Studying the Interplay Between the Durations and Breakages of Continuous Integration Builds
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
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 as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">build performance</i> . 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 two <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">build performance</i> measures: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">build durations</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">build breakages</i> . To this end, we extend an existing dataset called <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TravisTorrent</small> to exclude inactive projects and collect recent builds of active projects. As a result, we study 924,616 CI builds from 588 <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">GitHub</small> projects that are linked with <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Travis CI</small> . 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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it