Joel L. Wolf, Mark S. Squillante, et al.
IEEE Transactions on Knowledge and Data Engineering
This paper presents a measurement framework for evaluating model-based test generation (MBTG) tools. The proposed framework is derived by using the Goal Question Metric methodology, which helps formulate the metrics of interest: complexity, ease of learning, effectiveness, efficiency, and scalability. We demonstrate the steps involved in evaluating MBTG tools by describing a case study designed for this purpose. This case study involves the use of four MBTG tools that differ in their modeling techniques, test specification techniques, and test generation algorithms. © 2006 IBM.
Joel L. Wolf, Mark S. Squillante, et al.
IEEE Transactions on Knowledge and Data Engineering
Liat Ein-Dor, Y. Goldschmidt, et al.
IBM J. Res. Dev
Reena Elangovan, Shubham Jain, et al.
ACM TODAES
Charles H. Bennett, Aram W. Harrow, et al.
IEEE Trans. Inf. Theory