Bücher von Deepti Bala Mishra

Nowadays, we are using many semi or fully automated software applications in our day to day life. Qualitative, robust and trustworthy software are ensured by efficient testing. So, maintaining the quality of software is a crucial issue in our modern society. A huge number of software are developed for critical systems to support our everyday life including vending machines, automated traffic system and most electronic appliances. Developers are repeatedly trying to keep the software quality as high as possible through rigorous testing, which makes testing as the most important phase of Software Development Life Cycle (SDLC). In testing phase, different levels of testing are done for the Software Under Test (SUT), i.e. unit testing, integration testing, system testing and acceptance testing. Out of these testing techniques, unit testing which involves the testing process of a unit or a module, is the basis of all other testing techniques. During unit testing, if any error goes unidentified, then the error may propagate to the other modules.

This book provides awareness of different evolutionary methods used for automatic generation and optimization of test data in the field of software testing. While the book highlights on the foundations of software testing techniques, it also focuses on contemporary topics for research and development. This book covers the automated process of testing in different levels like unit level, integration level, performance level, evaluation of testing strategies, testing in security level, optimizing test cases using various algorithms, and controlling and monitoring the testing process etc. This book aids young researchers in the field of optimization of automated software testing, provides academics with knowledge on the emerging field of AI in software development, and supports universities, research centers, and industries in new projects using AI in software testing.Supports the advancement in the artificial intelligence used in software development;Advances knowledge on artificial intelligence based metaheuristic approach in software testing;Encourages innovation in traditional software testing field using recent artificial intelligence.*