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Automatic Detection and Removal of Conformance Faults in Feature Models

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F16%3A10331916" target="_blank" >RIV/00216208:11320/16:10331916 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1109/ICST.2016.10" target="_blank" >http://dx.doi.org/10.1109/ICST.2016.10</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/ICST.2016.10" target="_blank" >10.1109/ICST.2016.10</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Automatic Detection and Removal of Conformance Faults in Feature Models

  • Original language description

    Building a feature model for an existing SPL can improve the automatic analysis of the SPL and reduce the effort in maintenance. However, developing a feature model can be error prone, and checking that it correctly identifies each actual product of the SPL may be unfeasible due to the huge number of possible configurations. We apply mutation analysis and propose a method to detect and remove conformance faults by selecting special configurations that distinguish a feature model from its mutants. We propose a technique that, by iterating this process, is able to repair a faulty model. We devise several variations of a simple hill climbing algorithm for automatic fault removal and we compare them by a series of experiments on three different sets of feature models. We find that our technique is able to improve the conformance of around 90% of the models and find the correct model in around 40% of the cases.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2016

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    2016 IEEE International Conference on Software Testing, Verification and Validation

  • ISBN

    978-1-5090-1827-7

  • ISSN

    2381-2834

  • e-ISSN

  • Number of pages

    11

  • Pages from-to

    102-112

  • Publisher name

    Institute of Electrical and Electronics Engineers Inc.

  • Place of publication

    Neuveden

  • Event location

    Chicago

  • Event date

    Apr 10, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000391252900010