Automated test generation from graph models is essential to model-based testing. In this type of testing, graph coverage ensures test suite strength but also results in long test cases that take time to execute on the system under test. We propose a novel optimization-driven method, DJPlus, which generates reduced test suites while satisfying given graph-based test requirements. We implement DJPlus and show the feasibility of edge-pair criterion, a stronger coverage criterion than vertex or edge criteria, on four realistic systems, while prime path criterion poses scalability issues. Our evaluation reveals that the alternative methods generate 2 to 26 times more redundant test steps than DJPlus and DJPlus decreases test execution times by reducing the number of test steps. These results show that DJPlus is a positive step towards tackling the challenges of model-based testing at an industrial scale.

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