Prioritized test generation guided by software fault prediction

Eran Hershkovich, Roni Stern, Rui Abreu, Amir Elmishali

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

Abstract

Writing and running software unit tests is one of the fundamental techniques used to maintain software quality. However, this process is rather costly and time consuming. Thus, much effort has been devoted to generating unit tests automatically. The common objective of test generation algorithms is to maximize code coverage. However, maximizing coverage is not necessarily correlated with identifying faults [1]. In this work, we propose a novel approach for test generation aiming at generating a small set of tests that cover the software components that are likely to contain bugs. To identify which components are more likely to contain bugs, we train a software fault prediction model using machine learning techniques. We implemented this approach in practice in a tool called QUADRANT, and demonstrate its effectiveness on five real-world, open-source projects. Results show the benefit of using QUADRANT, where test generation guided by our fault prediction model can detect more than double the number of bugs compared to a coverage-oriented approach, thereby saving test generation and execution efforts.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages218-225
Number of pages8
ISBN (Electronic)9781665444569
DOIs
StatePublished - 1 Apr 2021
Event14th IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2021 - Virtual, Porto de Galinhas, Brazil
Duration: 12 Apr 202116 Apr 2021

Publication series

NameProceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2021

Conference

Conference14th IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2021
Country/TerritoryBrazil
CityVirtual, Porto de Galinhas
Period12/04/2116/04/21

Keywords

  • Automated testing generation
  • Fault prediction
  • Machine learning
  • Software testing

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Safety, Risk, Reliability and Quality

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