Detecting Continuous Integration Skip Commits Using Multi-Objective Evolutionary Search

Islem Saidani

doi:10.1109/TSE.2021.3129165

Return

Detecting Continuous Integration Skip Commits Using Multi-Objective Evolutionary Search

2022-12-01

PRE

Islem Saidani

Ali Ouni *

Mohamed Wiem Mkaouer

DOI：10.1109/TSE.2021.3129165

Original

Original request for help

Save

Abstract

En 中文

Continuous Integration (CI) consists of integrating the changes introduced by different developers more frequently through the automation of build process. Nevertheless, the CI build process is seen as a major barrier that causes delays in the product release dates. One of the main reasons for such delays is that some simple changes (i.e., can be skipped) trigger the build, which represents an unnecessary overhead and particularly painful for large projects. In order to cut off the expenses of CI build time, we propose in this paper, SkipCI, a novel search-based approach to automatically detect CI Skip commits based on the adaptation of Strength-Pareto Evolutionary Algorithm (SPEA-2). Our approach aims to provide the optimal trade-off between two conflicting objectives to deal with both skipped and non-skipped commits. We evaluate our approach and investigate the performance of both within and cross-project validations on a benchmark of 14,294 CI commits from 15 projects that use Travis CI system. The statistical tests revealed that our approach shows a clear advantage over the baseline approaches with average scores of 92% and 84% in terms of AUC for cross-validation and cross-project validations respectively. Furthermore, the features analysis reveals that documentation changes, terms appearing in the commit message and the committer experience are the most prominent features in CI skip detection. When it comes to the cross-project scenario, the results reveal that besides the documentation changes, there is a strong link between current and previous commits results. Moreover, we deployed and evaluated the usefulness of SkipCI with our industrial partner. Qualitative results demonstrate the effectiveness of SkipCI in providing relevant CI skip commit recommendations to developers for two large software projects from practitioner's point of view.

Keywords:

Continuous integration

travis CI

software build

search-based software engineering

genetic programming