Selection Optimization of Test Path Based on Bidirectional Breadth First Search and Binary Artificial Fish Swarm Algorithm

Abstract

Testing technology is significant for improving the usability and security of a system. The test point is an important source of obtaining test information. The test layout of the system is usually based on the concept of test point. In this paper, the defects of the current test point concept to solve the problem of fault isolation in the system are analyzed, then the concept of the test path is proposed and the special point of the test layout using the test path is expounded. Then, according to the concept of test path, a bidirectional breadth first search algorithm is proposed, which completes the node search of the test path that can be detected by the specific test path, and the correlation matrix is built based on the node set. According to the problem of the current optimization selection algorithm based on the correlation matrix, the traditional artificial fish swarm algorithm is improved based the optimization model of the test path to propose a binary artificial fish swarm algorithm to optimize the test path. Finally, the effectiveness of the binary fish swarm algorithm is verified by the case.