A critical review of Artificial Bee Colony optimizing technique in software testing

Any software development is governed by implementation of all steps in a Software Development Life Cycle in an effective manner. Out of all the steps in SDLC, the testing phase plays an important role in determining whether the software is developed in the most efficient and correct manner, since it states the measure of correctness of the product and also verifies whether the software is completely acceptable to the user or not. Testing phase can be achieved successfully either through manual means or can be automated by various testing tools. Manual testing will obviously take more time and may also lead to many errors that can remain unidentified. However, automatic testing ensures that all bugs are identified and all errors are removed with the help of various meta-heuristic techniques such as Genetic Algorithms with Mutation Testing, Artificial Bee Colony Algorithm and Ant Colony Optimization. The Artificial Bee Colony works on the intelligent synchronization of bees where they help each other to find nodes in the software code with promising results. This approach has been discussed in detail. The proposed approach is more scalable, requires less computation time and is easy to understand and implement.