Understanding automatically-generated patches through symbolic invariant differences

Padraic Cashin, Carianne Martinez, Westley Weimer, Stephanie Forrest

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

1 Scopus citations

Abstract

Developer trust is a major barrier to the deployment of automatically-generated patches. Understanding the effect of a patch is a key element of that trust. We find that differences in sets of formal invariants characterize patch differences and that implication-based distances in invariant space characterize patch similarities. When one patch is similar to another it often contains the same changes as well as additional behavior; this pattern is well-captured by logical implication. We can measure differences using a theorem prover to verify implications between invariants implied by separate programs. Although effective, theorem provers are computationally intensive; we find that string distance is an efficient heuristic for implication-based distance measurements. We propose to use distances between patches to construct a hierarchy highlighting patch similarities. We evaluated this approach on over 300 patches and found that it correctly categorizes programs into semantically similar clusters. Clustering programs reduces human effort by reducing the number of semantically distinct patches that must be considered by over 50%, thus reducing the time required to establish trust in automatically generated repairs.

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.
Pages411-414
Number of pages4
ISBN (Electronic)9781728125084
DOIs
StatePublished - Nov 2019
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

  • Automated Program Repair
  • Dynamic Invariants
  • Program Measurement

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software
  • Control and Optimization

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  • Cite this

    Cashin, P., Martinez, C., Weimer, W., & Forrest, S. (2019). Understanding automatically-generated patches through symbolic invariant differences. In Proceedings - 2019 34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019 (pp. 411-414). [8952219] (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.2019.00046