An optimization algorithm applied to the class integration and test order problem

作者：Zhang, Yanmei; Jiang, Shujuan^*; Wang, Xingya; Chen, Ruoyu; Zhang, Miao

来源：Soft Computing, 2019, 23(12): 4239-4253.

DOI：10.1007/s00500-018-3077-1

• Particle swarm optimization
• Intelligent optimization algorithms
• Integration testing
• Object-oriented software

In recent years, many intelligent optimization algorithms are applied to the class integration and test order problem and it has been proved that they can efficiently solve this problem. In this paper, the particle swarm optimization algorithm is applied to the class integration and test order problem. First, the initial population (test orders) is generated randomly and each test order is taken as a particle. Here, we map particles to one-dimensional space; then, a particle (an integration test order) can be represented by a position in the one-dimensional space; finally, the optimal particle (integration test order) is selected by particle swarm optimization algorithm. Also, whether the precedence table of dependency relations is introduced as the constraints in evolution can impact the effect of particle swarm optimization approach is validated through experiment. The experimental results show that the particle swarm optimization algorithm is encouraging in solving class integration and test order problem.

• 出版日期2019-6
• 单位中国矿业大学（北京）; 桂林电子科技大学