Abstract: The present disclosure discloses a defect location method and device based on coverage information, the method including: characterizing program structure information and test case coverage information of a target program in a graph to obtain a graph-characterized structure; generating a node attribute sequence and an adjacency matrix based on the graph-characterized structure; and inputting the node attribute sequence and the adjacency matrix to a trained graph neural network model, so that the graph neural network model outputs a suspicious degree list of the target program based on the node attribute sequence and the adjacency matrix. Through the graph-based unified information characterization, the coverage information can be saved without loss and compression, and the structure information may also be considered, thereby improving the accuracy of defect location.

Abstract: The present disclosure discloses a defect location method and device based on coverage information, the method including: characterizing program structure information and test case coverage information of a target program in a graph to obtain a graph-characterized structure; generating a node attribute sequence and an adjacency matrix based on the graph-characterized structure; and inputting the node attribute sequence and the adjacency matrix to a trained graph neural network model, so that the graph neural network model outputs a suspicious degree list of the target program based on the node attribute sequence and the adjacency matrix. Through the graph-based unified information characterization, the coverage information can be saved without loss and compression, and the structure information may also be considered, thereby improving the accuracy of defect location.