An EFSM-Based Test Data Generation Approach in Model-Based Testing

Testing is an integral part of software development. Current fast-paced system developments have rendered traditional testing techniques obsolete. Therefore, automated are needed to adapt such speed. Model-based (MBT) a technique that uses models generate and execute test cases automatically. It was identified the data generation (TDG) in many existing model-based case (MB-TCG) approaches were still manual. An automatic effective TDG can further reduce cost while detecting more faults. This study proposes approach MB-TCG using extended finite state machine model (EFSM). The proposed integrates MBT with combinatorial testing. information available EFSM boundary value analysis strategy used automate domain input classifications which done manually by approach. results showed able detect 6.62 percent faults than conventional but at same time generated 43 tests. effectively detects faults, treatment tests as prioritization should be increase effectiveness efficiency