Abstract: Selection of test case is a standard testing technique to opt a subset of existing test cases for execution, due to the limited budget and other necessary constraints. The key objective of this study is automatic generation and optimization of test cases using bio-inspired Genetic Algorithm (GA). These search optimization techniques lead to global best solution. These algorithms are used to generate test paths and then optimize them. The case study on telemedicine simulation system is being presented here using use case diagrams, activity diagram and sequence diagram. Activity diagram graph and sequence diagram graph show test paths which are being optimized using Genetic algorithm. This study presents a novel approach for generation of test cases using UML. Our approach consists of converting the all UML diagrams into graph and integrated to form System Under Test (SUT). From the graphs different control flow series also called test cases are recognized and then optimized using Genetic algorithm. The system graph is then traversed to generate test paths which are being optimized using GA. To explore the efficacy of our approach, we performed an empirical study using MATLAB programs with manifold paths and other parameters. Our results indicate that generation and optimization of test case is achieved efficiently in much less time.
Anju Bala and Rajender Singh Chhillar, 2019. Automatic Generation and Optimization of Test Cases Using Genetic Algorithm with UML Diagram. Journal of Engineering and Applied Sciences, 14: 1590-1600.