A Software Code Complexity Framework; Based on an Empirical Analysis of Software Cognitive Complexity Metrics using an Improved Merged Weighted Complexity Measure
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Abstract
 This research paper proposes a Software Complexity Code Framework Based on an empirical analysis of Software Cognitive Complexity Metrics using an Improved Merged Weighted Complexity Measure. Software Development Industry in Kenya is dominated by a myriad of Small Software Developers firms. It was observed that majority of the Small Software Developers Organizations have 2 - 20 employees indexed by 62.4%, whereas Large Software Developers Organizations index 30.4% [1]. The increased complexity of modern software applications also increases the difficulty of making the code reliable and maintainable. This research paper measures one internal measure of software products, namely software complexity. I develop a Software Code Complexity Framework using a proposed cognitive complexity metric for evaluating design of object-oriented (OO) code. The proposed metric is based on important features of the Object Oriented Systems: Inheritance, Control Structures, Nesting and Size. The proposed metric is applied on a real project for empirical validation and compared with Chidamber and Kemerer (CK) metrics suite [2]. The practical and empirical validations and the comparative study prove the robustness of the measure. The outcome of this Model leads to a development of Software Code Complexity Framework; a tool-set for static analysis of Java/C/C++ source code: a combination of automatic code review and automatic coding standards enforcement.
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