Software Metrics Evaluation Based on Entropy

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Author(s): R. Selvarani (Dayananda Sagar Institutions, Bangalore, India), T.R.Gopalakrishnan Nair (Dayananda Sagar Institutions, Bangalore, India), Muthu Ramachandran (Leeds Metropolitan University, UK)and Kamakshi Prasad (JNTU, Hyderabad, India)
Copyright: 2010
Pages: 13
Source title: Handbook of Research on Software Engineering and Productivity Technologies: Implications of Globalization
Source Author(s)/Editor(s): Muthu Ramachandran (Leeds Metropolitan University, UK)and Rogério Atem de Carvalho (Instituto Federal Fluminense, Brazil)
DOI: 10.4018/978-1-60566-731-7.ch011

Keywords: Computer Science & IT / Information Science Reference / Systems & Software Design / Systems and Software Engineering

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Abstract

The complexity of modern software, the commercial constraints and the expectation for high quality product demands the accurate fault prediction based on OO design metrics in the class level in the early stages of software development. The object oriented class metrics are used as quality predictors in the entire OO software development life cycle even when a highly iterative, incremental model or agile software process is employed. Recent research has shown some of the OO design metrics are useful for predicting fault-proneness of classes. In this chapter the empirical validation of a set of metrics proposed by Chidamber and Kemerer is performed to assess their ability in predicting the software quality in terms of fault proneness and degradation. The authors have also proposed the design complexity of object-oriented software with Weighted Methods per Class metric (WMC-CK metric) expressed in terms of Shannon entropy, and error proneness.

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Software Metrics Evaluation Based on Entropy

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