Automatic Generation of Data Flow Test Paths using a Genetic Algorithm

Abstract

Path testing a program involves generating all paths through the program, and finding a set of program inputs that will execute every path. Since it is impossible to cover all paths in a program, path testing can be relaxed by selecting a subset of all executable paths that fulfill a certain path selection criterion and finding test data to cover it. The automatic generation of such test paths leads to more test coverage paths thus resulting in efficient and effective testing strategy. This paper presents a structural-oriented technique that uses a genetic algorithm (GA) for automatic generation of a set of test paths that cover the all-uses criterion. In the case of programs that have loops, the proposed technique generates paths according to the ZOT-subset criterion, which requires paths that traverse loops zero, one and two times. The proposed GA uses a binary vector as a chromosome to represent the edges in the DD-graph of the program under test. The set of paths generated by the proposed GA can be passed to a test data generation tool to find program inputs that will execute them. Experiments have been carried out to evaluate the effectiveness of the proposed GA compared to the random test path generation technique. General TermsSoftware Engineering, Software Testing.

Automatic Data Flow Test Paths Generation using the Genetical Swarm Optimization Technique

“…This section describes a proposed GA for automatic test path generation [33]. The algorithm searches for test paths that satisfy the all-uses criterion.…”

“…(A test path is said to cover a def-use path, if it includes a subpath, which starts at the def-node and ends at the use node of the def-use path and does not pass through its killing nodes.) The fitness value fitness_value(vi) for each chromosome vi (i = 1, …, POPSIZE) is calculated as follows [16]:…”

“…Genetic algorithms (GAs) have been successfully used in software testing activities such as test data generation, (see e.g., [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19]). But very little attention has been paid to use GAs in path testing [20].…”

“…60.87 % * COVERED DEF-USE PATHS: 2,4,9 Path 4: ************* SELECTED ************* * Traversed Path: 5,6,7,8,9,10,14,15,16,17,18,19,31,32, * DEF-USE COVERAGE:…”

“…110111001110001 e0,e1,e3,e4,e10,e8,e9,e5,e14, (Path 5) 6. 110111001010011 e0,e1,e3,e4,e10,e8,e13,e5,e14, (Path 6) Path 1 ************* SELECTED ************* * Traversed Path: 5,6,7,8,9,10,14,15,16,17,18,19,20,21,22,23,24,29,30,19,31,32, * DEF-USE COVERAGE:…”