Defect proneness estimation and feedback approach for software design quality improvement

Abstract

Context Modern software engineering demands professionals and researchers to proactively and collectively work towards exploring and experimenting viable and valuable mechanisms in order to extract all kinds of degenerative bugs, security holes, and possible deviations at the initial stage. Having understood the real need here, we have introduced a novel methodology for the estimation of defect proneness of class structures in object oriented (OO) software systems at design stage. Objective The objective of this work is to develop an estimation model that provides significant assessment of defect proneness of object oriented software packages at design phase of SDLC. This frame work enhances the efficiency of SDLC through design quality improvement. Method This involves a data driven methodology which is based on the empirical study of the relationship existing between design parameters and defect proneness. In the first phase, a mapping of the relationship between the design metrics and normal occurrence pattern of defects are carried out. This is represented as a set of non linear multifunctional regression equations which reflects the influence of individual design metrics on defect proneness. The defect proneness estimation model is then generated by weighted linear combination of these multifunctional regression equations. The weighted coefficients are evaluated through GQM (Goal Question Metric) paradigm. Results The model evaluation and validation is carried out with a selected set of cases which is found to be promising. The current study is successfully dealt with three projects and it opens up the opportunity to extend this to a wide range of projects across industries. Conclusion The defect proneness estimation at design stage facilitates an effective feedback to the design architect and enabling him to identify and reduce the number of defects in the modules appropriately. This results in a considerable improvement in software design leading to cost effective products.