A Random Walk Based Algorithm for Structural Test Case Generation

TL;DR

This paper introduces WalkTest, a random walk based algorithm for structural test case generation that improves efficiency and coverage over existing methods by treating test data generation as an optimization problem.

Contribution

The paper proposes a novel random walk based framework, WalkTest, for automated structural test case generation, enhancing search efficiency and coverage.

Findings

WalkTest outperforms random test and tabu search in coverage rate.

WalkTest achieves better running time in experimental evaluations.

Sorting test goals by solution cost improves search efficiency.

Abstract

Structural testing is a significant and expensive process in software development. By converting test data generation into an optimization problem, search-based software testing is one of the key technologies of automated test case generation. Motivated by the success of random walk in solving the satisfiability problem (SAT), we proposed a random walk based algorithm (WalkTest) to solve structural test case generation problem. WalkTest provides a framework, which iteratively calls random walk operator to search the optimal solutions. In order to improve search efficiency, we sorted the test goals with the costs of solutions completely instead of traditional dependence analysis from control flow graph. Experimental results on the condition-decision coverage demonstrated that WalkTest achieves better performance than existing algorithms (random test and tabu search) in terms of running time and coverage rate.