From typestate verification to interpretable deep models (invited talk abstract)

Eran Yahav, Stephen J. Fink, Nurit Dor, G. Ramalingam, Emmanuel Geay

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The paper “Effective Typestate Verification in the Presence of Aliasing” was published in the International Symposium on Software Testing and Analysis (ISSTA) 2006 Proceedings, and has now been selected to receive the ISSTA 2019 Retrospective Impact Paper Award. The paper described a scalable framework for verification of typestate properties in real-world Java programs. The paper introduced several techniques that have been used widely in the static analysis of real-world programs. Specifically, it introduced an abstract domain combining access-paths, aliasing information, and typestate that turned out to be simple, powerful, and useful. We review the original paper and show the evolution of the ideas over the years. We show how some of these ideas have evolved into work on machine learning for code completion, and discuss recent general results in machine learning for programming.

Original languageEnglish
Title of host publicationISSTA 2019 - Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis
EditorsDongmei Zhang, Anders Moller
Pages4-5
Number of pages2
ISBN (Electronic)9781450362245
DOIs
StatePublished - 10 Jul 2019
Event28th ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2019 - Beijing, China
Duration: 15 Jul 201919 Jul 2019

Publication series

NameISSTA 2019 - Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis

Conference

Conference28th ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2019
Country/TerritoryChina
CityBeijing
Period15/07/1919/07/19

Keywords

  • Machine learning
  • Program analysis
  • Program synthesis

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Software

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