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    A framework to assess the effectiveness of quality assessment model developed using class level metrics

    Access Status
    Fulltext not available
    Authors
    Kumar, L.
    Krishna, Aneesh
    Rath, S.
    Bhattacharya, S.
    Date
    2016
    Type
    Conference Paper
    
    Metadata
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    Citation
    Kumar, L. and Krishna, A. and Rath, S. and Bhattacharya, S. 2016. A framework to assess the effectiveness of quality assessment model developed using class level metrics, 25th International Conference on Software Engineering and Data Engineering, SEDE 2016, pp. 23-28.
    Source Title
    25th International Conference on Software Engineering and Data Engineering, SEDE 2016
    ISBN
    9781943436057
    School
    Department of Computing
    URI
    http://hdl.handle.net/20.500.11937/51662
    Collection
    • Curtin Research Publications
    Abstract

    System and class level software metrics are often considered for predicting fault-prone modules in a software during the analysis and design phase of object-oriented software development life cycle (SDLC). However it is further observed that class level metrics also provide a good amount of insight on fault prediction. This study focuses on developing various fault prediction models based on public datasets. In order to validate efficiencies of prediction models for predicting fault proneness are often validated. To achieve this, a cost evaluation framework has been proposed to evaluate the effectiveness of the fault prediction models. This framework, is based on the classification of classes into faulty or not-faulty ones. From the obtained results, it is observed that fault prediction is useful for the projects with the percentage of faulty modules less than a certain threshold value. From the proposed models, it is also observed that no single model is sufficient to provide the best result (effective cost); but an attempt in this direction helps for an in-depth analysis.

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