Automatic detection of infeasible paths in software testing

Abstract

A challenging problem in path-oriented test data generation is the presence of infeasible paths. Timely detecting these infeasible paths cannot only save test resources but also improve test efficiency. A popular method of detecting infeasible paths is to determine branch correlations, which is a difficult task and usually cannot be done timely and exactly. In this study, the authors propose a method of automatically determining the branch correlations of different conditional statements, therefore detecting infeasible paths. First, some theorems are given to determine branch correlations based on the probabilities of the conditional distribution corresponding to different branches' outcome (i.e. true or false); then, the maximum likelihood estimation is employed to obtain the values of these probabilities; finally, infeasible paths are detected according to branch correlations. The authors apply the proposed method in some typical programs, and the results show that the proposed method can accurately detect infeasible paths. The achievement provides an effective and automatic method of detecting infeasible paths, which is significant in improving the efficiency of software testing.

A UML model-based approach to detect infeasible paths

“…If an infeasible path is found, then the test data generation process for the infeasible path is terminated immediately, thereby avoiding any further effort. Gong and Yao (2010) propose a dynamic technique using branch correlations, which may not be determined timely and accurately by static analysis (Bodík et al, 1997b). For this reason, Gong and Yao (2010) combine static and dynamic analysis and hence, collect sample data of reasonable size containing the outcomes of branches.…”

Mutant reduction based on dominance relation for weak mutation testing

“…However, to determine the feasibility of a mutant branch, we need to employ appropriate approaches. In this paper, we utilize the method proposed in [42]. However, this method cannot guarantee that all the feasible mutant branches of a program are detected.…”

“…In structural testing, Ghiduk and Girgis reduced the statements needed to cover by only covering the non-dominated ones [19]. Gong and Yao identified infeasible paths according to the correlations among branches to save valuable testing resources [42]. Correlations are also helpful to mutation testing.…”

Aware Time in Bug Fix—A Novel Automatic Test Case Selection for Prioritization of Version Control

“…Gong et al [9] have inaugurated a novel technique so as to automatically get the branch correlations of dissimilar constrained statements and recognize infeasible paths. In the beginning, many theorems were detailed in order to spot the branch correlations on account of probabilities of the conditional distribution equivalent to various branches result (i.e.…”