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The increasing complexity of real-world programs necessitates the automation of software testing. As a basic problem in software testing, the automation of path-wise test data generation is especially important, which is in essence a constraint satisfaction problem solved by search strategies. In this paper, the search algorithm branch and bound is introduced and optimized to tackle the problem of path-wise test data generation. The optimized branching operation is fulfilled by a dynamic variable ordering algorithm with a heuristic rule to break ties. The optimized bounding operation is accomplished by analyzing the results of interval arithmetic. In order to facilitate the search methods, the solution space is represented as state space. Experimental results prove the effectiveness of the optimized branching and bounding operations, and show that the proposed method outperformed some other methods used in test data generation. The results also demonstrate that the proposed method is applicable in engineering.

Optimized Branch and Bound for Path-wise Test Data Generation