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Computer Science and Information Systems
Article . 2020 . Peer-reviewed
License: CC BY NC ND
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Computer Science and Information Systems
Article
License: CC BY NC ND
Data sources: UnpayWall
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Comparison of systematically derived software metrics thresholds for object-oriented programming languages

Authors: Tina Beranic; Marjan Hericko;

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

Abstract

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.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Average
gold