Vectorizing Program Ingredients for Better JVM Testing

Tianchang Gao, Junjie Chen, Yingquan Zhao, Yuqun Zhang, Lingming Zhang

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

Abstract

JVM testing is one of the most widely-used methodologies for guaranteeing the quality of JVMs. Among various JVM testing techniques, synthesis-based JVM testing, which constructs a test program by synthesizing various code snippets (also called program ingredients), has been demonstrated state-of-the-art. The existing synthesis-based JVM testing work puts more efforts in ensuring the validity of synthesized test programs, but ignores the influence of huge ingredient space, which largely limits the ingredient exploration efficiency as well as JVM testing performance. In this work, we propose Vectorized JVM Testing (called VECT) to further promote the performance of synthesis-based JVM testing. Its key insight is to reduce the huge ingredient space by clustering semantically similar ingredients via vectorizing ingredients using state-of-the-art code representation. To make VECT complete and more effective, based on vectorized ingredients, VECT further designs a feedback-driven ingredient selection strategy and an enhanced test oracle. We conducted an extensive study to evaluate VECT on three popular JVMs (i.e., HotSpot, OpenJ9, and Bisheng JDK) involving five OpenJDK versions. The results demonstrate VECT detects 115.03% ∼ 776.92% more unique inconsistencies than the state-of-the-art JVM testing technique during the same testing time. In particular, VECT detects 26 previously unknown bugs for them, 15 of which have already been confirmed/fixed by developers.

Original languageEnglish (US)
Title of host publicationISSTA 2023 - Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis
EditorsRene Just, Gordon Fraser
PublisherAssociation for Computing Machinery
Pages526-537
Number of pages12
ISBN (Electronic)9798400702211
DOIs
StatePublished - Jul 12 2023
Event32nd ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2023 - Seattle, United States
Duration: Jul 17 2023Jul 21 2023

Publication series

NameISSTA 2023 - Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis

Conference

Conference32nd ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2023
Country/TerritoryUnited States
CitySeattle
Period7/17/237/21/23

Keywords

  • JVM Testing
  • Java Virtual Machine
  • Program Synthesis
  • Test Oracle

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

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