A novel quantitative evaluation approach for software project schedules using statistical model checking

Project schedules are essential for successfully carrying out software projects. To support manager's decision making, many project scheduling algorithms have been developed in recent years for generating candidate project schedules. However, these project schedules may not be able to be used directly because the uncertainty and complexity of real-world software development environments which have been overlooked or simplified in the project scheduling algorithms. Therefore, significant human efforts are still required to evaluate and compare these project schedules. To address such a problem, we propose a quantitative analysis approach based on statistical model checking technique which serves as a novel evaluation method for project schedules. By using the UPPAAL-SMC, we can systematically evaluate the performance of a project schedule and answer complex questions which are vital for manager's decision making but cannot be efficiently addressed by any existing tools. The preliminary results show that our approach can efficiently filter out unsatisfactory candidates by answering simple "yes or no" questions first and then help effectively compare the rest by answering complicated user specified questions. Therefore, the human efforts in planning project schedules can be significantly reduced.