Path similarity-based scheduling sequence sorting for multi-path coverage of parallel programs

Abstract

Testing is an important way of improving the reliability of a software product. Uncertain communication statements in the message-passing parallel program can lead to uncertainty in the order of the execution of processes, which increases the difficulty of testing. Taking into consideration the influence of an uncertain process-execution order on the difficulty of covering target paths, in this paper, we focus on a method for sorting scheduling sequences in a message-passing parallel program to enable multi-path coverage and improve the efficiency of generating test data for multi-path coverage. To fulfill this task, we first execute a parallel program on each sample in each scheduling sequence to generate a path coverage matrix. Then, we produce a number of path similarity matrixes based on the similarity of each path in the coverage matrix and for each target. Next, we evaluate each scheduling sequence with respect to the characteristics of the similarity matrixes, based on which we sort the scheduling sequences. Finally, we generate test data for multi-path coverage by performing a random sampling of the sorted scheduling sequence set, which are evaluated using the APFD index. We applied the proposed method to nine benchmark parallel programs, and compared the performances of the random and traditional methods. The experimental results indicate that the proposed method has no effect on path coverage, but significantly reduces the number of program executions during the test and running time.