Using Bayesian optimization algorithm for model-based integration testing

Model-based testing is an automated process in which executable tests are derived from behavioral models of a system. Model checking verification technique to reveal errors all reachable states system can be generated as state space. In the literature, different approaches suggest using model checkers for model-based testing. checker explores possible states, so utilizing various paths state-space test cases seems promising solution. However, these suffer two main challenges. The first challenge space explosion, prevents generating by checker. second one redundant cases. Recently, several methods meta-heuristic and evolutionary have been proposed cope with problems. Therefore, exploring portion optimization approach detect objectives proper way manage explosion generate optimal suite least redundancy. this paper, method Bayesian algorithm (BOA), bed service-oriented systems. approach, set on starting initial leading satisfied. research, we implemented BOA three structures GROOVE toolset, open-source toolset designing graph transformation. Experimental results show that our solution generates better terms coverage speed case studies than existing approaches.