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Conference Object Citation - WoS: 2Object-Oriented Inheritance Metrics: Cognitive Complexity Perspective(Springer-verlag Berlin, 2009) Mishra, Deepti; Mishra, AlokIdentifying high cognitive complexity modules can lead to a better quality software system and can help during maintenance also. It has been found that inheritance has an impact on cognitive complexity of a software system. In this paper, two inheritance metrics based on cognitive complexity, one at class level CCI (Class Complexity due to Inheritance) and another at program level ACI (Average Complexity of a program due to Inheritance), have been proposed for object-oriented software systems. These metrics are also compared with other well known object-oriented inheritance metrics.Article Citation - WoS: 4Citation - Scopus: 5Object-Oriented Inheritance Metrics in the Context of Cognitive Complexity(Ios Press, 2011) Mishra, Deepti; Mishra, AlokIt is important to identify modules that are fault prone or exhibit evidence of high cognitive complexity as these modules require corrective actions such as increased source code inspection, refactoring or performing more exhaustive testing. This can lead to a better quality software system. It has been found that inheritance has an impact on the cognitive complexity of a software system. In this paper, two inheritance metrics based on cognitive complexity, one at class level CCI (Class Complexity due to Inheritance) and another at program level ACI (Average Complexity of a program due to Inheritance), have been proposed for object-oriented software systems. Additionally, one more metric MC (Method Complexity) has been proposed to calculate the complexity of a method. These proposed metrics are compared with some well known object-oriented inheritance metrics by calculating their values for three random C++ programs. It has been observed that CCI and ACT are better to represent cognitive complexity due to inheritance than other well known class level and program level inheritance metrics.Article Citation - WoS: 12Citation - Scopus: 13Techniques for Calculating Software Product Metrics Threshold Values: a Systematic Mapping Study(Mdpi, 2021) Mishra, Alok; Shatnawi, Raed; Catal, Cagatay; Akbulut, AkhanSeveral 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.
