Conference
NearDuplicate Build Failure Detection from Continuous Integration Logs
| Title: | NearDuplicate Build Failure Detection from Continuous Integration Logs |
|---|---|
| Authors: | Mäntylä, Mika Viking, Nyyssölä, Jesse Aleksi, Luukkainen, Matti Juhani |
| Contributors: | Department of Computer Science, Teachers' Academy, RAGE - Agile Education Research group / Matti Luukkainen |
| Publication Year: | 2025 |
| Collection: | Helsingfors Universitet: HELDA – Helsingin yliopiston digitaalinen arkisto |
| Subject Terms: | Software Testing and Debugging Techniques, Computer and information sciences |
| Description: | Addressing build failures is important in software development, particularly within Continuous Integration and Deployment (CI/CD) pipelines. A common issue arises when a developer encounters a newbuild failure that has occurred in the past. We refer to such build failures as near-duplicate build failures. We collect build logs from a GitHub Actions CI/CD pipeline. We label near-duplicate build failures by identifying those that have the same failed tests. We propose a framework for detecting near-duplicate build failures through log similarity analysis. As the majority of log lines in failed builds are similar to passing logs, we propose using an Out-of-Vocabulary Detector (OOVD) filtering to identify only failure-relevant lines and to improve near-duplicate detection accuracy. Our results suggest a noticeable improvement using OOVD filtering across all metrics for Top-K results (K = 5, precision@K: 0.864 vs. 0.526 and MAP@K: 0.941 vs. 0.814). Finding near-duplicate build failures can be an important software engineering challenge that, to the best of our knowledge, has not been studied in the past. ; Peer reviewed |
| Document Type: | conference object |
| File Description: | application/pdf |
| Language: | English |
| ISBN: | 979-84-00-71594-5 |
| Relation: | PROMISE '25: Proceedings of the 21st International Conference on Predictive Models and Data Analytics in Software Engineering; 979-8-4007-1594-5; This work is funded by the Research Council of Finland (Decision No. 359861) under the academic project MuFAno. The authors acknowledge the CSC-IT Center for Science, Finland, for providing computational resources.; conference; https://hdl.handle.net/10138/602621; 105012243010; 001543698200005 |
| Availability: | https://hdl.handle.net/10138/602621 |
| Rights: | cc_by ; info:eu-repo/semantics/openAccess ; openAccess |
| Accession Number: | edsbas.5704A89D |
| Database: | BASE |
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