Fine-Granular Model Diff Solution For Model-Based Software Configuration Management

Abstract

Software Configuration Management (SCM) aims to provide a controlling mechanism for the evolution of software artifacts created during software development process.Controlling the evolution requires many activities to perform, such as, construction and creation of versions, computation of mappings and differences between versions, combining of two or more versions and so on. Traditional SCM systems are file-based SCM systems. File-based SCM systems arenot adequate for performing software configuration management activitiesbecause they consider software artifacts as a set of text files while today software development is model -driven and models are the main artifacts produced in the early phases of software life cycle. New challenges of model mappings, differencing, merging (combining two or more versions), and conflict detection (identifying conflicting changes by multiple users) arise while applying file-based solution to models.The goal of this work is to develop a configuration management solution for model representation, mappings and differences which overcomes the challenges faced by traditional SCM systems while model being the central artifact. Our solution is two-folded. First part deals with model representation. While traditional SCM systems represent models as textual files at fine-granular level, we represent models as graph structure at fine-granular level. In second part we are dealing with the issue of model diff, i.e., calculating the mappings and differences between two versions of a model. Since our model diff solution is based on our fine-granular model representation therefore we overcome not only the problem of textual representation of model but produce efficient results for model diff in terms of accuracy, execution time, tool independency and other evaluation parameters. We performed a controlled experiment using open source eclipse modeling framework and compare our approach with an open source tool EMF Compare. The results proved the efficiency of our approach.