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Open AccessArticle

Comparing Static and Dynamic Weighted Software Coupling Metrics

Software Engineering Group, Kiel University, 24098 Kiel, Germany
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in ICIST 2019, 10–12 October 2019, Vilnius, Lithuania.
Computers 2020, 9(2), 24;
Received: 20 February 2020 / Revised: 27 March 2020 / Accepted: 28 March 2020 / Published: 30 March 2020
Coupling metrics that count the number of inter-module connections in a software system are an established way to measure internal software quality with respect to modularity. In addition to static metrics, which are obtained from the source or compiled code of a program, dynamic metrics use runtime data gathered, e.g., by monitoring a system in production. Dynamic metrics have been used to improve the accuracy of static metrics for object-oriented software. We study weighted dynamic coupling that takes into account how often a connection (e.g., a method call) is executed during a system’s run. We investigate the correlation between dynamic weighted metrics and their static counterparts. To compare the different metrics, we use data collected from four different experiments, each monitoring production use of a commercial software system over a period of four weeks. We observe an unexpected level of correlation between the static and the weighted dynamic case as well as revealing differences between class- and package-level analyses. View Full-Text
Keywords: software metrics; monitoring; dynamic/static analysis software metrics; monitoring; dynamic/static analysis
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MDPI and ACS Style

Schnoor, H.; Hasselbring, W. Comparing Static and Dynamic Weighted Software Coupling Metrics. Computers 2020, 9, 24.

AMA Style

Schnoor H, Hasselbring W. Comparing Static and Dynamic Weighted Software Coupling Metrics. Computers. 2020; 9(2):24.

Chicago/Turabian Style

Schnoor, Henning; Hasselbring, Wilhelm. 2020. "Comparing Static and Dynamic Weighted Software Coupling Metrics" Computers 9, no. 2: 24.

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