Abstract
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.
Highlights
Software engineering aims to determine and advance the quality of software throughout the software development life cycle
Beranic and Hericko [3] concluded that thresholds are critical for software metric analyses and, they are important in practice [2]
Ferreira et al [2] stated that a lack of knowledge on metric threshold values constrains the wide use of software metrics, and several metrics are very useful to improve software design
Summary
Software engineering aims to determine and advance the quality of software throughout the software development life cycle For achieving this aim, software metrics are applied to consider the qualitative aspects of software components quantitatively [1]. Determining appropriate threshold values is a rigorous task as thresholds attained by achieving a correlation analysis are only for a defined group of identical software systems [5]. This is further supported by Zhang et al [6], who note that thresholds cannot be inferred and depend on distinct domains.
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