Testing Graph Searching Based Path Planning Algorithms by Metamorphic Testing
Jiantao Zhang, Zheng Zheng, Beibei Yin, Kun Qiu, Yang Liu · 2019
Path planning algorithms play critical roles in the systems of robots and unmanned aerial vehicles (UAVs). However, it is always difficult to verify the correctness of the implementations for such algorithms because the "planning oracles", the expected planning results, are usually hard to be obtained for complicate planning tasks. To improve software reliability, in this paper, we present a testing technique for verifying the implementations of graph searching based path planning algorithms deployed on robots and UAVs. Our approach is based on the technique of Metamorphic Testing, which has been shown considerable effectiveness in alleviating the absence of Oracle problems. According to the characteristics of graph searching based path planning problem, we present a framework to systematically design metamorphic relations. Based on the framework, six categories of metamorphic relations are proposed. We conduct the empirical analysis on 21 implements of three different path planning algorithms applied in a released business software project. The experimental results show that our approach can effectively detect dormant faults.