Impact of Size and Productivity on Testing and Rework Efforts for Web-based Development Projects

Abstract

In the planning of a software development project, a major challenge faced by project managers is to predict the rework effort. (Rework effort is the effort required to fix the software defects identified during system testing). The project manager's objective is to deliver the software within the time, cost and quality requirements given by the client. To ensure the quality of the software, many testing cycles will be conducted before it is finally delivered to the client for acceptance. Each testing cycle is a costly affair as it involves running all possible test scenarios in all possible environments, followed by defect fixing and re-verification of defect fixes. On average, two to three testing cycles are conducted but this depends on the number of defects identified during testing. The number of defects will depend on the team expertise and whether they earlier worked on similar projects and technologies. Therefore, it becomes critical to predict the number of defects that will be identified during testing and it is a very challenging task as it requires a good model to predict the rework effort. In this paper, we describe the relationships among software size, number of software defects, productivity and efforts for web-based development projects. These relationships are established by using the multiple linear regression technique on the benchmarking data published by International Software Benchmarking Standard Group. Results suggest that in web-based projects the number of defects identified is directly proportional to the productivity, i.e. higher productivity will led to more defects found and lower productivity will lead to fewer defects found, therefore, less testing and rework effort will be required if project is planned with lower productivity because we can spend more time on development (i.e. time spend till construction phase) to reduce the number of defects found during testing and it will directly contribute in reducing the rework efforts. We infer from the relationship that software size has a significant impact on the total number of defect identified. We also infer that while planning a software project we should use appropriate tools to reduce the margin of error in size estimation and we should also re-estimate the size after every phase of the development life cycle to re-calibrate overall efforts and to minimize the impact on the project plan.