---

name: benchmark-common description: Benchmarking skill for comparing multiple implementations. Creates comprehensive performance comparisons with proper methodology. Use when asked to benchmark or compare performance of different approaches.

Benchmark Common Skill

This skill provides comprehensive benchmarking standards for performance comparison. Designed to compare multiple implementations in a single benchmark file.

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When to Use

• Compare different implementations (e.g., RingBuffer vs LinkedListBuffer)
• Measure performance of Common packages
• Validate optimization effectiveness
• Find performance bottlenecks

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Quality Standards

Metric	Requirement
Warm-up	Reset state between iterations
Fair Comparison	Same data sizes, same conditions
Multiple Sizes	Test small, medium, large data
Memory Reporting	Use b.ReportAllocs()
Clear Naming	BenchmarkOperation_Implementation_Size

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Workflow (Strict 3-Step Process)

Step 1: Benchmark Design

Identify:

1. Implementations to compare: List all types/approaches
2. Operations to benchmark: Core operations (Read, Write, etc.)
3. Data sizes: Small (64B), Medium (1KB), Large (1MB)
4. Setup requirements: Pre-allocation, warm-up needs

Output Format:

## Benchmark Design: [comparison name]

### Implementations
- [Implementation 1]: Description
- [Implementation 2]: Description

### Operations
| Operation | Description | Why benchmark? |
|-----------|-------------|----------------|
| Write | Append data | Core operation |
| Read | Consume data | Core operation |

### Data Sizes
- Small: 64 bytes (cache-friendly)
- Medium: 1KB (typical payload)
- Large: 1MB (stress test)

STOP and wait for user approval.

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Step 2: Benchmark Case Design

Create benchmark matrix:

Benchmark ID	Operation	Implementation	Size	Setup
B1.1	Write	RingBuffer	64B	New(1024)
B1.2	Write	LinkedListBuffer	64B	New()
B2.1	Write	RingBuffer	1KB	New(4096)
B2.2	Write	LinkedListBuffer	1KB	New()

Considerations:

• Same data for all implementations
• Pre-allocate to avoid setup cost in measurement
• Reset between iterations
• Report memory allocations

STOP and wait for user approval.

---

Step 3: Benchmark Code Implementation

Follow these Go benchmarking standards:

File Structure

benchmark_comparison_test.go
├── // Data generators
│   var smallData = make([]byte, 64)
│   var mediumData = make([]byte, 1024)
│   var largeData = make([]byte, 1<<20)
│
├── // Comparison benchmarks (grouped by operation)
│   func BenchmarkWrite(b *testing.B)
│   ├── b.Run("RingBuffer/64B", ...)
│   ├── b.Run("RingBuffer/1KB", ...)
│   ├── b.Run("LinkedList/64B", ...)
│   └── b.Run("LinkedList/1KB", ...)
│
├── func BenchmarkRead(b *testing.B)
│   ├── b.Run("RingBuffer/64B", ...)
│   └── ...

Code Patterns

Comparison Benchmark (Grouped by Operation):

func BenchmarkWrite(b *testing.B) {
    sizes := []struct {
        name string
        data []byte
    }{
        {"64B", make([]byte, 64)},
        {"1KB", make([]byte, 1024)},
        {"1MB", make([]byte, 1<<20)},
    }

    for _, size := range sizes {
        // RingBuffer
        b.Run("RingBuffer/"+size.name, func(b *testing.B) {
            buf := NewRing(len(size.data) * 2)
            b.ResetTimer()
            b.ReportAllocs()
            for i := 0; i < b.N; i++ {
                buf.Write(size.data)
                buf.Reset()
            }
        })

        // LinkedListBuffer
        b.Run("LinkedList/"+size.name, func(b *testing.B) {
            buf := &LinkedListBuffer{}
            b.ResetTimer()
            b.ReportAllocs()
            for i := 0; i < b.N; i++ {
                buf.PushBack(size.data)
                buf.Reset()
            }
        })
    }
}

Read After Write Pattern:

func BenchmarkRead(b *testing.B) {
    data := make([]byte, 1024)
    readBuf := make([]byte, 1024)

    b.Run("RingBuffer", func(b *testing.B) {
        buf := NewRing(2048)
        b.ResetTimer()
        b.ReportAllocs()
        for i := 0; i < b.N; i++ {
            buf.Write(data)
            buf.Read(readBuf)
        }
    })

    b.Run("LinkedList", func(b *testing.B) {
        buf := &LinkedListBuffer{}
        b.ResetTimer()
        b.ReportAllocs()
        for i := 0; i < b.N; i++ {
            buf.PushBack(data)
            buf.Read(readBuf)
        }
    })
}

Memory-Heavy Benchmark:

func BenchmarkMemory(b *testing.B) {
    b.Run("RingBuffer/Grow", func(b *testing.B) {
        b.ReportAllocs()
        for i := 0; i < b.N; i++ {
            buf := NewRing(64)
            for j := 0; j < 1000; j++ {
                buf.Write(make([]byte, 100))
            }
        }
    })
}

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Running Benchmarks

# Run all benchmarks
go test -bench=. -benchmem

# Run specific comparison
go test -bench=BenchmarkWrite -benchmem

# Run with count for stability
go test -bench=. -benchmem -count=5

# Compare with benchstat
go test -bench=. -benchmem -count=10 > old.txt
# (make changes)
go test -bench=. -benchmem -count=10 > new.txt
benchstat old.txt new.txt

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Output Interpretation

BenchmarkWrite/RingBuffer/64B-8    10000000    120 ns/op    0 B/op    0 allocs/op
BenchmarkWrite/LinkedList/64B-8    5000000     250 ns/op    64 B/op   1 allocs/op

Column	Meaning
-8	GOMAXPROCS (8 cores)
10000000	Iterations run
120 ns/op	Time per operation
0 B/op	Bytes allocated per op
0 allocs/op	Allocations per op

Interpretation: RingBuffer ~2x faster, no allocations.

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Rules (Non-negotiable)

1. Always use b.ResetTimer() after setup code
2. Always use b.ReportAllocs() for memory analysis
3. Same data sizes for fair comparison
4. Reset state between iterations
5. Clear naming convention: Operation/Implementation/Size
6. Run multiple times for stable results

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Best Practices

Practice	Why
Pre-allocate data outside loop	Avoid measurement pollution
Use b.StopTimer() / b.StartTimer()	Exclude setup from measurement
Reset buffers after write	Simulate real usage pattern
Test multiple sizes	Find performance characteristics
Run -count=10	Statistical stability

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Approval Prompt

After each step, ask:

"Please review the above and confirm if I should proceed to the next step."