Adding Process Metrics to Enhance Modification Complexity Prediction

Software estimation is used in various contexts including cost, maintainability or defect prediction. To make the estimate, different models are usually applied based on attributes of the development process and the product itself. However, often only one type of attributes is used, like historical process data or product metrics, and rarely their combination is employed. In this report, we present a project in which we started to develop a framework for such complex measurement of software projects, which can be used to build combined models for different estimations related to software maintenance and comprehension. First, we performed an experiment to predict modification complexity (cost of a unity change) based on a combination of process and product metrics. We observed promising results that confirm the hypothesis that a combined model performs significantly better than any of the individual measurements.