A Survey on Software Testing Techniques using Genetic Algorithm
It addresses software testing challenges for the software industry, but it is incremental as it reviews existing GA approaches rather than proposing new methods.
This paper surveys the use of Genetic Algorithms (GA) to tackle issues in software testing, such as test case generation and prioritization, aiming to improve efficiency and reduce effort, time, and cost.
The overall aim of the software industry is to ensure delivery of high quality software to the end user. To ensure high quality software, it is required to test software. Testing ensures that software meets user specifications and requirements. However, the field of software testing has a number of underlying issues like effective generation of test cases, prioritisation of test cases etc which need to be tackled. These issues demand on effort, time and cost of the testing. Different techniques and methodologies have been proposed for taking care of these issues. Use of evolutionary algorithms for automatic test generation has been an area of interest for many researchers. Genetic Algorithm (GA) is one such form of evolutionary algorithms. In this research paper, we present a survey of GA approach for addressing the various issues encountered during software testing.