Directed Search Based on Improved Whale Optimization Algorithm for Test Case Prioritization

With the advent of information age, iterative speed software update is gradually accelerating which makes development severely limited by testing. Test case prioritization an effective way to accelerate testing progress. introduction heuristic algorithm this task, processing efficiency test cases has been greatly improved. However, overcome shortcomings slow convergence and easy fall into local optimum, improved whale optimization proposed for prioritization. Firstly, a model called n-dimensional directed search space established swarm intelligence algorithm. Secondly, enhanced applied while backtracking behavior conducted individuals when hitting wall. In addition, separate storage Pareto second also designed filter optimal solutions multi-objective tasks. Finally, both single-objective experiments are carried out open source projects real-world projects, respectively. The results show that using more conducive decisions with fast speed.