Techniques for Calculating Software Product Metrics Threshold Values: A Systematic Mapping Study

Applied Sciences

Akhan Akbulut¹  Cagatay Catal²  Raed Shatnawi³  Alok Mishra⁴ 

[1] Department of Computer Engineering, Istanbul Kultur University, Istanbul 34158, Turkey;Department of Computer Science and Engineering, Qatar University, Doha 2713, Qatar;Department of Software Engineering, Jordan University of Science and Technology, Irbid 22110, Jordan;Molde University College—Specialized University in Logistics, Faculty of Logistics, 6410 Molde, Norway;

关键词: object-oriented metrics;    software metrics;    object-oriented measures;    thresholds;    systematic mapping;    software quality;   

DOI  :  10.3390/app112311377

来源: DOAJ

【 摘 要 】

Several aspects of software product quality can be assessed and measured using product metrics. Without software metric threshold values, it is difficult to evaluate different aspects of quality. To this end, the interest in research studies that focus on identifying and deriving threshold values is growing, given the advantage of applying software metric threshold values to evaluate various software projects during their software development life cycle phases. The aim of this paper is to systematically investigate research on software metric threshold calculation techniques. In this study, electronic databases were systematically searched for relevant papers; 45 publications were selected based on inclusion/exclusion criteria, and research questions were answered. The results demonstrate the following important characteristics of studies: (a) both empirical and theoretical studies were conducted, a majority of which depends on empirical analysis; (b) the majority of papers apply statistical techniques to derive object-oriented metrics threshold values; (c) Chidamber and Kemerer (CK) metrics were studied in most of the papers, and are widely used to assess the quality of software systems; and (d) there is a considerable number of studies that have not validated metric threshold values in terms of quality attributes. From both the academic and practitioner points of view, the results of this review present a catalog and body of knowledge on metric threshold calculation techniques. The results set new research directions, such as conducting mixed studies on statistical and quality-related studies, studying an extensive number of metrics and studying interactions among metrics, studying more quality attributes, and considering multivariate threshold derivation.

【 授权许可】

Unknown