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Antinyan, V., Staron, M. and Sandberg, A. (2017) Evaluating Code Complexity Triggers, Use of Complexity Measures and the Influence of Code Complexity on Maintenance Time. Empirical Software Engineering, 22, 3057-3087.
https://doi.org/10.1007/s10664-017-9508-2

has been cited by the following article:

• TITLE: Framework for Observing the Maintenance Needs, Runtime Metrics and the Overall Quality-in-Use

  AUTHORS: Timo Hynninen, Jussi Kasurinen, Ossi Taipale

  KEYWORDS: Software Maintenance, Software Life-Cycle, Measurement, Test Metrics, Maintenance Costs

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.11 No.4, March 29, 2018

  ABSTRACT: The post-release maintenance is usually the most expensive phase in the software product lifecycle from the first design concepts to the end of product support. To reduce the costs related to post-release maintenance, we propose a run-time framework for measuring software quality characteristics applying the ISO/IEC 25000 software quality and software quality in use models as the starting point. Measurement probes are linked into the software during the development phase and used to collect quality information during the run time. As a proof-of-concept, we implemented measurements in an open-source software project to demonstrate the utility of the framework. As a result, this paper presents a framework for collecting runtime metrics and measuring software quality-in-use with a systematic interface. Additionally, examples of measurement scenarios are presented.