@article{MAKHILLAJIT20191836759,
    title = {Performance Calculation and Benchmarking using the ISBSG Dataset
Release 12 Data Repository: Empirical Study},
    journal = {Asian Journal of Information Technology},
    volume = {18},
    number = {3},
    pages = {124-132},
    year = {2019},
    issn = {1682-3915},
    doi = {ajit.2019.124.132},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2019.124.132},
    author = {Ahed J.,Shadi Mohammad,Hala Hani,Khaled and},
    keywords = {ISBSG,performance,productivity,effort,size,quality,neural network,data clustering,data
visualization},
    abstract = {The International Software Benchmarking Standards Group (ISBSG) maintains a software
development repository with 6,006 software projects. The definition of productivity is a single ratio of output
to input and then combined with various cost factors leading to a single value. Of these values we have dataset
makes it possible to calculate the productivity of projects, effort, size and quality. By contrast, the concept of
performance is more comprehensive than productivity. This study explores a comparison between performance
and productivity and how it can affect projects by several other factors that affect its using ISBSG dataset V.12.
In this research, tree data analysis techniques were applied: data clustering, neural network. SPSS was used to
conduct statistical analysis and data visualization.}
    }