A Fuzzified Approach for the Prediction of Fault Proneness and Defect Density
نویسنده
چکیده
The requirement to improve software productivity has promoted the research on software metrics technology. Object Oriented paradigm is the technology being used to build fault free and stupendous softwares; and to make them fault free object oriented metrics are being used. These metrics are used to identify high risk components early in the design phase and hence help us to reduce the rework and improve the software productivity. CK metrics can be used to obtain the fault proneness and MOOD metrics can be used to obtain the defect density in the modules. An algorithm using fuzzy logic toolbox has been proposed to measure fault proneness and defect density, and the results are shown. This process can be used to discover faults and defects in the early phases of the software development process and hence can be used to minimize rework. Index Terms – CK Metrics suite, Fuzzy inference system, Mamdani inference model, MOOD Metrics, Sugeno inference model.
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