Model‐based Testing for Fun and Profit
Dept. of Computer Science, University of Maryland
Model-based testing is emerging in many domains as an indispensible approach to validating software. In these approaches, an executable model of desired behavior is first constructed; this model may then be used to verify software responses to tests, and also as a source from which test cases themselves may be extracted. For design processes that already rely on the develop of models (examples include automotive and aerospace control software, among others), model-based testing offers tremendous opportunities for improvements in testing efficiency, and one may discern significant commercial activity in this arena as a result.
This talk will describe the speaker's experience in the building of Reactis(r), an automated model-based testing tool used for verifying embedded control software. Reactis generates test cases from MATLAB / Simulink(r) / Stateflow(r) models and is used heavily in the the automotive industry. Some of the key technical challenges in designing Reactis will be presented, and approaches to addressing these discussed.
Rance Cleaveland is Professor of Computer Science at the University of Maryland at College Park, where he is also Executive and Scientific Director of the Fraunhofer USA Center for Experimental and Software Engineering. Prior to joining the Maryland faculty, he held professorships at the State University of New York at Stony Brook and at North Carolina State University. He also co-founded Reactive Systems, Inc., in 1999 to commercialize tools for model-based testing of embedded software; Reactive Systems currently has numerous customers worldwide in the automotive and aerospace industries. He is a past recipient of Young Investigator Awards from the National Science Foundation and from the Office of Naval Research. He has published over 125 papers in the areas of software verification and validation, formal methods, model checking, software specification formalisms, and verification tools. Cleaveland received B.S. degrees in Mathematics and Computer Science from Duke University and his M.S. and Ph.D. degrees from Cornell University. He is a member of IEEE, the Association for Computing Machinery, and the Society for Automotive Engineering.