Prioritizing MCDC test cases by spectral analysis of Boolean functions. (1st August 2017)

• Record Type: Journal Article
• Authors: Ayav, Tolga
• Is Part Of: Software testing, verification & reliability. Volume 27:Number 7(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-08-01
• Subjects: Boolean functions -- MCDC -- mutation analysis -- spectral analysis -- test prioritization; Computer software -- Testing -- Periodicals; Computer software -- Verification -- Periodicals; Computer software -- Reliability -- Periodicals; 005.14
• DOI: 10.1002/stvr.1641
• Languages: English
• ISSNs: 0960-0833

Abstract

Summary: Test case prioritization aims at scheduling test cases in an order that improves some performance goal. One performance goal is a measure of how quickly faults are detected. Such prioritization can be performed by exploiting the fault exposing potential (FEP) parameters associated to the test cases. The FEP is usually approximated by mutation analysis under certain fault assumptions. Although this technique is effective, it could be relatively expensive compared to the other prioritization techniques. This study proposes a cost‐effective FEP approximation for prioritizing modified condition decision coverage (MCDC) test cases. A strict negative correlation between the FEP of an MCDC test case and the influence value of the associated input condition allows to order the test cases easily without the need of an extensive mutation analysis. The method is entirely based on mathematics and it provides useful insight into how spectral analysis of Boolean functions can benefit software testing. Abstract : Test case prioritization allows earlier detection of software faults. This study proposes a spectral analysis‐based prioritization scheme for modified condition decision coverage test cases. The new scheme is formal and easy to perform, and it eliminates the extensive mutation analysis for prioritization.