bheisler/criterion.rs

Statistics-driven benchmarking library for Rust

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Summary Information

Updated 56 minutes ago
Added to GitGenius on September 12th, 2026
Created on May 26th, 2014
Open Issues & Pull Requests: 223 (+0)
GitHub issues: Enabled
Number of forks: 359
Total Stargazers: 5,528 (+0)
Total Subscribers: 26 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 28.5 days
Mean response time: 211.8 days
90th percentile: 599.8 days
Tracked items: 51

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 100% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Only 0% of issues opened in the past year have been closed. Three people close 57% of everything that gets resolved.

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Issue Activity (beta)

Open issues: 71
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 765 days
Stale 30+ days: 71
Stale 90+ days: 70

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • Enhancement (1)

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Detailed Description

Criterion.rs is a statistics-driven benchmarking library for Rust that automates the collection and analysis of microbenchmark measurements.

The library solves the problem of unreliable benchmark results by applying statistical methods to distinguish genuine performance differences from noise. It collects multiple samples from each benchmark run, performs statistical analysis to detect outliers and compute confidence intervals, and generates detailed reports showing how performance changes across runs. This approach eliminates the guesswork from interpreting benchmark data and makes it easier to catch real regressions.

Criterion.rs suits projects where performance matters and developers need confidence that optimizations actually work. It integrates into Rust's built-in test framework, making it straightforward to add to existing codebases. The library generates both textual summaries and graphical plots to visualize performance trends, which helps when communicating results to teammates or tracking changes over time. Teams working on performance-critical systems, libraries, or applications where even small regressions matter will find the statistical rigor particularly valuable compared to running benchmarks once and eyeballing the numbers.

Development of the tool has transitioned to a dedicated organization to ensure continuity and active maintenance. The project maintains a backlog of pending contributions and is working through accumulated pull requests to bring the codebase current.