Improving faulty interaction localization using logistic regression

Kinari Nishiura, Eun Hye Choi, Osamu Mizuno

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

6 Citations (Scopus)

Abstract

Combinatorial testing is a widely used technique to detect failures caused by interactions of system under test (SUT) parameters. Faulty interaction localization (FIL) is a problem to locate parameter-value combinations that trigger failures from combinatorial test cases and their testing results. FIL is important for debugging, but is expensive for large test suites and SUTs since the number of candidates of faulty interactions increases exponentially with the number of parameters and the size of interactions. To address this problem, this paper proposes a method employing logistic regression. The proposed FIL based on Regression coefficients Of loGistic regression analysis (called FROG) computes the suspiciousness of each parameter-value combination to be included in a faulty interaction from its corresponding regression coefficient. We evaluate the proposed method by applying FROG to combinatorial t-way test cases (2 ≤ t ≤ 4) for real application SUT models, e.g. TCAS, GCC, and Apache. Our experiment results show that FROG can effectively locate faulty interactions injected while efficiently reducing the number of candidates of potential faulty interactions to be checked.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE International Conference on Software Quality, Reliability and Security, QRS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages138-149
Number of pages12
ISBN (Electronic)9781538605929
DOIs
Publication statusPublished - Aug 11 2017
Externally publishedYes
Event17th IEEE International Conference on Software Quality, Reliability and Security, QRS 2017 - Prague, Czech Republic
Duration: Jul 25 2017Jul 29 2017

Publication series

NameProceedings - 2017 IEEE International Conference on Software Quality, Reliability and Security, QRS 2017

Conference

Conference17th IEEE International Conference on Software Quality, Reliability and Security, QRS 2017
Country/TerritoryCzech Republic
CityPrague
Period7/25/177/29/17

Keywords

  • Combinatorial testing
  • Faulty interaction
  • Faulty interaction localization
  • Logistic regression
  • Regression coefficient
  • T-way testing

ASJC Scopus subject areas

  • Software
  • Safety, Risk, Reliability and Quality

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