Comparison of systematically derived software metrics thresholds for object-oriented programming languages

Tina Beranič1 and Marjan Heričko1

  1. University of Maribor, Faculty of Electrical Engineering and Computer Science
    Koroška cesta 46, 2000 Maribor, Slovenia
    {tina.beranic, marjan.hericko}


Without reliable software metrics threshold values, the efficient quality evaluation of software could not be done. In order to derive reliable thresholds, we have to address several challenges, which impact the final result. For instance, software metrics implementations vary in various software metrics tools, including varying threshold values that result from different threshold derivation approaches. In addition, the programming language is also another important aspect. In this paper, we present the results of an empirical study aimed at comparing systematically obtained threshold values for nine software metrics in four object-oriented programming languages (i.e., Java, C++, C#, and Python). We addressed challenges in the threshold derivation domain within introduced adjustments of the benchmarkbased threshold derivation approach. The data set was selected in a uniform way, allowing derivation repeatability, while input values were collected using a single software metric tool, enabling the comparison of derived thresholds among the chosen object-oriented programming languages. Within the performed empirical study, the comparison reveals that threshold values differ between different programming languages.

Key words

software metrics, threshold values, reference values, object-oriented, benchmark data, programming language interdependence, reliable derivation, repeatability, replication

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Publication information

Volume 17, Issue 1 (January 2020)
Year of Publication: 2020
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

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Beranič, T., Heričko, M.: Comparison of systematically derived software metrics thresholds for object-oriented programming languages. Computer Science and Information Systems, Vol. 17, No. 1, 181-203. (2020),