@article{MAKHILLJEAS201914517530,
    title = {Automatic Generation and Optimization of Test Cases Using Genetic Algorithm with
UML Diagram},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {14},
    number = {5},
    pages = {1590-1600},
    year = {2019},
    issn = {1816-949x},
    doi = {jeasci.2019.1590.1600},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2019.1590.1600},
    author = {Anju and},
    keywords = {Telemedicine diagnosis system,Genetic algorithm,use case,sequence diagram,activity diagram,MATLAB},
    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.}
    }