@article{MAKHILLIJSC20105321013,
    title = {Automation of Software Artifacts Classification},
    journal = {International Journal of Soft Computing},
    volume = {5},
    number = {3},
    pages = {109-115},
    year = {2010},
    issn = {1816-9503},
    doi = {ijscomp.2010.109.115},
    url = {https://makhillpublications.co/view-article.php?issn=1816-9503&doi=ijscomp.2010.109.115},
    author = {Qusai and},
    keywords = {machine learning algorithms,software metrics,Software classification,instance-based algorithm,domain,LOC},
    abstract = {With the huge increase of software functionalities, sizes and application domain, the difficulty of categorizing and classifying software packages for reuse and maintenance purposes is on demand. This research includes the use of structure information contained in source code programs to automate program classification. Three software metrics namely; Line Of Codes (LOC), McCabe's Cyclomatic Complexity (MVG) and Weighted Methods per Class (WMC1) are used to automatically classify software packages into the appropriate application domains. The undertaken experiment using Instance-Based (IBK) algorithm generates classification accuracy as high as 74.82%. This indicates that further exploration on the use of structure information in the domain of software classification should be continued.}
    }