Name
Abstract | ||
|---|---|---|
ABSTRACTContinuous Integration (CI) aims at supporting developers in inte-grating code changes quickly through automated building. How-ever, there is a consensus that CI build failure is a major barrierthat developers face, which prevents them from proceeding furtherwith development. In this paper, we introduceBF-Detector, anautomated tool to detect CI build failure. Based on the adaptationof Non-dominated Sorting Genetic Algorithm (NSGA-II), our toolaims at finding the best prediction rules based on two conflictingobjective functions to deal with both minority and majority classes.We evaluated the effectiveness of our tool on a benchmark of 56,019CI builds. The results reveal that our technique outperforms state-of-the-art approaches by providing a better balance between bothfailed and passed builds.BF-Detectortool is publicly available,with a demo video, at: https://github.com/stilab-ets/BF-Detector. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3468264.3473115 | Foundations of Software Engineering |
Keywords | DocType | Citations |
Continuous Integration, Build Prediction, Multi-Objective Optimization, Search-Based Software Engineering, Machine Learning | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Islem Saidani | 1 | 4 | 3.09 |
| Ali Ouni 0001 | 2 | 210 | 15.67 |
| Moataz Chouchen | 3 | 7 | 2.84 |
| Mohamed Wiem Mkaouer | 4 | 228 | 28.58 |