Bench-node is a powerful Node.js module specifically designed for micro-benchmarking JavaScript code blocks, accurately measuring operations per second (ops/sec). Its current stable version is 0.14.0, and it maintains an active development pace with frequent minor releases every few weeks to months, indicating robust maintenance. A primary differentiator of `bench-node` is its explicit use of V8 deoptimization (via `%NeverOptimizeFunction`) to ensure that benchmarked code is not aggressively optimized away by the V8 engine. While this approach yields highly stable and reproducible results for micro-benchmarks, users should be aware that these "accurate" measurements might not perfectly reflect "realistic" performance in a fully optimized production environment. To further assist developers, the library includes an opt-in Dead Code Elimination (DCE) detection plugin that warns if benchmarked code is being optimized out, although enabling it disables V8 deoptimization. Additionally, `bench-node` offers statistical significance testing (Welch's t-test) to evaluate if observed performance differences are statistically meaningful, a crucial feature for benchmarking in high-variance environments. It provides a rich set of built-in reporters (text, chart, HTML, JSON, CSV, pretty) for result visualization and ships with TypeScript types for enhanced developer experience. Other features include support for setup/teardown routines, execution in worker threads for isolation, and both operations and time-based benchmarking modes.
npm install bench-nodeVerified import paths — ran on the pinned version, not inferred.
This example demonstrates how to set up a `Suite` with a custom reporter, add multiple benchmarks, and run them. It compares different array population methods and explicitly uses the result to prevent dead code elimination.
Always interpret microbenchmark results with caution. For real-world performance assessments, consider profiling under production-like conditions or using macro-benchmarks that allow V8 to optimize code naturally.
Ensure that the results of your benchmarked operations are always used, for example, by returning them, asserting against them, or logging them, to prevent V8 from eliminating the code. Refer to the 'Dead Code Elimination Detection' section in the documentation for specific patterns to avoid.
Review existing code that directly invokes reporter functions. If you were relying on implicit stdout printing, adapt your code to use the new `to<Format>()` methods or pass the reporter to the `Suite` options directly.
Isolate resource-intensive setup logic outside the timed block by performing it before `suite.add()`, or carefully consider if manual timing is truly necessary and understand its implications.
Be aware of the increased execution time when enabling `ttest: true`. Adjust `repeatSuite` manually if fewer repetitions are acceptable for preliminary analysis, or ensure your CI/CD pipeline can accommodate longer runtimes for statistically robust comparisons.
Ensure the benchmarked function's result is used or has observable side effects. For example, assign the result to a variable that is then used in a conditional `if (result !== expected) throw new Error('Unexpected');` or return the result from the benchmark function. Enable `detectDeadCodeElimination` in suite options to get these warnings.If using ES Modules, ensure you're using `import { Suite } from 'bench-node';`. If in a CommonJS environment, use `const { Suite } = require('bench-node');` to correctly destructure the named export. Ensure your build configuration (e.g., TypeScript, Babel) handles module interop correctly.Modify your benchmark code to ensure that the operations performed have a visible effect or that their results are consumed. For instance, return the result, store it in an external variable (if not part of the timed operation), or perform a simple check like `if (result === undefined) throw new Error();`. Using the `detectDeadCodeElimination` option can help identify such cases.
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