Chi Square Test for Software Defect Prediction

Abstract

Software Defect Prediction (SDP) is an important activity in testing Phase of Software Development Life Cycle. It identifies the modules that are defect prone and requires extensive testing. This way, the testing resources can be used efficiently without violating the constraints. Though Software Defect Prediction (SDP) is very helpful in testing, it’s not always easy to predict the defective modules. There are various issues that hinder the smooth performance as well as use of the defect prediction models. In my research, I would like to carry out a survey on different software firms to identify and analyze their software prediction models, carry out a SWOT (Strength Weakness Opportunities Threats) analysis of each model, identify non value added activities in these models using VSM (Value Stream Mapping) and FMEA (Failure Model Effective Analysis) as a tool & finally come out with an adoptive model which will have benefits of all models & can be widely used.