A methodology for quantitatively managing the bug fixing process using Mahalanobis Taguchi system

Abstract

The controlling of bug fixing process during the system testing phase of software development life cycle is very important for fixing all the detected bugs within the scheduled time. The presence of open bugs often delays the release of the software or result in releasing the software with compromised functionalities. These can lead to customer dissatisfaction, cost overrun and eventually the loss of market share. In this paper, the authors propose a methodology to quantitatively manage the bug fixing process during system testing. The proposed methodology identifies the critical milestones in the system testing phase which differentiates the successful projects from the unsuccessful ones using Mahalanobis Taguchi system. Then a model is developed to predict whether a project is successful or not with the bug fix progress at critical milestones as control factors. Finally the model is used to control the bug fixing process. It is found that the performance of the proposed methodology using Mahalanobis Taguchi system is superior to the models developed using other multi-dimensional pattern recognition techniques. The proposed methodology also reduces the number of control points providing the managers with more options and flexibility to utilize the bug fixing resources across system testing phase. Moreover the methodology allows the mangers to carry out mid- course corrections to bring the bug fixing process back on track so that all the detected bugs can be fixed on time. The methodology is validated with eight new projects and the results are very encouraging.

Keywords

• Bug fixing
• Software testing
• Mahalanobis Taguchi system
• Design of Experiments
• K-Nearest Neighbour classifier