Continuous productivity assessment and effort prediction based on Bayesian analysis

Abstract

Project management is one of the most critical activities in modern software development projects. Without realistic and objective management, the software development process cannot be managed in an effective way. However, difficulty in assessment of project attributes leads a project into failure. Therefore, it is essential to keep providing objective assessment of project attributes as software development evolves. Another important aspect of a software development project is to know how much it will cost. And predicting development effort is central to the project management. However, effort prediction is one of the most difficult tasks in project management. We use Bayesian approach to update productivity and predict effort based on the updated productivity. In this work we describe an extended tool that we added to PAMPA 2 (Project Attributes Monitoring and Prediction Associate) to help manage a project.