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    Filling the gaps: Imputation of missing metrics’ values in a software quality model

    Access Status
    Fulltext not available
    Authors
    Kupinski, S.
    Walter, B.
    Wolski, Marcin
    Chojnacki, J.
    Date
    2017
    Type
    Conference Paper
    
    Metadata
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    Citation
    Kupinski, S. and Walter, B. and Wolski, M. and Chojnacki, J. 2017. Filling the gaps: Imputation of missing metrics’ values in a software quality model, in Proceedings of the 27th International Workshop on Software Measurement (IWSM) and 12th International Conference on Software Process and Product Measurement, Oct 25-27 2017, pp. 82-87. Göteborg, Sweden: Association for Computing Machinery (ACM).
    Source Title
    ACM International Conference Proceeding Series
    DOI
    10.1145/3143434.3143451
    ISBN
    9781450348539
    School
    School of Civil and Mechanical Engineering (CME)
    URI
    http://hdl.handle.net/20.500.11937/60161
    Collection
    • Curtin Research Publications
    Abstract

    Hierarchical software quality models usually rely on a number of metrics, which, once aggregated, provide an overview of selected perspectives of a system’s quality. Missing values of some metrics, that usually result from data unavailability, can seriously affect the final score. In the paper we empirically validate a few imputation methods in context of a custom Géant-QM framework, used for evaluation of several open source systems. Early results indicate imputing a missing value based on its close neighbors as data donors introduces less noise that using a wider set of donors.

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