Computer Engineering / Bilgisayar Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/10

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2016 - 20172

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Subject: search.filters.subject.Test prioritization

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  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 5
    Automation Architecture for Bayesian Network Based Test Case Prioritization and Execution
    (Institute of Electrical and Electronics Engineers Inc., 2016) Ufuktepe, Ekincan; Tuğlular, Tuğkan
    An automation architecture for Bayesian Network based test case prioritization is designed for software written in Java programming language following the approach proposed by Mirarab and Tahvildari [2]. The architecture is implemented as an integration of a series of tools and called Bayesian Network based test case prioritization and execution platform. The platform is triggered by a change in the source code, then it collects necessary information to be supplied to Bayesian Network and uses Bayesian Network evaluation results to run high priority unit tests.
  • Article
    Citation - WoS: 4
    Citation - Scopus: 8
    Prioritizing Mcdc Test Cases by Spectral Analysis of Boolean Functions
    (John Wiley and Sons Inc., 2017) Ayav, Tolga
    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. 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 a 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.