Emerging aspects of software fault localization

T. H. Tse, David Lo, Alex Groce, Michael Perscheid, Robert Hirschfeld, W. Eric Wong

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In this final chapter of the Handbook, we introduce emerging, innovative methods in software fault localization. First, we present scientific and systematic hypothesis-testing techniques and show they may be applied in practice. Second, for fault localization in the absence of a test oracle, we present a semi-proving methodology based on metamorphic relations and symbolic evaluation. It hinges on causes and effects instead of statistical probabilities. Third, we present an approach to predict the effectiveness of fault localization tools using machine learning. Lastly, we discuss why manually produced test cases are not ideal for fault localization and explain how to mitigate the problem by using automatically generated test cases.

Original languageEnglish (US)
Title of host publicationHandbook of Software Fault Localization
Subtitle of host publicationFoundations and Advances
Publisherwiley
Pages529-579
Number of pages51
ISBN (Electronic)9781119880929
ISBN (Print)9781119291800
DOIs
StatePublished - Jan 2 2023

Keywords

  • Automated test case generation tool
  • Fault localization tool
  • Machine-learning approach
  • Metamorphic relations

ASJC Scopus subject areas

  • General Computer Science

Fingerprint

Dive into the research topics of 'Emerging aspects of software fault localization'. Together they form a unique fingerprint.

Cite this