Automatic software testing framework for all def-use with genetic algorithm

Abstract

The primary objective of automatic testing is to reduce the repetitive manual work and avoid redundancy such that end user gets error free Software. Testing in most of projects/Software has been manual, requiring high number of resources for a significantly large period of time resulting in high project cost and other glitches like efforts, cumbersome tests, and poor result maintenance. Getting most of it out with automation is a process of evaluating the test goals and matching the right tool for the Software/program e.g. choosing right tool and designing appropriate test cases. Several other researchers used numerous techniques to create test cases automatically. Many Algorithms which are nature inspired e.g. Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Genetic Algorithms (GA) etc. are used in research for automation of test case generation. In the current article, authors have used a method based on Genetic Algorithm (GA) to generate the test cases automatically. The key purpose of generating the test cases with the help of the genetic algorithm is to reduce time of input data.