Fuzzy Technique for software Quality Measurement (International Journal of Engineering and Computer Science, 2014)
The software quality prediction is a major issue these days. in order to develop software quality prediction model, one must first identify the factors that strongly influence software quality and the number of residual errors.unfortunatly,it is extremely difficult, to accurately identify relevant quality factors. that is although exact and discrete metric data are used, inference rules used may be fuzzy in nature. the benefits of inspections, originally indicated by Fagan[1],have been re-confirmed by other practitioners. Software inspection is considered as an essential practice to develop high quality software. if it is possible to identify potentially error –prone modules with relatively high degree of accuracy at a little or no extra cost by analyzing the present inspection data. this paper purpose a fuzzy logic based precise approach to quantify quality of software modules based on inspection rate and error density to predict quality factor such as whether a component is fault prone or not.