Test Case Prioritization Based on Simulation Annealing Algorithm

Using intelligent technology to solve the test optimization problem has become one of the recent research hotspots. Aiming at the test case prioritization problem, an intelligent approach based on simulated annealing algorithm is proposed. First, described the general expression of the requirement-based test case prioritization problem, and gave the test case evaluation index and the definition of test case distance. Secondly, the solution strategy based on simulated annealing algorithm was proposed, and designed its implementation process, algorithm elements and basic steps. The algorithm elements include state expression method, domain definitions and searching method, cooling functions and heat balance method, annealing ending method, etc. Finally, some experiments were carried out to verify the effectiveness of the algorithm. Experimental results show that the intelligent approach based on simulated annealing algorithm has a good global optimization capability, and is better than random testing in overall effect.