$\mu$OpTime: Statically Reducing the Execution Time of Microbenchmark Suites Using Stability Metrics

TL;DR

$OpTime is a static method that reduces microbenchmark suite execution time by determining the minimal number of repetitions needed for accurate results, enabling faster performance regression detection in CI/CD pipelines.

Contribution

It introduces a static approach using stability metrics to optimize microbenchmark repetitions, significantly decreasing execution time while maintaining accuracy.

Findings

Up to 95.83% reduction in execution time for Go projects.

Effective regression detection with reduced measurement phases.

Stability metric choice varies with project and language.

Abstract

Performance regressions have a tremendous impact on the quality of software. One way to catch regressions before they reach production is executing performance tests before deployment, e.g., using microbenchmarks, which measure performance at subroutine level. In projects with many microbenchmarks, this may take several hours due to repeated execution to get accurate results, disqualifying them from frequent use in CI/CD pipelines. We propose $\mu$OpTime, a static approach to reduce the execution time of microbenchmark suites by configuring the number of repetitions for each microbenchmark. Based on the results of a full, previous microbenchmark suite run, $\mu$OpTime determines the minimal number of (measurement) repetitions with statistical stability metrics that still lead to accurate results. We evaluate $\mu$OpTime with an experimental study on 14 open-source projects written in two programming languages and five stability metrics. Our results show that (i) $\mu$OpTime reduces the total suite execution time (measurement phase) by up to 95.83% (Go) and 94.17% (Java), (ii) the choice of stability metric depends on the project and programming language, (iii) microbenchmark warmup phases have to be considered for Java projects (potentially leading to higher reductions), and (iv) $\mu$OpTime can be used to reliably detect performance regressions in CI/CD pipelines.