Temporal Analysis and Repair of Flaky Dockerfiles
<|reference_start|>Temporal Analysis and Repair of Flaky Dockerfiles: Dockerfile flakiness, characterized by inconsistent build behavior without Dockerfile or project source code changes, poses significant challenges in Continuous Integration and Delivery (CI/CD) pipelines. This issue can lead to unreliable deployments and increased debugging efforts, yet it remains underexplored in current research. We conduct a systematic analysis of Dockerfile flakiness, presenting a comprehensive taxonomy of common flakiness categories, including dependency-related errors and server connectivity issues. Furthermore, we introduce FlakiDock, a tool leveraging large language models and retrieval-augmented generation techniques with dynamic analysis and an iterative feedback loop to automatically repair flaky Dockerfiles. Our evaluation shows that FlakiDock achieves a 73.55% repair accuracy, outperforming existing tools such as PARFUM by 12,581% and GPT-4-based prompting by 94.63%. These results underscore the effectiveness of FlakiDock in addressing Dockerfile flakiness and improving build reliability.<|reference_end|>
@article{shabani2024temporal,
    title={Temporal Analysis and Repair of Flaky Dockerfiles},
    author={Taha Shabani, Noor Nashid, Parsa Alian, Ali Mesbah},
    journal={arXiv preprint arXiv:2408.05379},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.05379},
    primaryClass={cs.SE}
}