benchmarking

Measure Go function performance with the testing package and benchstat.

1|Updated Mar 5, 2026

Search Tags:#performance #optimization #benchmarking #golang #go #profiling

Ready to run

npx skills add https://github.com/baphled/dotopencode --skill benchmarking-baphled

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: benchmarking
Source: https://github.com/baphled/dotopencode/tree/main/skills/benchmarking
Command: npx skills add https://github.com/baphled/dotopencode --skill benchmarking-baphled

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps developers measure and optimize the performance of their Go code by providing tools and techniques for writing reliable benchmarks.

Core Features & Use Cases

Performance Measurement: Accurately measure the execution time and memory allocations of Go functions.
Optimization Verification: Verify the impact of code optimizations by comparing benchmark results before and after changes.
Bottleneck Identification: Identify performance hotspots in critical code paths.
Use Case: When you've refactored a critical function and want to ensure your changes have actually improved performance without introducing regressions, use this skill to benchmark the new implementation against the old one.

Quick Start

Use the benchmarking skill to run a benchmark for the ProcessData function in the current Go package.

Frequently Asked Questions about benchmarking

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I write reliable benchmarks in Go to measure code performance?▼

To write reliable Go benchmarks, use the `testing` package and isolate execution with `b.ResetTimer()`. Track memory allocations using `b.ReportAllocs()` and supply realistic data inputs to accurately measure execution time.

What is the best way to compare Go benchmark results after refactoring?▼

Compare Go benchmark results after refactoring by analyzing outputs with `benchstat` to verify statistical significance. This confirms your code optimizations improved performance and introduced no regressions in critical paths.

How does b.ReportAllocs() work when benchmarking Go functions?▼

The `b.ReportAllocs()` function works by enabling memory allocation reporting during Go benchmarking. It reveals memory hotspots alongside execution time, helping you identify bottlenecks and verify optimization impacts accurately.

When do I need to use benchstat for Go performance optimization?▼

You need `benchstat` for Go performance optimization when comparing benchmark results before and after code changes. It calculates statistical significance, ensuring observed execution time differences are reliable rather than random variance.

Can I identify bottlenecks in critical Go code paths using the testing package?▼

Yes, you can identify bottlenecks in critical Go code paths using the `testing` package. By running targeted benchmarks with realistic data inputs, you isolate performance hotspots and measure their execution time.

Why do my Go benchmark results vary and how can I make them reliable?▼

Go benchmark results vary due to setup overhead and inconsistent inputs. Make them reliable by calling `b.ResetTimer()` to exclude initialization, using realistic data inputs, and verifying statistical significance with `benchstat`.