Root cause localization for unreproducible builds via causality analysis over system call tracing

Zhilei Ren, Changlin Liu, Xusheng Xiao, He Jiang, Tao Xie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Localization of the root causes for unreproducible builds during software maintenance is an important yet challenging task, primarily due to limited runtime traces from build processes and high diversity of build environments. To address these challenges, in this paper, we propose RepTrace, a framework that leverages the uniform interfaces of system call tracing for monitoring executed build commands in diverse build environments and identifies the root causes for unreproducible builds by analyzing the system call traces of the executed build commands. Specifically, from the collected system call traces, RepTrace performs causality analysis to build a dependency graph starting from an inconsistent build artifact (across two builds) via two types of dependencies: read/write dependencies among processes and parent/child process dependencies, and searches the graph to find the processes that result in the inconsistencies. To address the challenges of massive noisy dependencies and uncertain parent/child dependencies, RepTrace includes two novel techniques: (1) using differential analysis on multiple builds to reduce the search space of read/write dependencies, and (2) computing similarity of the runtime values to filter out noisy parent/child process dependencies. The evaluation results of RepTrace over a set of real-world software packages show that RepTrace effectively finds not only the root cause commands responsible for the unreproducible builds, but also the files to patch for addressing the unreproducible issues. Among its Top-10 identified commands and files, RepTrace achieves high accuracy rate of 90.00% and 90.56% in identifying the root causes, respectively.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages527-538
Number of pages12
ISBN (Electronic)9781728125084
DOIs
StatePublished - Nov 2019
Externally publishedYes
Event34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019 - San Diego, United States
Duration: Nov 10 2019Nov 15 2019

Publication series

NameProceedings - 2019 34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019

Conference

Conference34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019
CountryUnited States
CitySan Diego
Period11/10/1911/15/19

Keywords

  • Localization
  • System call tracing
  • Unreproducible builds

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software
  • Control and Optimization

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  • Cite this

    Ren, Z., Liu, C., Xiao, X., Jiang, H., & Xie, T. (2019). Root cause localization for unreproducible builds via causality analysis over system call tracing. In Proceedings - 2019 34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019 (pp. 527-538). [8952375] (Proceedings - 2019 34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ASE.2019.00056