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Ontology-based quality attributes prediction in component-based development.

Li, Chengpu, Pooley, Rob and Liu, Xiaodong (2010) Ontology-based quality attributes prediction in component-based development. International Journal of Computer Science & Information Technology (IJCSIT), 2 (5). pp. 12-29. ISSN 0975-4660

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    Abstract/Description

    Despite the success that Component-Based Development (CBD) has achieved so far, component
    mismatch remains as a big obstacle for wider and smoother component reuse. Mismatch refers that the
    selected component does not satisfy the functional requirements, or that it fails the user’s expectation in
    terms of the Quality Attributes (QAs) of the component-based system. This allows us the potential to
    predict the quality attributes of a software system by analysing the result of component retrieval. In this
    paper, applicable quality attributes for prediction are selected by investigating existing software quality
    attributes. A novel ontology-based approach was proposed to achieve precise component retrieval and
    quality attribute prediction. The approach contains three steps: the first is to develop a Quality Attributes
    Oriented Component Specification ontology model (QAOCS), where applicable QAs related knowledge of
    application domains were integrated into the ontology. The second is to establish an ontology-based QAs
    oriented component retrieval method to retrieve components according to the reuse requirements. The
    third is to predict the quality attributes of component-based system on the basis of the matching
    information. Based on these three steps, a prototype tool with an example component repository was built
    to verify and scale up the approach.

    Item Type: Article
    Print ISSN: 0975-4660
    Electronic ISSN: 0975-3826
    Uncontrolled Keywords: System quality atributes; quality attributes prediction; component-based development; ontology;
    University Divisions/Research Centres: Faculty of Engineering, Computing and Creative Industries > School of Computing
    Dewey Decimal Subjects: 000 Computer science, information & general works > 000 Computer science, knowledge & systems > 005 Computer programming, programs & data
    Library of Congress Subjects: Q Science > QA Mathematics > QA76 Computer software
    Item ID: 3909
    Depositing User: Computing Research
    Date Deposited: 28 Jan 2011 12:00
    Last Modified: 06 Dec 2012 11:36
    URI: http://researchrepository.napier.ac.uk/id/eprint/3909

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