TesCaV: An Approach for Learning Model-Based Testing and Coverage in Practice

Academy and industry permanently remark the importance of software-testing techniques to improve software quality and to reduce development and maintenance costs. A testing method to be considered for this purpose is Model-Based Testing (MBT), which generates test cases from a model that represents the structure and the behavior of the system to be developed. The generated test suite is easier to maintain and adapt to changes in requirements or evolution of the developed system. However, teaching and learning MBT techniques are not easy tasks; students need to know the different testing techniques to assure that the requirements are fulfilled as well as to identify any failure in the software system modeled. In this work, we present TesCaV, an MBT teaching tool for university students, which is based on a model-driven technology for the automatic software generation from UML diagrams. TesCaV allows validating the test cases defined by students and graphically determines the level of testing coverage over the system modeled. Preliminary results show TesCaV as a promising approach for MBT teaching/learning processes.