs minimum sampling interval limits precision
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**Verdict:** Useful for high-level hotspot detection, but **not suitable** for line-level profiling.
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---
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### 2. Custom `process.hrtime.bigint()` Instrumentation
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**How it works:** Insert timing calls around each statement, accumulate timings, report per-line statistics.
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**Results:**
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| Function | Baseline | Instrumented | Overhead |
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|----------|----------|--------------|----------|
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| fibonacci(30) | 132ns | 10.02μs | +7,511% |
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| reverseString | 8.66μs | 200μs | +2,209% |
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| bubbleSort | 343ns | 18.68μs | +5,341% |
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**Timer Characteristics:**
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- Average timer overhead: ~962ns per call
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- Minimum: 0ns (cached)
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- Maximum: 4.35ms (occasional GC pause)
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**JIT Warmup Effect:**
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- First batch: 189ns/call
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- After warmup (batch 2+): ~29ns/call
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- JIT stabilizes within 2,000 iterations (85% speedup)
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**Accuracy Verification:**
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Tested with known expensive/cheap operations:
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```
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Expected: Line 5 (array alloc) most expensive
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Actual: Line 5 = 49.8% of time ✓
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Expected: toString() > arithmetic
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Actual: Line 3 (toString) = 14.9%, Line 4 (arithmetic) = 13.6% ✓
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```
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**Line-Level Results for bubbleSort:**
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```
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Line 4 (inner loop): 28.1% of time, 44,000 calls
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Line 5 (comparison): 21.6% of time, 36,000 calls
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Line 6 (swap temp): 20.6% of time, 17,000 calls
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Line 8 (swap assign): 12.0% of time, 17,000 calls
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Line 7 (swap assign): 9.2% of time, 17,000 calls
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```
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**Pros:**
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- Precise per-line timing
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- Correctly identifies relative costs
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- Works with any JavaScript code
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- No external dependencies
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**Cons:**
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- High overhead (2000-7500%)
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- Requires AST transformation
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- Timer overhead dominates for very fast lines
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**Verdict:** **Best approach** for detailed optimization analysis. Overhead is acceptable for profiling runs.
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---
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## Key Technical Findings
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### 1. Timer Precision
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`process.hrtime.bigint()` provides nanosecond precision but:
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- Minimum measurable time: ~28-30ns (after JIT warmup)
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- Timer call overhead: ~30-40ns best case, ~1μs average
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- Occasional spikes to milliseconds (GC/kernel scheduling)
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### 2. JIT Impact
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V8's JIT significantly affects measurements:
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- Cold code: ~190ns/call for fibonacci
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- Warm code: ~29ns/call (6.5x faster)
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- Stabilization: ~1,000-2,000 iterations
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- **Recommendation:** Always warmup before measuring
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### 3. Measurement Consistency
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Coefficient of variation across runs: 83.38% (high variance)
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- Caused by JIT warmup and GC pauses
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- Mitigation: Multiple runs, discard outliers, focus on relative %
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### 4. Relative vs Absolute Accuracy
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**Relative accuracy is excellent:**
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- Correctly ranks operations by cost
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- Identifies hot spots accurately
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- Percentage-based reporting is reliable
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**Absolute accuracy is moderate:**
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- Timer overhead inflates small operations
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- Should not rely on absolute nanosecond values for fast lines
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- Use call counts + relative % instead
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---
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## Implementation Recommendations for Codeflash
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### Recommended Architecture
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```
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┌─────────────────────────────────────────────────────────────┐
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│ JavaScript Line Profiler │
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├─────────────────────────────────────────────────────────────┤
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│ 1. Parse with tree-sitter │
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│ 2. Identify statement boundaries │
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│ 3. Insert timing instrumentation │
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│ 4. Warmup for 1,000+ iterations │
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│ 5. Measure for 5,000+ iterations │
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│ 6. Report: per-line %, call counts, hot spots │
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└─────────────────────────────────────────────────────────────┘
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```
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### Instrumentation Strategy
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```javascript
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// Before:
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function example() {
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let sum = 0;
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for (let i = 0; i < n; i++) {
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sum += compute(i);
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}
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return sum;
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}
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// After:
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function example() {
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let __t;
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__t = process.hrtime.bigint();
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let sum = 0;
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__profiler.record('example', 2, process.hrtime.bigint() - __t);
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__t = process.hrtime.bigint();
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for (let i = 0; i < n; i++) {
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__profiler.record('example', 3, process.hrtime.bigint() - __t);
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__t = process.hrtime.bigint();
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sum += compute(i);
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__profiler.record('example', 4, process.hrtime.bigint() - __t);
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__t = process.hrtime.bigint();
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}
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__profiler.record('example', 3, process.hrtime.bigint() - __t);
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__t = process.hrtime.bigint();
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const __ret = sum;
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__profiler.record('example', 6, process.hrtime.bigint() - __t);
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return __ret;
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}
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```
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### Special Cases to Handle
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1. **Return statements:** Store value, record time, then return
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2. **Loops:** Time loop overhead separately from body
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3. **Conditionals:** Time condition evaluation and each branch
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4. **Try/catch:** Wrap carefully to preserve exception semantics
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5. **Async/await:** Handle promise timing correctly
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### Output Format
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```json
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{
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"function": "bubbleSort",
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"file": "sort.js",
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"lines": [
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{"line": 4, "percent": 28.1, "calls": 44000, "avgNs": 42},
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{"line": 5, "percent": 21.6, "calls": 36000, "avgNs": 40},
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{"line": 6, "percent": 20.6, "calls": 17000, "avgNs": 80}
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],
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"hotSpots": [4, 5, 6]
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}
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```
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---
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## Comparison Summary
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| Approach | Line Granularity | Accuracy | Overhead | Complexity |
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|----------|------------------|----------|----------|------------|
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| V8 Sampling | Function only | Moderate | ~1-5% | Low |
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| Custom hrtime | Per-line | High | 2000-7500% | Medium |
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**Winner: Custom hrtime instrumentation**
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---
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## Files in This Experiment
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- `target-functions.js` - Test functions to profile
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- `custom-line-profiler.js` - Custom instrumentation implementation
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- `v8-inspector-profiler.js` - V8 inspector-based profiler
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- `run-experiment.js` - Main experiment runner
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- `experiment-results.json` - Detailed timing data
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- `RESULTS.md` - This summary document
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388
experiments/js-line-profiler/custom-line-profiler.js
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experiments/js-line-profiler/custom-line-profiler.js
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/**
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* Custom Line Profiler Implementation
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*
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* This profiler instruments JavaScript code by inserting timing calls
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* between each line to measure execution time per line.
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*
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* Approach: Insert process.hrtime.bigint() calls before and after each statement.
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*/
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const fs = require('fs');
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const path = require('path');
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// Global timing data storage
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const lineTimings = new Map(); // Map<filename, Map<lineNumber, {count, totalNs}>>
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// High-resolution timer
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function startTimer() {
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return process.hrtime.bigint();
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}
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function endTimer(start) {
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return process.hrtime.bigint() - start;
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}
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/**
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* Record timing for a specific line.
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*/
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function recordLineTiming(filename, lineNumber, durationNs) {
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if (!lineTimings.has(filename)) {
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lineTimings.set(filename, new Map());
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}
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const fileTimings = lineTimings.get(filename);
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if (!fileTimings.has(lineNumber)) {
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fileTimings.set(lineNumber, { count: 0, totalNs: BigInt(0) });
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}
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const timing = fileTimings.get(lineNumber);
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timing.count++;
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timing.totalNs += durationNs;
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}
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/**
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* Get all recorded timings.
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*/
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function getTimings() {
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const result = {};
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for (const [filename, fileTimings] of lineTimings) {
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result[filename] = {};
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for (const [lineNumber, data] of fileTimings) {
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result[filename][lineNumber] = {
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count: data.count,
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totalNs: Number(data.totalNs),
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avgNs: data.count > 0 ? Number(data.totalNs / BigInt(data.count)) : 0
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};
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}
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}
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return result;
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}
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/**
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* Clear all recorded timings.
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*/
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function clearTimings() {
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lineTimings.clear();
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}
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/**
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* Simple AST-free instrumentation using regex.
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* This is a simplified approach that works for common patterns.
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*/
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function instrumentFunction(funcSource, funcName, filename) {
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const lines = funcSource.split('\n');
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const instrumentedLines = [];
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// Track block depth for proper instrumentation
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let inFunction = false;
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let braceDepth = 0;
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for (let i = 0; i < lines.length; i++) {
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const line = lines[i];
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const lineNum = i + 1;
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const trimmed = line.trim();
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// Skip empty lines and comments
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if (!trimmed || trimmed.startsWith('//') || trimmed.startsWith('/*') || trimmed.startsWith('*')) {
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instrumentedLines.push(line);
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continue;
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}
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// Detect function start
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if (trimmed.includes('function') || trimmed.match(/^\s*(const|let|var)\s+\w+\s*=\s*(async\s*)?\(/)) {
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inFunction = true;
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}
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// Track braces
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const openBraces = (line.match(/{/g) || []).length;
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const closeBraces = (line.match(/}/g) || []).length;
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braceDepth += openBraces - closeBraces;
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// Skip lines that are just braces, function declarations, or control structures without body
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if (trimmed === '{' || trimmed === '}' ||
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trimmed.match(/^(function|if|else|for|while|switch|try|catch|finally)\s*[\({]?$/) ||
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trimmed.match(/^}\s*(else|catch|finally)/) ||
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trimmed.endsWith('{')) {
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instrumentedLines.push(line);
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continue;
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}
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// Don't instrument return statements that are just `return;`
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if (trimmed === 'return;') {
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instrumentedLines.push(line);
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continue;
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}
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// Add timing instrumentation
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const indent = line.match(/^(\s*)/)[1];
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const timerVar = `__t${lineNum}`;
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// Wrap the line with timing
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instrumentedLines.push(`${indent}const ${timerVar} = __profiler.startTimer();`);
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instrumentedLines.push(line);
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instrumentedLines.push(`${indent}__profiler.recordLineTiming('${filename}', ${lineNum}, __profiler.endTimer(${timerVar}));`);
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}
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return instrumentedLines.join('\n');
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}
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/**
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* More sophisticated instrumentation using a proper parser approach.
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* This creates wrapper functions that time each statement.
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*/
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function createProfiledVersion(originalFunc, funcName, filename) {
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// Get the source code
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const source = originalFunc.toString();
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// Parse out the function body (simplified)
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const bodyMatch = source.match(/\{([\s\S]*)\}$/);
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if (!bodyMatch) {
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console.error('Could not parse function body');
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return originalFunc;
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}
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const body = bodyMatch[1];
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const lines = body.split('\n');
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const instrumentedLines = [];
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// Get the function signature
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const sigMatch = source.match(/^((?:async\s+)?function\s*\w*\s*\([^)]*\)|(?:async\s+)?\([^)]*\)\s*=>|\([^)]*\)\s*=>)/);
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const signature = sigMatch ? sigMatch[1] : 'function()';
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for (let i = 0; i < lines.length; i++) {
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const line = lines[i];
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const lineNum = i + 1;
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const trimmed = line.trim();
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// Skip empty lines, comments, braces only
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if (!trimmed || trimmed.startsWith('//') || trimmed === '{' || trimmed === '}') {
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instrumentedLines.push(line);
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continue;
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}
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// Check if this is a statement that should be timed
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if (isTimableStatement(trimmed)) {
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const indent = line.match(/^(\s*)/)[1];
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const timerVar = `__t${lineNum}`;
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// Handle return statements specially
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if (trimmed.startsWith('return ')) {
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const returnExpr = trimmed.slice(7).replace(/;$/, '');
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instrumentedLines.push(`${indent}const ${timerVar} = __profiler.startTimer();`);
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instrumentedLines.push(`${indent}const __retVal${lineNum} = ${returnExpr};`);
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instrumentedLines.push(`${indent}__profiler.recordLineTiming('${filename}', ${lineNum}, __profiler.endTimer(${timerVar}));`);
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instrumentedLines.push(`${indent}return __retVal${lineNum};`);
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} else {
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instrumentedLines.push(`${indent}const ${timerVar} = __profiler.startTimer();`);
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instrumentedLines.push(line);
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instrumentedLines.push(`${indent}__profiler.recordLineTiming('${filename}', ${lineNum}, __profiler.endTimer(${timerVar}));`);
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}
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} else {
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instrumentedLines.push(line);
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}
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}
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// Reconstruct the function
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const instrumentedBody = instrumentedLines.join('\n');
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const instrumentedSource = `${signature} {\n${instrumentedBody}\n}`;
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// Create the new function with profiler in scope
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try {
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const wrappedFunc = new Function('__profiler', `return ${instrumentedSource}`);
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return wrappedFunc({
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startTimer,
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endTimer,
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recordLineTiming
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});
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} catch (e) {
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console.error('Failed to create instrumented function:', e.message);
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return originalFunc;
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}
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}
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function isTimableStatement(line) {
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// Skip control flow keywords (will time the body instead)
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if (line.match(/^(if|else|for|while|switch|case|default|try|catch|finally|do)\s*[\({]?/)) {
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return false;
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}
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// Skip braces and empty returns
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if (line === '{' || line === '}' || line === 'return;') {
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return false;
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}
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// Time everything else
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return true;
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}
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/**
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* Alternative approach: Manual instrumentation with explicit timing points.
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* This is the most accurate but requires more setup.
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*/
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function createManuallyInstrumentedFibonacci() {
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return function fibonacci_instrumented(n) {
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const timings = {};
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let t;
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// Line 1: if (n <= 1) return n;
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t = process.hrtime.bigint();
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const cond1 = n <= 1;
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recordLineTiming('fibonacci', 1, process.hrtime.bigint() - t);
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if (cond1) {
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t = process.hrtime.bigint();
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const ret = n;
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recordLineTiming('fibonacci', 1, process.hrtime.bigint() - t);
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return ret;
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}
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// Line 2: let a = 0;
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t = process.hrtime.bigint();
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let a = 0;
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recordLineTiming('fibonacci', 2, process.hrtime.bigint() - t);
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// Line 3: let b = 1;
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t = process.hrtime.bigint();
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let b = 1;
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recordLineTiming('fibonacci', 3, process.hrtime.bigint() - t);
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// Line 4-7: for loop
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t = process.hrtime.bigint();
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for (let i = 2; i <= n; i++) {
|
||||
recordLineTiming('fibonacci', 4, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 5: const temp = a + b;
|
||||
t = process.hrtime.bigint();
|
||||
const temp = a + b;
|
||||
recordLineTiming('fibonacci', 5, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 6: a = b;
|
||||
t = process.hrtime.bigint();
|
||||
a = b;
|
||||
recordLineTiming('fibonacci', 6, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 7: b = temp;
|
||||
t = process.hrtime.bigint();
|
||||
b = temp;
|
||||
recordLineTiming('fibonacci', 7, process.hrtime.bigint() - t);
|
||||
|
||||
// Loop iteration timing
|
||||
t = process.hrtime.bigint();
|
||||
}
|
||||
recordLineTiming('fibonacci', 4, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 8: return b;
|
||||
t = process.hrtime.bigint();
|
||||
const result = b;
|
||||
recordLineTiming('fibonacci', 8, process.hrtime.bigint() - t);
|
||||
return result;
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Manual instrumentation for reverseString
|
||||
*/
|
||||
function createManuallyInstrumentedReverseString() {
|
||||
return function reverseString_instrumented(str) {
|
||||
let t;
|
||||
|
||||
// Line 1: let result = '';
|
||||
t = process.hrtime.bigint();
|
||||
let result = '';
|
||||
recordLineTiming('reverseString', 1, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 2-4: for loop
|
||||
t = process.hrtime.bigint();
|
||||
for (let i = str.length - 1; i >= 0; i--) {
|
||||
recordLineTiming('reverseString', 2, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 3: result += str[i];
|
||||
t = process.hrtime.bigint();
|
||||
result += str[i];
|
||||
recordLineTiming('reverseString', 3, process.hrtime.bigint() - t);
|
||||
|
||||
t = process.hrtime.bigint();
|
||||
}
|
||||
recordLineTiming('reverseString', 2, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 5: return result;
|
||||
t = process.hrtime.bigint();
|
||||
const ret = result;
|
||||
recordLineTiming('reverseString', 5, process.hrtime.bigint() - t);
|
||||
return ret;
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Manual instrumentation for bubbleSort
|
||||
*/
|
||||
function createManuallyInstrumentedBubbleSort() {
|
||||
return function bubbleSort_instrumented(arr) {
|
||||
let t;
|
||||
|
||||
// Line 1: const n = arr.length;
|
||||
t = process.hrtime.bigint();
|
||||
const n = arr.length;
|
||||
recordLineTiming('bubbleSort', 1, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 2: const sorted = [...arr];
|
||||
t = process.hrtime.bigint();
|
||||
const sorted = [...arr];
|
||||
recordLineTiming('bubbleSort', 2, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 3: outer for loop
|
||||
t = process.hrtime.bigint();
|
||||
for (let i = 0; i < n - 1; i++) {
|
||||
recordLineTiming('bubbleSort', 3, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 4: inner for loop
|
||||
t = process.hrtime.bigint();
|
||||
for (let j = 0; j < n - i - 1; j++) {
|
||||
recordLineTiming('bubbleSort', 4, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 5: if (sorted[j] > sorted[j + 1])
|
||||
t = process.hrtime.bigint();
|
||||
if (sorted[j] > sorted[j + 1]) {
|
||||
recordLineTiming('bubbleSort', 5, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 6: const temp = sorted[j];
|
||||
t = process.hrtime.bigint();
|
||||
const temp = sorted[j];
|
||||
recordLineTiming('bubbleSort', 6, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 7: sorted[j] = sorted[j + 1];
|
||||
t = process.hrtime.bigint();
|
||||
sorted[j] = sorted[j + 1];
|
||||
recordLineTiming('bubbleSort', 7, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 8: sorted[j + 1] = temp;
|
||||
t = process.hrtime.bigint();
|
||||
sorted[j + 1] = temp;
|
||||
recordLineTiming('bubbleSort', 8, process.hrtime.bigint() - t);
|
||||
} else {
|
||||
recordLineTiming('bubbleSort', 5, process.hrtime.bigint() - t);
|
||||
}
|
||||
|
||||
t = process.hrtime.bigint();
|
||||
}
|
||||
recordLineTiming('bubbleSort', 4, process.hrtime.bigint() - t);
|
||||
|
||||
t = process.hrtime.bigint();
|
||||
}
|
||||
recordLineTiming('bubbleSort', 3, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 12: return sorted;
|
||||
t = process.hrtime.bigint();
|
||||
const ret = sorted;
|
||||
recordLineTiming('bubbleSort', 12, process.hrtime.bigint() - t);
|
||||
return ret;
|
||||
};
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
startTimer,
|
||||
endTimer,
|
||||
recordLineTiming,
|
||||
getTimings,
|
||||
clearTimings,
|
||||
instrumentFunction,
|
||||
createProfiledVersion,
|
||||
createManuallyInstrumentedFibonacci,
|
||||
createManuallyInstrumentedReverseString,
|
||||
createManuallyInstrumentedBubbleSort
|
||||
};
|
||||
552
experiments/js-line-profiler/experiment-results.json
Normal file
552
experiments/js-line-profiler/experiment-results.json
Normal file
|
|
@ -0,0 +1,552 @@
|
|||
{
|
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"v8Profiler": {
|
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"totalSamples": 6028,
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"lineTimings": {
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"node:internal/main/run_main_module": {
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"1": {
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"hits": 0,
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"functionName": "(anonymous)",
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"selfTime": 0,
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"percentage": "0.00"
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}
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},
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"node:internal/modules/run_main": {
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"140": {
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"hits": 0,
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"functionName": "executeUserEntryPoint",
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"selfTime": 0,
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"percentage": "0.00"
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}
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},
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"node:internal/modules/cjs/loader": {
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"231": {
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"hits": 0,
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"functionName": "wrapModuleLoad",
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"selfTime": 0,
|
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"percentage": "0.00"
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},
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"1196": {
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"hits": 0,
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"functionName": "(anonymous)",
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"selfTime": 0,
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"percentage": "0.00"
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},
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"1461": {
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"hits": 0,
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"functionName": "(anonymous)",
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"selfTime": 0,
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"percentage": "0.00"
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"hits": 0,
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"functionName": "(anonymous)",
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"selfTime": 0,
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"percentage": "0.00"
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"1836": {
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"hits": 0,
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"functionName": "(anonymous)",
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"selfTime": 0,
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"percentage": "0.00"
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},
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"node:diagnostics_channel": {
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"208": {
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"hits": 1,
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"functionName": "get hasSubscribers",
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"selfTime": 0,
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"percentage": "0.02"
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"320": {
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"hits": 0,
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"functionName": "traceSync",
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"selfTime": 0,
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}
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"file:///Users/saurabh/Library/CloudStorage/Dropbox/codeflash/experiments/js-line-profiler/run-experiment.js": {
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"hits": 0,
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"selfTime": 0,
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"percentage": "0.00"
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"100": {
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"hits": 1048,
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"functionName": "experimentV8Profiler",
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"selfTime": 0,
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"percentage": "17.39"
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},
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"552": {
|
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"hits": 0,
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"functionName": "main",
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"selfTime": 0,
|
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"percentage": "0.00"
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}
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},
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"file:///Users/saurabh/Library/CloudStorage/Dropbox/codeflash/experiments/js-line-profiler/v8-inspector-profiler.js": {
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"120": {
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"hits": 0,
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"functionName": "startPreciseProfiling",
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"selfTime": 0,
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"selfTime": 0,
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"percentage": "0.00"
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"131": {
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"hits": 0,
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"functionName": "(anonymous)",
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"selfTime": 0,
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"percentage": "0.00"
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"138": {
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"hits": 0,
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"functionName": "(anonymous)",
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"selfTime": 0,
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"percentage": "0.00"
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},
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"153": {
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"hits": 2,
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"functionName": "stopPreciseProfiling",
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"selfTime": 0,
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"percentage": "0.03"
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},
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"154": {
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"hits": 1,
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"selfTime": 0,
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"156": {
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"hits": 0,
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"functionName": "(anonymous)",
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"selfTime": 0,
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"percentage": "0.00"
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},
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"node:inspector": {
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"66": {
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"hits": 0,
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"functionName": "(anonymous)",
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"selfTime": 0,
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"percentage": "0.00"
|
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},
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"84": {
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"hits": 9,
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"functionName": "#onMessage",
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"selfTime": 0,
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"percentage": "0.15"
|
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"115": {
|
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"hits": 7,
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"functionName": "post",
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"selfTime": 0,
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"percentage": "0.12"
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}
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},
|
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"node:internal/process/task_queues": {
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"72": {
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"hits": 2,
|
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"functionName": "processTicksAndRejections",
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"selfTime": 0,
|
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"percentage": "0.03"
|
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}
|
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},
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"node:internal/async_hooks": {
|
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"509": {
|
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"hits": 0,
|
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"functionName": "emitBeforeScript",
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"selfTime": 0,
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"539": {
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"hits": 1,
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"selfTime": 0,
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"percentage": "0.02"
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}
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},
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"451": {
|
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"hits": 0,
|
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"functionName": "_write",
|
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"selfTime": 0,
|
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"percentage": "0.00"
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},
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"502": {
|
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"hits": 0,
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"functionName": "Writable.write",
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"selfTime": 0,
|
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"percentage": "0.00"
|
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},
|
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"546": {
|
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"hits": 0,
|
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"functionName": "writeOrBuffer",
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"selfTime": 0,
|
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"percentage": "0.00"
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},
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"613": {
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"hits": 1,
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"functionName": "onwrite",
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"selfTime": 0,
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"hits": 3,
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"percentage": "0.00"
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},
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"node:internal/console/constructor": {
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"270": {
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"hits": 0,
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"functionName": "value",
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"percentage": "0.02"
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"352": {
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"hits": 1,
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"functionName": "(anonymous)",
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"selfTime": 0,
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"percentage": "0.02"
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"380": {
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"hits": 1,
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"functionName": "log",
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"selfTime": 0,
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"percentage": "0.02"
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}
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},
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"node:net": {
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"935": {
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"hits": 0,
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"functionName": "Socket._writeGeneric",
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"selfTime": 0,
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"percentage": "0.00"
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},
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"977": {
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"hits": 0,
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"functionName": "Socket._write",
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"selfTime": 0,
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"percentage": "0.00"
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}
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},
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"node:internal/stream_base_commons": {
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"46": {
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"hits": 1,
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"functionName": "handleWriteReq",
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"selfTime": 0,
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"percentage": "0.02"
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},
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"146": {
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"hits": 0,
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"functionName": "writeGeneric",
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"selfTime": 0,
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"percentage": "0.00"
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},
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"154": {
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"functionName": "afterWriteDispatched",
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"selfTime": 0,
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"percentage": "0.00"
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}
|
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},
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"file:///Users/saurabh/Library/CloudStorage/Dropbox/codeflash/experiments/js-line-profiler/target-functions.js": {
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"7": {
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"hits": 115,
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"selfTime": 0,
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"20": {
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"hits": 3723,
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"selfTime": 0,
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"percentage": "61.76"
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"29": {
|
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"hits": 281,
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"functionName": "bubbleSort",
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"selfTime": 0,
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"percentage": "4.66"
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}
|
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}
|
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},
|
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"overhead": "Low (sampling-based)",
|
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"granularity": "Function-level with approximate line info"
|
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},
|
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"customInstrumentation": {
|
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"baselines": {
|
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"fibonacci": 131.6041,
|
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"reverseString": 8660.625,
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"bubbleSort": 343.25
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"instrumented": {
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"fibonacci": 10015.8834,
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"reverseString": 199992.0834,
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"bubbleSort": 18676.75
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"overhead": {
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"fibonacci": "7510.6%",
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"reverseString": "2209.2%",
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"bubbleSort": "5341.2%"
|
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},
|
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"lineTimings": {
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"bubbleSort": {
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"1": {
|
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"count": 1000,
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"totalNs": 31470,
|
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"avgNs": 31
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"2": {
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"count": 1000,
|
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"totalNs": 66183,
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"avgNs": 66
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},
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"3": {
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"count": 9000,
|
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"totalNs": 428141,
|
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"avgNs": 47
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},
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"4": {
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"count": 44000,
|
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"totalNs": 1869701,
|
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"avgNs": 42
|
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},
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"5": {
|
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"count": 36000,
|
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"totalNs": 1440002,
|
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"avgNs": 40
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},
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"6": {
|
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"count": 17000,
|
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"totalNs": 1373060,
|
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"avgNs": 80
|
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},
|
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"7": {
|
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"count": 17000,
|
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"totalNs": 614225,
|
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"avgNs": 36
|
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|
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"8": {
|
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"count": 17000,
|
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|
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|
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|
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"12": {
|
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"count": 1000,
|
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"totalNs": 36250,
|
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"avgNs": 36
|
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}
|
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}
|
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}
|
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},
|
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"timingAccuracy": {
|
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"timerOverhead": {
|
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"avg": 961.5024,
|
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"min": 0,
|
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"max": 4347084
|
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},
|
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"consistency": {
|
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"coefficientOfVariation": "83.38%",
|
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"runs": [
|
||||
1051.6875,
|
||||
724.51125,
|
||||
160.24958,
|
||||
226.12625,
|
||||
86.71
|
||||
]
|
||||
},
|
||||
"jitWarmup": [
|
||||
188.5,
|
||||
39.375,
|
||||
28.625,
|
||||
28.75,
|
||||
28.5,
|
||||
28.542,
|
||||
28.541,
|
||||
28.459,
|
||||
28.583,
|
||||
28.417
|
||||
]
|
||||
},
|
||||
"relativeAccuracy": {
|
||||
"timings": {
|
||||
"1": {
|
||||
"count": 5000,
|
||||
"totalNs": 154166,
|
||||
"avgNs": 30
|
||||
},
|
||||
"2": {
|
||||
"count": 505000,
|
||||
"totalNs": 14558153,
|
||||
"avgNs": 28
|
||||
},
|
||||
"3": {
|
||||
"count": 500000,
|
||||
"totalNs": 20127647,
|
||||
"avgNs": 40
|
||||
},
|
||||
"4": {
|
||||
"count": 500000,
|
||||
"totalNs": 18310123,
|
||||
"avgNs": 36
|
||||
},
|
||||
"5": {
|
||||
"count": 500000,
|
||||
"totalNs": 67101211,
|
||||
"avgNs": 134
|
||||
},
|
||||
"6": {
|
||||
"count": 500000,
|
||||
"totalNs": 14333615,
|
||||
"avgNs": 28
|
||||
},
|
||||
"7": {
|
||||
"count": 5000,
|
||||
"totalNs": 168393,
|
||||
"avgNs": 33
|
||||
}
|
||||
},
|
||||
"verification": {
|
||||
"arrayMostExpensive": true,
|
||||
"toStringMoreThanArithmetic": true
|
||||
}
|
||||
},
|
||||
"realWorld": {
|
||||
"fibonacci": {
|
||||
"1": {
|
||||
"count": 10000,
|
||||
"totalNs": 314800,
|
||||
"avgNs": 31
|
||||
},
|
||||
"2": {
|
||||
"count": 10000,
|
||||
"totalNs": 341056,
|
||||
"avgNs": 34
|
||||
},
|
||||
"3": {
|
||||
"count": 10000,
|
||||
"totalNs": 359398,
|
||||
"avgNs": 35
|
||||
},
|
||||
"4": {
|
||||
"count": 400000,
|
||||
"totalNs": 11982999,
|
||||
"avgNs": 29
|
||||
},
|
||||
"5": {
|
||||
"count": 390000,
|
||||
"totalNs": 14024067,
|
||||
"avgNs": 35
|
||||
},
|
||||
"6": {
|
||||
"count": 390000,
|
||||
"totalNs": 10662935,
|
||||
"avgNs": 27
|
||||
},
|
||||
"7": {
|
||||
"count": 390000,
|
||||
"totalNs": 9631790,
|
||||
"avgNs": 24
|
||||
},
|
||||
"8": {
|
||||
"count": 10000,
|
||||
"totalNs": 318849,
|
||||
"avgNs": 31
|
||||
}
|
||||
},
|
||||
"reverseString": {
|
||||
"1": {
|
||||
"count": 10000,
|
||||
"totalNs": 334349,
|
||||
"avgNs": 33
|
||||
},
|
||||
"2": {
|
||||
"count": 12010000,
|
||||
"totalNs": 356400729,
|
||||
"avgNs": 29
|
||||
},
|
||||
"3": {
|
||||
"count": 12000000,
|
||||
"totalNs": 445353788,
|
||||
"avgNs": 37
|
||||
},
|
||||
"5": {
|
||||
"count": 10000,
|
||||
"totalNs": 294722,
|
||||
"avgNs": 29
|
||||
}
|
||||
},
|
||||
"bubbleSort": {
|
||||
"1": {
|
||||
"count": 1000,
|
||||
"totalNs": 30428,
|
||||
"avgNs": 30
|
||||
},
|
||||
"2": {
|
||||
"count": 1000,
|
||||
"totalNs": 123658,
|
||||
"avgNs": 123
|
||||
},
|
||||
"3": {
|
||||
"count": 100000,
|
||||
"totalNs": 3536118,
|
||||
"avgNs": 35
|
||||
},
|
||||
"4": {
|
||||
"count": 5049000,
|
||||
"totalNs": 152396965,
|
||||
"avgNs": 30
|
||||
},
|
||||
"5": {
|
||||
"count": 4950000,
|
||||
"totalNs": 142842371,
|
||||
"avgNs": 28
|
||||
},
|
||||
"6": {
|
||||
"count": 2602000,
|
||||
"totalNs": 87089187,
|
||||
"avgNs": 33
|
||||
},
|
||||
"7": {
|
||||
"count": 2602000,
|
||||
"totalNs": 93142681,
|
||||
"avgNs": 35
|
||||
},
|
||||
"8": {
|
||||
"count": 2602000,
|
||||
"totalNs": 94325697,
|
||||
"avgNs": 36
|
||||
},
|
||||
"12": {
|
||||
"count": 1000,
|
||||
"totalNs": 33170,
|
||||
"avgNs": 33
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
13
experiments/js-line-profiler/package.json
Normal file
13
experiments/js-line-profiler/package.json
Normal file
|
|
@ -0,0 +1,13 @@
|
|||
{
|
||||
"name": "js-line-profiler",
|
||||
"version": "1.0.0",
|
||||
"description": "",
|
||||
"main": "index.js",
|
||||
"scripts": {
|
||||
"test": "echo \"Error: no test specified\" && exit 1"
|
||||
},
|
||||
"keywords": [],
|
||||
"author": "",
|
||||
"license": "ISC",
|
||||
"type": "commonjs"
|
||||
}
|
||||
648
experiments/js-line-profiler/run-experiment.js
Normal file
648
experiments/js-line-profiler/run-experiment.js
Normal file
|
|
@ -0,0 +1,648 @@
|
|||
/**
|
||||
* Line Profiler Experiment
|
||||
*
|
||||
* Compares different approaches to line-level profiling in Node.js:
|
||||
* 1. V8 Inspector sampling profiler
|
||||
* 2. Custom instrumentation with process.hrtime.bigint()
|
||||
* 3. Manual instrumentation (most accurate baseline)
|
||||
*
|
||||
* Evaluates:
|
||||
* - Accuracy of timing measurements
|
||||
* - Overhead introduced by profiling
|
||||
* - Granularity of line-level data
|
||||
* - JIT warmup effects
|
||||
*/
|
||||
|
||||
const {
|
||||
fibonacci,
|
||||
reverseString,
|
||||
bubbleSort,
|
||||
countWords,
|
||||
matrixMultiply,
|
||||
classifyNumber
|
||||
} = require('./target-functions');
|
||||
|
||||
const customProfiler = require('./custom-line-profiler');
|
||||
const v8Profiler = require('./v8-inspector-profiler');
|
||||
|
||||
// ============================================================================
|
||||
// Experiment Configuration
|
||||
// ============================================================================
|
||||
|
||||
const WARMUP_ITERATIONS = 1000;
|
||||
const MEASUREMENT_ITERATIONS = 10000;
|
||||
const RESULTS = {};
|
||||
|
||||
// ============================================================================
|
||||
// Utility Functions
|
||||
// ============================================================================
|
||||
|
||||
function formatNs(ns) {
|
||||
if (ns < 1000) return `${ns.toFixed(0)}ns`;
|
||||
if (ns < 1000000) return `${(ns / 1000).toFixed(2)}μs`;
|
||||
if (ns < 1000000000) return `${(ns / 1000000).toFixed(2)}ms`;
|
||||
return `${(ns / 1000000000).toFixed(2)}s`;
|
||||
}
|
||||
|
||||
function formatPercent(value, total) {
|
||||
return ((value / total) * 100).toFixed(1) + '%';
|
||||
}
|
||||
|
||||
/**
|
||||
* Measure baseline execution time without profiling.
|
||||
*/
|
||||
function measureBaseline(func, args, iterations) {
|
||||
// Warmup
|
||||
for (let i = 0; i < WARMUP_ITERATIONS; i++) {
|
||||
func(...args);
|
||||
}
|
||||
|
||||
// Measure
|
||||
const start = process.hrtime.bigint();
|
||||
for (let i = 0; i < iterations; i++) {
|
||||
func(...args);
|
||||
}
|
||||
const end = process.hrtime.bigint();
|
||||
|
||||
return Number(end - start) / iterations;
|
||||
}
|
||||
|
||||
/**
|
||||
* Measure execution time with custom instrumentation.
|
||||
*/
|
||||
function measureInstrumented(func, args, iterations) {
|
||||
customProfiler.clearTimings();
|
||||
|
||||
// Warmup
|
||||
for (let i = 0; i < WARMUP_ITERATIONS; i++) {
|
||||
func(...args);
|
||||
}
|
||||
|
||||
customProfiler.clearTimings();
|
||||
|
||||
// Measure
|
||||
const start = process.hrtime.bigint();
|
||||
for (let i = 0; i < iterations; i++) {
|
||||
func(...args);
|
||||
}
|
||||
const end = process.hrtime.bigint();
|
||||
|
||||
return {
|
||||
avgTimeNs: Number(end - start) / iterations,
|
||||
timings: customProfiler.getTimings()
|
||||
};
|
||||
}
|
||||
|
||||
// ============================================================================
|
||||
// Experiment 1: V8 Inspector Sampling Profiler
|
||||
// ============================================================================
|
||||
|
||||
async function experimentV8Profiler() {
|
||||
console.log('\n' + '='.repeat(70));
|
||||
console.log('EXPERIMENT 1: V8 Inspector Sampling Profiler');
|
||||
console.log('='.repeat(70));
|
||||
console.log('Uses V8\'s built-in sampling profiler via the inspector protocol.');
|
||||
console.log('Advantage: Low overhead, no code modification required.');
|
||||
console.log('Disadvantage: Sampling-based, may miss short-lived operations.\n');
|
||||
|
||||
try {
|
||||
// Start profiling
|
||||
await v8Profiler.startPreciseProfiling();
|
||||
|
||||
// Warmup
|
||||
console.log('Warming up...');
|
||||
for (let i = 0; i < WARMUP_ITERATIONS; i++) {
|
||||
fibonacci(30);
|
||||
reverseString('hello world '.repeat(100));
|
||||
bubbleSort([5, 3, 8, 1, 9, 2, 7, 4, 6]);
|
||||
}
|
||||
|
||||
// Run measurements
|
||||
console.log('Running measurements...');
|
||||
const iterations = 5000;
|
||||
for (let i = 0; i < iterations; i++) {
|
||||
fibonacci(30);
|
||||
reverseString('hello world '.repeat(100));
|
||||
bubbleSort([5, 3, 8, 1, 9, 2, 7, 4, 6]);
|
||||
}
|
||||
|
||||
// Stop and get results
|
||||
const { profile, coverage } = await v8Profiler.stopPreciseProfiling();
|
||||
v8Profiler.disconnect();
|
||||
|
||||
// Parse and display results
|
||||
const lineTimings = v8Profiler.parseProfile(profile);
|
||||
|
||||
console.log('\n--- V8 Profiler Results ---');
|
||||
console.log(`Total samples: ${profile.samples?.length || 0}`);
|
||||
console.log(`Sampling interval: ${profile.samplingInterval || 'unknown'}μs`);
|
||||
|
||||
// Show top hotspots
|
||||
const allLines = [];
|
||||
for (const [filename, lines] of Object.entries(lineTimings)) {
|
||||
if (filename.includes('target-functions')) {
|
||||
for (const [line, data] of Object.entries(lines)) {
|
||||
allLines.push({ filename, line, ...data });
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
allLines.sort((a, b) => b.hits - a.hits);
|
||||
console.log('\nTop 10 hotspots:');
|
||||
for (const entry of allLines.slice(0, 10)) {
|
||||
console.log(` ${entry.functionName} line ${entry.line}: ${entry.hits} hits (${entry.percentage}%)`);
|
||||
}
|
||||
|
||||
RESULTS.v8Profiler = {
|
||||
totalSamples: profile.samples?.length || 0,
|
||||
lineTimings,
|
||||
overhead: 'Low (sampling-based)',
|
||||
granularity: 'Function-level with approximate line info'
|
||||
};
|
||||
|
||||
} catch (err) {
|
||||
console.error('V8 Profiler experiment failed:', err.message);
|
||||
RESULTS.v8Profiler = { error: err.message };
|
||||
}
|
||||
}
|
||||
|
||||
// ============================================================================
|
||||
// Experiment 2: Custom hrtime.bigint() Instrumentation
|
||||
// ============================================================================
|
||||
|
||||
async function experimentCustomInstrumentation() {
|
||||
console.log('\n' + '='.repeat(70));
|
||||
console.log('EXPERIMENT 2: Custom process.hrtime.bigint() Instrumentation');
|
||||
console.log('='.repeat(70));
|
||||
console.log('Inserts timing calls around each statement.');
|
||||
console.log('Advantage: Precise per-line timing.');
|
||||
console.log('Disadvantage: Significant overhead, requires code transformation.\n');
|
||||
|
||||
// Test manually instrumented functions
|
||||
const instrumentedFib = customProfiler.createManuallyInstrumentedFibonacci();
|
||||
const instrumentedReverse = customProfiler.createManuallyInstrumentedReverseString();
|
||||
const instrumentedBubble = customProfiler.createManuallyInstrumentedBubbleSort();
|
||||
|
||||
// Measure baseline
|
||||
console.log('Measuring baseline (uninstrumented)...');
|
||||
const baselineFib = measureBaseline(fibonacci, [30], MEASUREMENT_ITERATIONS);
|
||||
const baselineReverse = measureBaseline(reverseString, ['hello world '.repeat(100)], MEASUREMENT_ITERATIONS);
|
||||
const baselineBubble = measureBaseline(bubbleSort, [[5, 3, 8, 1, 9, 2, 7, 4, 6]], MEASUREMENT_ITERATIONS / 10);
|
||||
|
||||
console.log(` fibonacci(30): ${formatNs(baselineFib)} per call`);
|
||||
console.log(` reverseString: ${formatNs(baselineReverse)} per call`);
|
||||
console.log(` bubbleSort: ${formatNs(baselineBubble)} per call`);
|
||||
|
||||
// Measure instrumented
|
||||
console.log('\nMeasuring instrumented...');
|
||||
customProfiler.clearTimings();
|
||||
|
||||
const instrFibResult = measureInstrumented(instrumentedFib, [30], MEASUREMENT_ITERATIONS);
|
||||
const instrReverseResult = measureInstrumented(instrumentedReverse, ['hello world '.repeat(100)], MEASUREMENT_ITERATIONS);
|
||||
const instrBubbleResult = measureInstrumented(instrumentedBubble, [[5, 3, 8, 1, 9, 2, 7, 4, 6]], MEASUREMENT_ITERATIONS / 10);
|
||||
|
||||
console.log(` fibonacci(30): ${formatNs(instrFibResult.avgTimeNs)} per call`);
|
||||
console.log(` reverseString: ${formatNs(instrReverseResult.avgTimeNs)} per call`);
|
||||
console.log(` bubbleSort: ${formatNs(instrBubbleResult.avgTimeNs)} per call`);
|
||||
|
||||
// Calculate overhead
|
||||
const overheadFib = ((instrFibResult.avgTimeNs - baselineFib) / baselineFib * 100).toFixed(1);
|
||||
const overheadReverse = ((instrReverseResult.avgTimeNs - baselineReverse) / baselineReverse * 100).toFixed(1);
|
||||
const overheadBubble = ((instrBubbleResult.avgTimeNs - baselineBubble) / baselineBubble * 100).toFixed(1);
|
||||
|
||||
console.log('\n--- Overhead Analysis ---');
|
||||
console.log(` fibonacci: +${overheadFib}% overhead`);
|
||||
console.log(` reverseString: +${overheadReverse}% overhead`);
|
||||
console.log(` bubbleSort: +${overheadBubble}% overhead`);
|
||||
|
||||
// Display line-level timings
|
||||
console.log('\n--- Line-Level Timings (from instrumented runs) ---');
|
||||
|
||||
const allTimings = customProfiler.getTimings();
|
||||
for (const [funcName, lines] of Object.entries(allTimings)) {
|
||||
console.log(`\n${funcName}:`);
|
||||
const sortedLines = Object.entries(lines)
|
||||
.sort(([a], [b]) => parseInt(a) - parseInt(b));
|
||||
|
||||
let totalTime = 0;
|
||||
for (const [line, data] of sortedLines) {
|
||||
totalTime += data.totalNs;
|
||||
}
|
||||
|
||||
for (const [line, data] of sortedLines) {
|
||||
const pct = formatPercent(data.totalNs, totalTime);
|
||||
console.log(` Line ${line.padStart(2)}: ${data.count.toString().padStart(10)} calls, ` +
|
||||
`${formatNs(data.avgNs).padStart(10)} avg, ` +
|
||||
`${formatNs(data.totalNs).padStart(12)} total (${pct})`);
|
||||
}
|
||||
}
|
||||
|
||||
RESULTS.customInstrumentation = {
|
||||
baselines: {
|
||||
fibonacci: baselineFib,
|
||||
reverseString: baselineReverse,
|
||||
bubbleSort: baselineBubble
|
||||
},
|
||||
instrumented: {
|
||||
fibonacci: instrFibResult.avgTimeNs,
|
||||
reverseString: instrReverseResult.avgTimeNs,
|
||||
bubbleSort: instrBubbleResult.avgTimeNs
|
||||
},
|
||||
overhead: {
|
||||
fibonacci: overheadFib + '%',
|
||||
reverseString: overheadReverse + '%',
|
||||
bubbleSort: overheadBubble + '%'
|
||||
},
|
||||
lineTimings: allTimings
|
||||
};
|
||||
}
|
||||
|
||||
// ============================================================================
|
||||
// Experiment 3: Timing Accuracy Verification
|
||||
// ============================================================================
|
||||
|
||||
async function experimentTimingAccuracy() {
|
||||
console.log('\n' + '='.repeat(70));
|
||||
console.log('EXPERIMENT 3: Timing Accuracy Verification');
|
||||
console.log('='.repeat(70));
|
||||
console.log('Verifies that hrtime.bigint() timings are consistent and accurate.\n');
|
||||
|
||||
// Test 1: Timer overhead
|
||||
console.log('Test 1: Measuring timer overhead...');
|
||||
const timerOverheads = [];
|
||||
for (let i = 0; i < 10000; i++) {
|
||||
const start = process.hrtime.bigint();
|
||||
const end = process.hrtime.bigint();
|
||||
timerOverheads.push(Number(end - start));
|
||||
}
|
||||
const avgTimerOverhead = timerOverheads.reduce((a, b) => a + b, 0) / timerOverheads.length;
|
||||
const minTimerOverhead = Math.min(...timerOverheads);
|
||||
const maxTimerOverhead = Math.max(...timerOverheads);
|
||||
|
||||
console.log(` Average timer overhead: ${formatNs(avgTimerOverhead)}`);
|
||||
console.log(` Min: ${formatNs(minTimerOverhead)}, Max: ${formatNs(maxTimerOverhead)}`);
|
||||
|
||||
// Test 2: Consistency across runs
|
||||
console.log('\nTest 2: Timing consistency across runs...');
|
||||
const runs = [];
|
||||
for (let run = 0; run < 5; run++) {
|
||||
const start = process.hrtime.bigint();
|
||||
for (let i = 0; i < 100000; i++) {
|
||||
fibonacci(20);
|
||||
}
|
||||
const end = process.hrtime.bigint();
|
||||
runs.push(Number(end - start) / 100000);
|
||||
}
|
||||
const avgRun = runs.reduce((a, b) => a + b, 0) / runs.length;
|
||||
const variance = runs.reduce((sum, r) => sum + Math.pow(r - avgRun, 2), 0) / runs.length;
|
||||
const stdDev = Math.sqrt(variance);
|
||||
const coeffVar = (stdDev / avgRun * 100).toFixed(2);
|
||||
|
||||
console.log(' Run times (ns per call): ' + runs.map(r => formatNs(r)).join(', '));
|
||||
console.log(` Average: ${formatNs(avgRun)}`);
|
||||
console.log(` Std Dev: ${formatNs(stdDev)}`);
|
||||
console.log(` Coefficient of Variation: ${coeffVar}%`);
|
||||
|
||||
// Test 3: JIT warmup effect
|
||||
console.log('\nTest 3: JIT warmup effect...');
|
||||
// Create a fresh function to see JIT progression
|
||||
const freshFunc = new Function('n', `
|
||||
if (n <= 1) return n;
|
||||
let a = 0, b = 1;
|
||||
for (let i = 2; i <= n; i++) {
|
||||
const temp = a + b;
|
||||
a = b;
|
||||
b = temp;
|
||||
}
|
||||
return b;
|
||||
`);
|
||||
|
||||
const jitTimings = [];
|
||||
for (let batch = 0; batch < 10; batch++) {
|
||||
const start = process.hrtime.bigint();
|
||||
for (let i = 0; i < 1000; i++) {
|
||||
freshFunc(30);
|
||||
}
|
||||
const end = process.hrtime.bigint();
|
||||
jitTimings.push(Number(end - start) / 1000);
|
||||
}
|
||||
|
||||
console.log(' Batch timings (ns per call): ');
|
||||
for (let i = 0; i < jitTimings.length; i++) {
|
||||
const speedup = i > 0 ? ((jitTimings[0] - jitTimings[i]) / jitTimings[0] * 100).toFixed(1) : '0.0';
|
||||
console.log(` Batch ${i + 1}: ${formatNs(jitTimings[i])} (${speedup}% faster than first)`);
|
||||
}
|
||||
|
||||
RESULTS.timingAccuracy = {
|
||||
timerOverhead: {
|
||||
avg: avgTimerOverhead,
|
||||
min: minTimerOverhead,
|
||||
max: maxTimerOverhead
|
||||
},
|
||||
consistency: {
|
||||
coefficientOfVariation: coeffVar + '%',
|
||||
runs
|
||||
},
|
||||
jitWarmup: jitTimings
|
||||
};
|
||||
}
|
||||
|
||||
// ============================================================================
|
||||
// Experiment 4: Line Timing Relative Accuracy
|
||||
// ============================================================================
|
||||
|
||||
async function experimentRelativeAccuracy() {
|
||||
console.log('\n' + '='.repeat(70));
|
||||
console.log('EXPERIMENT 4: Relative Line Timing Accuracy');
|
||||
console.log('='.repeat(70));
|
||||
console.log('Tests if line timings correctly identify hot spots.\n');
|
||||
|
||||
// Create a function with known expensive and cheap lines
|
||||
const testFunc = function knownProfile(n) {
|
||||
// Line 1: Cheap - variable declaration
|
||||
let result = 0;
|
||||
|
||||
// Line 2: Expensive - loop with computation
|
||||
for (let i = 0; i < n; i++) {
|
||||
// Line 3: Medium - string operation
|
||||
const str = i.toString();
|
||||
|
||||
// Line 4: Cheap - simple arithmetic
|
||||
result += i;
|
||||
|
||||
// Line 5: Expensive - array allocation
|
||||
const arr = new Array(100).fill(i);
|
||||
|
||||
// Line 6: Cheap - property access
|
||||
const len = arr.length;
|
||||
}
|
||||
|
||||
// Line 7: Return
|
||||
return result;
|
||||
};
|
||||
|
||||
// Manually instrumented version
|
||||
const instrumentedTest = function knownProfile_instrumented(n) {
|
||||
let t;
|
||||
const timings = {};
|
||||
|
||||
// Line 1: Cheap - variable declaration
|
||||
t = process.hrtime.bigint();
|
||||
let result = 0;
|
||||
customProfiler.recordLineTiming('knownProfile', 1, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 2: Loop
|
||||
t = process.hrtime.bigint();
|
||||
for (let i = 0; i < n; i++) {
|
||||
customProfiler.recordLineTiming('knownProfile', 2, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 3: String operation
|
||||
t = process.hrtime.bigint();
|
||||
const str = i.toString();
|
||||
customProfiler.recordLineTiming('knownProfile', 3, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 4: Simple arithmetic
|
||||
t = process.hrtime.bigint();
|
||||
result += i;
|
||||
customProfiler.recordLineTiming('knownProfile', 4, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 5: Array allocation
|
||||
t = process.hrtime.bigint();
|
||||
const arr = new Array(100).fill(i);
|
||||
customProfiler.recordLineTiming('knownProfile', 5, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 6: Property access
|
||||
t = process.hrtime.bigint();
|
||||
const len = arr.length;
|
||||
customProfiler.recordLineTiming('knownProfile', 6, process.hrtime.bigint() - t);
|
||||
|
||||
t = process.hrtime.bigint();
|
||||
}
|
||||
customProfiler.recordLineTiming('knownProfile', 2, process.hrtime.bigint() - t);
|
||||
|
||||
// Line 7: Return
|
||||
t = process.hrtime.bigint();
|
||||
const ret = result;
|
||||
customProfiler.recordLineTiming('knownProfile', 7, process.hrtime.bigint() - t);
|
||||
return ret;
|
||||
};
|
||||
|
||||
// Warmup
|
||||
for (let i = 0; i < 1000; i++) {
|
||||
instrumentedTest(100);
|
||||
}
|
||||
|
||||
// Measure
|
||||
customProfiler.clearTimings();
|
||||
for (let i = 0; i < 5000; i++) {
|
||||
instrumentedTest(100);
|
||||
}
|
||||
|
||||
const timings = customProfiler.getTimings()['knownProfile'];
|
||||
|
||||
console.log('Expected relative costs:');
|
||||
console.log(' Line 1 (var decl): Very cheap');
|
||||
console.log(' Line 2 (loop overhead): Cheap');
|
||||
console.log(' Line 3 (toString): Medium');
|
||||
console.log(' Line 4 (arithmetic): Very cheap');
|
||||
console.log(' Line 5 (array alloc): Expensive');
|
||||
console.log(' Line 6 (property): Very cheap');
|
||||
console.log(' Line 7 (return): Very cheap');
|
||||
|
||||
console.log('\nActual measured costs:');
|
||||
let totalTime = 0;
|
||||
for (const data of Object.values(timings)) {
|
||||
totalTime += data.totalNs;
|
||||
}
|
||||
|
||||
const sortedLines = Object.entries(timings)
|
||||
.sort(([, a], [, b]) => b.totalNs - a.totalNs);
|
||||
|
||||
for (const [line, data] of sortedLines) {
|
||||
const pct = formatPercent(data.totalNs, totalTime);
|
||||
console.log(` Line ${line}: ${pct.padStart(6)} - ${formatNs(data.avgNs)} avg`);
|
||||
}
|
||||
|
||||
// Verify expected ordering
|
||||
console.log('\nVerification:');
|
||||
const line5Time = timings[5]?.totalNs || 0; // Array allocation
|
||||
const line3Time = timings[3]?.totalNs || 0; // toString
|
||||
const line4Time = timings[4]?.totalNs || 0; // arithmetic
|
||||
|
||||
const line5Dominant = line5Time > line3Time && line5Time > line4Time;
|
||||
const line3MoreThan4 = line3Time > line4Time;
|
||||
|
||||
console.log(` Array allocation (line 5) is most expensive: ${line5Dominant ? 'YES ✓' : 'NO ✗'}`);
|
||||
console.log(` toString (line 3) more expensive than arithmetic (line 4): ${line3MoreThan4 ? 'YES ✓' : 'NO ✗'}`);
|
||||
|
||||
RESULTS.relativeAccuracy = {
|
||||
timings,
|
||||
verification: {
|
||||
arrayMostExpensive: line5Dominant,
|
||||
toStringMoreThanArithmetic: line3MoreThan4
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
// ============================================================================
|
||||
// Experiment 5: Real-World Function Analysis
|
||||
// ============================================================================
|
||||
|
||||
async function experimentRealWorld() {
|
||||
console.log('\n' + '='.repeat(70));
|
||||
console.log('EXPERIMENT 5: Real-World Function Analysis');
|
||||
console.log('='.repeat(70));
|
||||
console.log('Profile actual functions to identify optimization opportunities.\n');
|
||||
|
||||
// Profile the target functions with detailed line timings
|
||||
const instrumentedFib = customProfiler.createManuallyInstrumentedFibonacci();
|
||||
const instrumentedReverse = customProfiler.createManuallyInstrumentedReverseString();
|
||||
const instrumentedBubble = customProfiler.createManuallyInstrumentedBubbleSort();
|
||||
|
||||
customProfiler.clearTimings();
|
||||
|
||||
// Run each function multiple times
|
||||
console.log('Profiling fibonacci(40)...');
|
||||
for (let i = 0; i < 10000; i++) {
|
||||
instrumentedFib(40);
|
||||
}
|
||||
|
||||
console.log('Profiling reverseString("hello world " * 100)...');
|
||||
for (let i = 0; i < 10000; i++) {
|
||||
instrumentedReverse('hello world '.repeat(100));
|
||||
}
|
||||
|
||||
console.log('Profiling bubbleSort([100 random elements])...');
|
||||
const testArray = Array.from({ length: 100 }, () => Math.floor(Math.random() * 1000));
|
||||
for (let i = 0; i < 1000; i++) {
|
||||
instrumentedBubble(testArray);
|
||||
}
|
||||
|
||||
const allTimings = customProfiler.getTimings();
|
||||
|
||||
console.log('\n--- Profiling Results ---');
|
||||
|
||||
for (const [funcName, lines] of Object.entries(allTimings)) {
|
||||
console.log(`\n${funcName}:`);
|
||||
|
||||
let totalTime = 0;
|
||||
for (const data of Object.values(lines)) {
|
||||
totalTime += data.totalNs;
|
||||
}
|
||||
|
||||
const sortedByTime = Object.entries(lines)
|
||||
.sort(([, a], [, b]) => b.totalNs - a.totalNs);
|
||||
|
||||
console.log(' Hot spots (by total time):');
|
||||
for (const [line, data] of sortedByTime.slice(0, 5)) {
|
||||
const pct = formatPercent(data.totalNs, totalTime);
|
||||
console.log(` Line ${line.padStart(2)}: ${pct.padStart(6)} of time, ` +
|
||||
`${data.count.toString().padStart(10)} calls, ` +
|
||||
`${formatNs(data.avgNs).padStart(10)} avg`);
|
||||
}
|
||||
}
|
||||
|
||||
RESULTS.realWorld = allTimings;
|
||||
}
|
||||
|
||||
// ============================================================================
|
||||
// Main Experiment Runner
|
||||
// ============================================================================
|
||||
|
||||
async function main() {
|
||||
console.log('╔══════════════════════════════════════════════════════════════════╗');
|
||||
console.log('║ Node.js Line Profiler Experiment Suite ║');
|
||||
console.log('╚══════════════════════════════════════════════════════════════════╝');
|
||||
console.log(`\nNode.js version: ${process.version}`);
|
||||
console.log(`Platform: ${process.platform} ${process.arch}`);
|
||||
console.log(`Warmup iterations: ${WARMUP_ITERATIONS}`);
|
||||
console.log(`Measurement iterations: ${MEASUREMENT_ITERATIONS}`);
|
||||
|
||||
try {
|
||||
await experimentV8Profiler();
|
||||
} catch (err) {
|
||||
console.error('V8 Profiler experiment failed:', err);
|
||||
}
|
||||
|
||||
await experimentCustomInstrumentation();
|
||||
await experimentTimingAccuracy();
|
||||
await experimentRelativeAccuracy();
|
||||
await experimentRealWorld();
|
||||
|
||||
// Summary
|
||||
console.log('\n' + '='.repeat(70));
|
||||
console.log('SUMMARY AND RECOMMENDATIONS');
|
||||
console.log('='.repeat(70));
|
||||
|
||||
console.log('\n┌─────────────────────────────────────────────────────────────────┐');
|
||||
console.log('│ Approach Comparison │');
|
||||
console.log('├─────────────────────────────────────────────────────────────────┤');
|
||||
console.log('│ V8 Sampling Profiler │');
|
||||
console.log('│ ✓ Low overhead (~1-5%) │');
|
||||
console.log('│ ✓ No code modification required │');
|
||||
console.log('│ ✗ Sampling-based - misses fast operations │');
|
||||
console.log('│ ✗ Limited line-level granularity │');
|
||||
console.log('│ Best for: Overall hotspot identification │');
|
||||
console.log('├─────────────────────────────────────────────────────────────────┤');
|
||||
console.log('│ Custom hrtime.bigint() Instrumentation │');
|
||||
console.log('│ ✓ Precise per-line timing │');
|
||||
console.log('│ ✓ Accurate relative costs │');
|
||||
console.log('│ ✗ Significant overhead (50-500%+ depending on code) │');
|
||||
console.log('│ ✗ Requires AST transformation │');
|
||||
console.log('│ Best for: Detailed optimization analysis │');
|
||||
console.log('└─────────────────────────────────────────────────────────────────┘');
|
||||
|
||||
console.log('\n┌─────────────────────────────────────────────────────────────────┐');
|
||||
console.log('│ Key Findings │');
|
||||
console.log('├─────────────────────────────────────────────────────────────────┤');
|
||||
|
||||
if (RESULTS.timingAccuracy) {
|
||||
console.log(`│ Timer overhead: ~${formatNs(RESULTS.timingAccuracy.timerOverhead.avg).padEnd(10)} per call │`);
|
||||
console.log(`│ Timing consistency (CV): ${RESULTS.timingAccuracy.consistency.coefficientOfVariation.padEnd(10)} │`);
|
||||
}
|
||||
|
||||
if (RESULTS.customInstrumentation) {
|
||||
console.log('│ Instrumentation overhead: │');
|
||||
console.log(`│ fibonacci: ${RESULTS.customInstrumentation.overhead.fibonacci.padEnd(10)} │`);
|
||||
console.log(`│ reverseString: ${RESULTS.customInstrumentation.overhead.reverseString.padEnd(10)} │`);
|
||||
console.log(`│ bubbleSort: ${RESULTS.customInstrumentation.overhead.bubbleSort.padEnd(10)} │`);
|
||||
}
|
||||
|
||||
if (RESULTS.relativeAccuracy) {
|
||||
const { verification } = RESULTS.relativeAccuracy;
|
||||
console.log('│ Relative accuracy verification: │');
|
||||
console.log(`│ Correctly identifies expensive operations: ${verification.arrayMostExpensive ? 'YES' : 'NO '} │`);
|
||||
console.log(`│ Correctly ranks operation costs: ${verification.toStringMoreThanArithmetic ? 'YES' : 'NO '} │`);
|
||||
}
|
||||
|
||||
console.log('└─────────────────────────────────────────────────────────────────┘');
|
||||
|
||||
console.log('\n┌─────────────────────────────────────────────────────────────────┐');
|
||||
console.log('│ RECOMMENDATION FOR CODEFLASH │');
|
||||
console.log('├─────────────────────────────────────────────────────────────────┤');
|
||||
console.log('│ Use CUSTOM INSTRUMENTATION (hrtime.bigint) because: │');
|
||||
console.log('│ │');
|
||||
console.log('│ 1. Provides accurate per-line timing data │');
|
||||
console.log('│ 2. Correctly identifies hot spots and optimization targets │');
|
||||
console.log('│ 3. Overhead is acceptable for profiling runs (not production) │');
|
||||
console.log('│ 4. Already have AST infrastructure for JavaScript │');
|
||||
console.log('│ 5. Works reliably despite JIT - warmup stabilizes quickly │');
|
||||
console.log('│ │');
|
||||
console.log('│ Implementation strategy: │');
|
||||
console.log('│ - Use tree-sitter to parse and find statement boundaries │');
|
||||
console.log('│ - Insert hrtime.bigint() timing around each statement │');
|
||||
console.log('│ - Handle control flow (loops, conditionals) specially │');
|
||||
console.log('│ - Warmup for ~1000 iterations before measuring │');
|
||||
console.log('│ - Report both per-line % and absolute times │');
|
||||
console.log('└─────────────────────────────────────────────────────────────────┘');
|
||||
|
||||
// Save detailed results to file
|
||||
const fs = require('fs');
|
||||
const resultsPath = './experiment-results.json';
|
||||
fs.writeFileSync(resultsPath, JSON.stringify(RESULTS, (key, value) =>
|
||||
typeof value === 'bigint' ? value.toString() : value
|
||||
, 2));
|
||||
console.log(`\nDetailed results saved to: ${resultsPath}`);
|
||||
}
|
||||
|
||||
main().catch(console.error);
|
||||
100
experiments/js-line-profiler/target-functions.js
Normal file
100
experiments/js-line-profiler/target-functions.js
Normal file
|
|
@ -0,0 +1,100 @@
|
|||
/**
|
||||
* Target functions to profile.
|
||||
* These represent different types of code patterns we want to measure.
|
||||
*/
|
||||
|
||||
// Simple arithmetic function - good baseline
|
||||
function fibonacci(n) {
|
||||
if (n <= 1) return n;
|
||||
let a = 0;
|
||||
let b = 1;
|
||||
for (let i = 2; i <= n; i++) {
|
||||
const temp = a + b;
|
||||
a = b;
|
||||
b = temp;
|
||||
}
|
||||
return b;
|
||||
}
|
||||
|
||||
// String manipulation - common pattern
|
||||
function reverseString(str) {
|
||||
let result = '';
|
||||
for (let i = str.length - 1; i >= 0; i--) {
|
||||
result += str[i];
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
// Array operations - heap allocations
|
||||
function bubbleSort(arr) {
|
||||
const n = arr.length;
|
||||
const sorted = [...arr];
|
||||
for (let i = 0; i < n - 1; i++) {
|
||||
for (let j = 0; j < n - i - 1; j++) {
|
||||
if (sorted[j] > sorted[j + 1]) {
|
||||
const temp = sorted[j];
|
||||
sorted[j] = sorted[j + 1];
|
||||
sorted[j + 1] = temp;
|
||||
}
|
||||
}
|
||||
}
|
||||
return sorted;
|
||||
}
|
||||
|
||||
// Object manipulation
|
||||
function countWords(text) {
|
||||
const words = text.toLowerCase().split(/\s+/);
|
||||
const counts = {};
|
||||
for (const word of words) {
|
||||
if (word) {
|
||||
counts[word] = (counts[word] || 0) + 1;
|
||||
}
|
||||
}
|
||||
return counts;
|
||||
}
|
||||
|
||||
// Nested loops - demonstrates hot spots
|
||||
function matrixMultiply(a, b) {
|
||||
const rowsA = a.length;
|
||||
const colsA = a[0].length;
|
||||
const colsB = b[0].length;
|
||||
const result = [];
|
||||
|
||||
for (let i = 0; i < rowsA; i++) {
|
||||
result[i] = [];
|
||||
for (let j = 0; j < colsB; j++) {
|
||||
let sum = 0;
|
||||
for (let k = 0; k < colsA; k++) {
|
||||
sum += a[i][k] * b[k][j];
|
||||
}
|
||||
result[i][j] = sum;
|
||||
}
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
// Function with conditionals - branch coverage
|
||||
function classifyNumber(n) {
|
||||
let result = '';
|
||||
if (n < 0) {
|
||||
result = 'negative';
|
||||
} else if (n === 0) {
|
||||
result = 'zero';
|
||||
} else if (n < 10) {
|
||||
result = 'small';
|
||||
} else if (n < 100) {
|
||||
result = 'medium';
|
||||
} else {
|
||||
result = 'large';
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
fibonacci,
|
||||
reverseString,
|
||||
bubbleSort,
|
||||
countWords,
|
||||
matrixMultiply,
|
||||
classifyNumber
|
||||
};
|
||||
224
experiments/js-line-profiler/v8-inspector-profiler.js
Normal file
224
experiments/js-line-profiler/v8-inspector-profiler.js
Normal file
|
|
@ -0,0 +1,224 @@
|
|||
/**
|
||||
* V8 Inspector-based Profiler
|
||||
*
|
||||
* Uses the built-in V8 inspector protocol to collect CPU profiling data.
|
||||
* This is the same mechanism used by Chrome DevTools.
|
||||
*/
|
||||
|
||||
const inspector = require('inspector');
|
||||
const session = new inspector.Session();
|
||||
|
||||
let isSessionConnected = false;
|
||||
|
||||
/**
|
||||
* Start the profiler.
|
||||
*/
|
||||
async function startProfiling() {
|
||||
if (!isSessionConnected) {
|
||||
session.connect();
|
||||
isSessionConnected = true;
|
||||
}
|
||||
|
||||
return new Promise((resolve, reject) => {
|
||||
session.post('Profiler.enable', (err) => {
|
||||
if (err) return reject(err);
|
||||
|
||||
session.post('Profiler.setSamplingInterval', { interval: 100 }, (err) => {
|
||||
if (err) return reject(err);
|
||||
|
||||
session.post('Profiler.start', (err) => {
|
||||
if (err) return reject(err);
|
||||
resolve();
|
||||
});
|
||||
});
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Stop the profiler and get the profile data.
|
||||
*/
|
||||
async function stopProfiling() {
|
||||
return new Promise((resolve, reject) => {
|
||||
session.post('Profiler.stop', (err, { profile }) => {
|
||||
if (err) return reject(err);
|
||||
resolve(profile);
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Parse the V8 profile to extract line-level timings.
|
||||
*/
|
||||
function parseProfile(profile) {
|
||||
const lineTimings = {};
|
||||
|
||||
// Build a map of node IDs to their hit counts
|
||||
const nodeHits = {};
|
||||
for (const sample of profile.samples || []) {
|
||||
nodeHits[sample] = (nodeHits[sample] || 0) + 1;
|
||||
}
|
||||
|
||||
// Process nodes to extract line information
|
||||
function processNode(node, parentHits = 0) {
|
||||
const { callFrame } = node;
|
||||
const filename = callFrame.url || callFrame.scriptId;
|
||||
const lineNumber = callFrame.lineNumber + 1; // V8 uses 0-indexed lines
|
||||
const functionName = callFrame.functionName || '(anonymous)';
|
||||
|
||||
const hits = nodeHits[node.id] || 0;
|
||||
|
||||
if (filename && lineNumber > 0) {
|
||||
if (!lineTimings[filename]) {
|
||||
lineTimings[filename] = {};
|
||||
}
|
||||
if (!lineTimings[filename][lineNumber]) {
|
||||
lineTimings[filename][lineNumber] = {
|
||||
hits: 0,
|
||||
functionName,
|
||||
selfTime: 0
|
||||
};
|
||||
}
|
||||
lineTimings[filename][lineNumber].hits += hits;
|
||||
}
|
||||
|
||||
// Process children
|
||||
if (node.children) {
|
||||
for (const childId of node.children) {
|
||||
const childNode = findNode(profile.nodes, childId);
|
||||
if (childNode) {
|
||||
processNode(childNode, hits);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
function findNode(nodes, id) {
|
||||
return nodes.find(n => n.id === id);
|
||||
}
|
||||
|
||||
// Start from the root
|
||||
if (profile.nodes && profile.nodes.length > 0) {
|
||||
processNode(profile.nodes[0]);
|
||||
}
|
||||
|
||||
// Calculate percentages
|
||||
const totalSamples = profile.samples?.length || 1;
|
||||
for (const filename of Object.keys(lineTimings)) {
|
||||
for (const line of Object.keys(lineTimings[filename])) {
|
||||
const data = lineTimings[filename][line];
|
||||
data.percentage = (data.hits / totalSamples * 100).toFixed(2);
|
||||
}
|
||||
}
|
||||
|
||||
return lineTimings;
|
||||
}
|
||||
|
||||
/**
|
||||
* Alternative: Use precise CPU profiling with tick processor.
|
||||
*/
|
||||
async function startPreciseProfiling() {
|
||||
if (!isSessionConnected) {
|
||||
session.connect();
|
||||
isSessionConnected = true;
|
||||
}
|
||||
|
||||
return new Promise((resolve, reject) => {
|
||||
session.post('Profiler.enable', (err) => {
|
||||
if (err) return reject(err);
|
||||
|
||||
// Use microsecond precision
|
||||
session.post('Profiler.setSamplingInterval', { interval: 10 }, (err) => {
|
||||
if (err) return reject(err);
|
||||
|
||||
// Enable precise coverage if available
|
||||
session.post('Profiler.startPreciseCoverage', {
|
||||
callCount: true,
|
||||
detailed: true
|
||||
}, (err) => {
|
||||
// Ignore error if not supported
|
||||
session.post('Profiler.start', (err) => {
|
||||
if (err) return reject(err);
|
||||
resolve();
|
||||
});
|
||||
});
|
||||
});
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Stop precise profiling and get coverage data.
|
||||
*/
|
||||
async function stopPreciseProfiling() {
|
||||
return new Promise((resolve, reject) => {
|
||||
// Get precise coverage
|
||||
session.post('Profiler.takePreciseCoverage', (coverageErr, coverageResult) => {
|
||||
// Get regular profile
|
||||
session.post('Profiler.stop', (err, { profile }) => {
|
||||
if (err) return reject(err);
|
||||
resolve({
|
||||
profile,
|
||||
coverage: coverageResult?.result || []
|
||||
});
|
||||
});
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Parse coverage data for line-level information.
|
||||
*/
|
||||
function parseCoverage(coverage) {
|
||||
const lineTimings = {};
|
||||
|
||||
for (const script of coverage) {
|
||||
const scriptId = script.scriptId;
|
||||
const url = script.url;
|
||||
|
||||
for (const func of script.functions) {
|
||||
const funcName = func.functionName || '(anonymous)';
|
||||
|
||||
for (const range of func.ranges) {
|
||||
const startLine = range.startOffset; // Note: these are byte offsets
|
||||
const endLine = range.endOffset;
|
||||
const count = range.count;
|
||||
|
||||
if (!lineTimings[url]) {
|
||||
lineTimings[url] = {};
|
||||
}
|
||||
// For simplicity, use offset as key (would need source map for lines)
|
||||
const key = `offset:${startLine}-${endLine}`;
|
||||
lineTimings[url][key] = {
|
||||
functionName: funcName,
|
||||
count,
|
||||
startOffset: startLine,
|
||||
endOffset: endLine
|
||||
};
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return lineTimings;
|
||||
}
|
||||
|
||||
/**
|
||||
* Disconnect the session.
|
||||
*/
|
||||
function disconnect() {
|
||||
if (isSessionConnected) {
|
||||
session.post('Profiler.disable', () => {});
|
||||
session.disconnect();
|
||||
isSessionConnected = false;
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
startProfiling,
|
||||
stopProfiling,
|
||||
parseProfile,
|
||||
startPreciseProfiling,
|
||||
stopPreciseProfiling,
|
||||
parseCoverage,
|
||||
disconnect
|
||||
};
|
||||
Loading…
Reference in a new issue