Studying the Interplay Between the Durations and Breakages of Continuous Integration Builds
Notice bibliographique
Résumé
The Continuous Integration (CI) practice allows developers to build software projects automatically and more frequently. However, CI builds may undergo long build durations or frequent build breakages, which we refer to asbuild performance. Both long durations and frequent breakages of CI builds can impede developers from engaging in other development activities. Prior research has conducted independent studies on build durations or build breakages. However, there is little attention to the possible interplay between reducing build durations and build breakages. In particular, it is unclear from prior studies (i) whether and how build performance is influenced by the context of projects; (ii) whether the actions to reduce build durations would reduce or increase build breakages; and (iii) whether fixing build breakages would lead to longer or faster builds. It is important for developers to understand the practices that make both timely and passing CI builds. In this paper, we conduct experimental and survey studies on the practices that can have dual or inverse associations with twobuild performancemeasures:build durationsandbuild breakages. To this end, we extend an existing dataset calledTravisTorrentto exclude inactive projects and collect recent builds of active projects. As a result, we study 924,616 CI builds from 588GitHubprojects that are linked withTravis CI. In addition, we survey developers who contributed to the projects in our dataset to get their feedback on our experimental observations. First, we investigate project-level metrics and find that project characteristics have a significant association with build durations and breakages. In addition, we investigate how build-level metrics are associated with both build durations and breakages and observe an evident interplay between them. In particular, we observe that actions to fix build breakages (e.g., retrying or waiting for build commands) not only increase build durations but also do not guarantee passing builds. We also find that improving the build performance of a project is dependent on the current build durations and breakages of that project. Furthermore, we analyze how build performance changes over time and observe nearly a third of projects in which one performance measure is sacrificed in favor of the other, especially when not possible to achieve both together. The majority of our experimental observations are confirmed by survey results, which provide useful insights though some survey responses disagree with some of our experimental observations. Our work (a) provides developers with development and building practices to maintain timely and passing CI builds, and (b) encourages researchers to highlight any potential dual or inverse side effects when reporting actionable findings about CI builds.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,014 | 0,131 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».