EvidenT: An Evidence-Preserving Framework for Iterative System-Level Package Repair
Chenyu Zhao, Minghua Ma, Shenglin Zhang, Zeshun Huang, Yongqian Sun, Chetan Bansal, Saravan Rajmohan, Dan Pei

TL;DR
EvidenT is a framework that improves system-level package repair by systematically managing evidence, leveraging external build services, and iteratively validating repairs, significantly outperforming existing methods.
Contribution
The paper introduces EvidenT, a novel evidence-preserving, iterative repair framework that effectively handles complex system-level build failures across diverse architectures.
Findings
EvidenT repairs 53.88% of real-world failures, outperforming baselines.
72% of failures are due to dependency and environment issues.
Preliminary results show robustness across different hardware architectures.
Abstract
Frequent toolchain updates and growing ISA diversity have made system-level software package repair increasingly important. Diagnosing and repairing build failures remains challenging because failures involve heterogeneous evidence, dependency constraints, and architecture-specific build conventions. While recent LLM-based repair methods show promise for project-level source fixes, they struggle with system-level repair, where failures span multi-language artifacts such as build recipes, scripts, and source archives, and require iterative validation through external build services. In this paper, we first conduct a systematic empirical study of real-world system-level build failures. We find that 72% of failures stem from dependency and environment misconfigurations rather than isolated code defects, suggesting that effective repair must prioritize packaging logic and iterative…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
