Requirement Change Prediction Model for Small Software Systems

Abstract

The software industry is rising gradually, it seems that there is no end to software development. Modern era software projects are complex and consist of many components, so change is unavoidable in these projects. Therefore, change in the software requirements document must be predicted at an early stage to preserve the resources. There are a lot of requirement change prediction models proposed in the literature and they are addressing a smaller number of variables and including experts knowledge for analyzing the requirement specification document. In this work, we have focused on the small software systems which have focused few variables of requirement change prediction model.The variables have a major effect on the software requirements and these are analyzed by the stakeholders, developers and experts with the questionnaire method. Their knowledge is incorporated in the Bayesian network as conditional probabilities of independent and dependent variables.This is actually the proposed model for software requirements change prediction.We used an algorithm with the model by utilizing variable elimination method to obtain the posterior probability of the revisions in software requirement document. However this model can also be used for the large software systems because it is effecent to resolve their problems also. the The proposed model is evaluated by hypothesis testing, sensitivity analysis and by comparing with the existing models. The results obtained proved to be promising as it decreases the probability of revisions in the requirement document. We obtained the 0.42 probability for the revisions in the requirement document so the results have improved the existing model predictions.