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records:49818 a azonOnto:Article ;
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    azonOnto:authorInfo [ a azonOnto:AuthorInfo ;
            azonOnto:author person:12923 ;
            azonOnto:position 1 ],
        [ a azonOnto:AuthorInfo ;
            azonOnto:author person:12924 ;
            azonOnto:position 2 ],
        [ a azonOnto:AuthorInfo ;
            azonOnto:author person:12925 ;
            azonOnto:position 3 ],
        [ a azonOnto:AuthorInfo ;
            azonOnto:author person:12926 ;
            azonOnto:position 4 ] ;
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    azonOnto:description "Testing is an indispensable part of the software development life cycle. It is performed to improvethe performance, quality and reliability of the software. Various types of testing such as functionaltesting and structural testing are performed on software to uncover the faults caused by an incorrectcode, interaction of input parameters, etc. One of the major factors in deciding the quality of testing is the design of relevant test cases which is crucial for the success of testing. In this paper we concentrate on generating test cases to uncover faults caused by the interaction of input parameters.It is advisable to perform thorough testing but the number of test cases grows exponentially with the increase in the number of input parameters, which makes exhaustive testing of interactionof input parameters imprudent. An alternative to exhaustive testing is combinatorial interactiontesting (CIT) which requires that every t-way interaction of input parameters be covered by at leastone test case. Here, we present a novel strategy ABC-CAG (Artificial Bee Colony-Covering ArrayGenerator) based on the Artificial Bee Colony (ABC) algorithm to generate covering an array anda mixed covering array for pair-wise testing. The proposed ABC-CAG strategy is implemented in a tool and experiments are conducted on various benchmark problems to evaluate the efficacy ofthe proposed approach. Experimental results show that ABC-CAG generates better/comparable results as compared to the existing state-of-the-art algorithms."@en ;
    azonOnto:destinationGroup "naukowcy"@pl,
        "ogół społeczeństwa"@pl,
        "studenci"@pl ;
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            azonOnto:value "10.5277/e-Inf160101"^^xsd:string ] ;
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            azonOnto:name "e-Informatica_Vol.10_2016_Issue_1_Art_1.zip"^^xsd:string ;
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            azonOnto:name "adaptacja"@pl ;
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            azonOnto:uri "https://azon.e-science.pl/licencje/ID-NC-ND_PWr.pdf"^^xsd:anyURI ] ;
    azonOnto:numeration "Vol. 10, issue 1"^^xsd:string ;
    azonOnto:pageFrom 9 ;
    azonOnto:pageTo 29 ;
    azonOnto:partner [ a azonOnto:Organization ;
            azonOnto:name "Politechnika Wrocławska"^^xsd:string ] ;
    azonOnto:publicationYear 2016 ;
    azonOnto:publisher "Oficyna Wydawnicza Politechniki Wrocławskiej"^^xsd:string ;
    azonOnto:relatedLink [ a azonOnto:RelatedLinkInfo ;
            azonOnto:name "e-Informatica Software Engineering Journal, Vol. 10, 2016, Issue 1"^^xsd:string ;
            azonOnto:uri "https://www.dbc.wroc.pl/dlibra/publication/40282/edition/37399"^^xsd:anyURI ] ;
    azonOnto:scientificDiscipline "dziedzina nauk technicznych / informatyka (2011)"@pl ;
    azonOnto:source [ a azonOnto:Source ;
            azonOnto:title "e-Informatica: Software Engineering Journal"@pl ] ;
    azonOnto:submitter [ a azonOnto:Person ;
            azonOnto:name "Magdalena Kruczek"^^xsd:string ] ;
    azonOnto:title "ABC-CAG: covering array generator for pair-wise testing using artificial bee colony algorithm"@pl .

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