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Contribution Details
| Type | Conference or Workshop Paper |
| Scope | Contributions to practice |
| Published in Proceedings | Yes |
| Title | Configuration Smells in Continuous Delivery Pipelines: A Linter and a Six-Month Study on GitLab |
| Organization Unit | |
| Authors |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Page Range | 327 - 337 |
| Event Title | ESEC/FSE '20: 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering |
| Event Type | conference |
| Event Location | Virtual Event, USA |
| Event Start Date | November 8 - 2020 |
| Event End Date | November 13 - 2020 |
| Place of Publication | New York, United States |
| Publisher | ACM |
| Abstract Text | An effective and efficient application of Continuous Integration (CI) and Delivery (CD) requires software projects to follow certain principles and good practices. Configuring such a CI/CD pipeline is challenging and error-prone. Therefore, automated linters have been proposed to detect errors in the pipeline. While existing linters identify syntactic errors, detect security vulnerabilities or misuse of the features provided by build servers, they do not support developers that want to prevent common misconfigurations of a CD pipeline that potentially violate CD principles (“CD smells”). To this end, we propose CD-Linter, a semantic linter that can automatically identify four different smells in pipeline configuration files. We have evaluated our approach through a large-scale and long-term study that consists of (i) monitoring 145 issues (opened in as many open-source projects) over a period of 6 months, (ii) manually validating the detection precision and recall on a representative sample of issues, and (iii) assessing the magnitude of the observed smells on 5,312 open-source projects on GitLab. Our results show that CD smells are accepted and fixed by most of the developers and our linter achieves a precision of 87% and a recall of 94%. Those smells can be frequently observed in the wild, as 31% of projects with long configurations are affected by at least one smell. |
| Related URLs | |
| Digital Object Identifier | 10.1145/3368089.3409709 |
| Other Identification Number | merlin-id:20339 |
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