IEEE Computer Society
Faculty of Computing, Health and Science
School of Computer and Security Science
Generally, quality software production seeks timely delivery with higher productivity at lower cost. Redundancy in a test suite raises the execution cost and wastes scarce project resources. In model-based testing, the testing process starts with earlier software developmental phases and enables fault detection in earlier phases. The redundancy in the test suites generated from models can be detected earlier as well and removed prior to its execution. The paper presents a novel max-min multiobjective technique incorporated into a test suite optimization framework to find a better trade-off between the intrinsically conflicting goals. For illustration two objectives i.e. coverage and size of a test suite were used however it can be extended to more objectives. The study is associated with model based testing and reports the results of the empirical analysis on four UML based synthetic as well as industrial Activity Diagram models.