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P2 ECSTATIC: Automatic Configuration-Aware Testing and Debugging of Static Analysis Tools

ECSTATIC:静态分析工具的自动配置感知测试与调试
ISSTA Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis2023匹配度 3/10 · 该论文研究静态分析工具的配置感知测试与调试,属于静态分析工程与调试方向,但完全不涉及 LLM/Agent、浮点程序分析或贝叶斯程序分析,也未利用 LLM 改进静态分析,因此与用户画像的核心交叉方向不匹配,仅与静态分析工具有边缘关联。引用 2 inbox
Austin Mordahl, Dakota Soles, Miao Miao, Zenong Zhang, Shiyi Wei
crossref: 2026-09-12

AI 速览

一句话:提出配置感知的静态分析器自动化测试与调试工具 ECSTATIC,利用配置偏序关系发现 74 个缺陷并高效归约程序。

静态分析工具通常提供大量配置选项以保证通用性,但这使测试与调试更困难。ECSTATIC 利用分析配置选项之间的偏序关系,在无需 ground truth 的情况下自动测试和调试静态分析器;其运行于 Docker 容器中保证可复现,并提供扩展接口以加入新工具与输入程序。作者在四个流行的数据流分析工具上评估,共发现 74 个缺陷;其新颖的两阶段 delta debugging 能将真实程序缩减约 50%,而基线仅 6%。

问题
静态分析工具可配置,配置空间大且缺少 ground truth,导致自动化测试与调试困难。
方法
利用配置选项间偏序关系生成和比较测试、检测不一致,并在 Docker 中保证可复现,提供扩展接口,采用两阶段 delta debugging 缩减程序。
评估
在四个流行数据流分析工具上评估,发现 74 个缺陷;两阶段 delta debugging 将真实程序缩减 50%,基线为 6%。
原文摘要(Abstract)

Static analyses are powerful tools that can serve as a complement to dynamic approaches such as testing. In order to ensure generality, many static analysis tools are configurable. However, these configurations can make testing and debugging more difficult. To address this issue, we introduce a new tool, ECSTATIC, which leverages partial order relations between analysis configuration options to automatically test and debug static analyzers, even without ground truths. ECSTATIC’s results are reproducible by virtue of running within Docker containers, and ECSTATIC provides clear extension interfaces for users to add their own tools and input programs. We evaluated ECSTATIC on four popular dataflow analysis tools, and found 74 bugs in all four tools. We also found that ECSTATIC’s novel two-staged delta debugging was able to reduce real-world programs by 50%, compared to a baseline of 6%.

链接与引用

DOI 原文 · PDF(开放获取) ·

BibTeX
@inproceedings{paperbot8054,
  title = {ECSTATIC: Automatic Configuration-Aware Testing and Debugging of Static Analysis Tools},
  author = {Austin Mordahl and Dakota Soles and Miao Miao and Zenong Zhang and Shiyi Wei},
  booktitle = {ISSTA},
  year = {2023},
  doi = {10.1145/3597926.3604918}
}