By optimizing the execution order of test cases, test case prioritization technology can improve the efficiency of software testing. It is an important research topic for enhanced software and regression testing. Aiming at the demand-based test case prioritization problem, a solution method based on ant colony algorithm is proposed. Based on different test case sequence evaluation strategies, two different implementations of the method are given. Firstly, according to the characteristics of black-box software testing, a general demand-based test case sequence evaluation index is designed. Secondly, the concept of test case aspiration is proposed, which was used to define the distance between test cases. Then, the main design strategies such as pheromone updating strategy, optimal solution set updating strategy, and local optimal solution mutation strategy are given. Finally, the two implementations (distance-based approach and index-based approach) are achieved. The experimental results show that this method had a good global search ability, and has better overall effect than other methods such as particle swarm algorithm, genetic algorithm and random testing.