A statistical comparison of Java and python software metric properties

Giuseppe Destefanis, Marco Ortu, Simone Porru, Stephen Swift, Michele Marchesi

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    6 Citations (Scopus)

    Abstract

    This paper presents a statistical analysis of 20 opens ource object-oriented systems with the purpose of detecting differences in metrics distribution between Java and Python projects. We selected ten Java projects from the Java Qual itas Corpus and ten projects written in Python. For each system, we considered 10 class-level software metrics. We performed a best fit procedure on the empirical distributions through the log-normal distribution and the double Pareto distribution to identify differences between the two languages. Even though the statistical distributions for projects written in Java and Python may appear the same for lower values of the metric, performing the procedure with the double Pareto distribution for the Number of Local Methods metric reveals that major differences can be noticed along the queue of the distributions. On the contrary, the same analysis performed with the Number of Statements metric reveals that only the initial portion of the double Pareto distribution shows differences between the two languages. In addition, the dispersion parameter associated to the log-normal distribution fit for the total Number Of Methods can be used for distinguishing Java projects from Python projects.

    Original languageEnglish
    Title of host publicationProceedings - 7th International Workshop on Emerging Trends in Software Metrics, WETSoM 2016
    PublisherACM Press
    Pages22-28
    Number of pages7
    ISBN (Electronic)9781450341776
    DOIs
    Publication statusPublished - 14 May 2016
    Event7th International Workshop on Emerging Trends in Software Metrics, WETSoM 2016 - Austin, United States
    Duration: 14 May 2016 → …

    Conference

    Conference7th International Workshop on Emerging Trends in Software Metrics, WETSoM 2016
    Country/TerritoryUnited States
    CityAustin
    Period14/05/16 → …

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