AI based Software Testing

dc.contributor.author	Khan, Saquib Ali
dc.contributor.author	Oshin, Nabilah Tabassum
dc.contributor.author	Musfique, Md Masum
dc.contributor.author	Nizam, Mahmuda
dc.contributor.author	Ahmed, Ishtiaque
dc.contributor.author	Hasan, Mahady
dc.date.accessioned	2023-10-30T09:44:09Z
dc.date.available	2023-10-30T09:44:09Z
dc.date.issued	2023-07
dc.identifier.uri	https://ar.iub.edu.bd/handle/123456789/621
dc.description.abstract	As the complexity of software applications continues to increase,software testing becomes more challenging and time-consuming.The use of artiﬁcialintelligence (AI) in software testing has emerged as a promising approach to address these challenges. AI-based software testing techniques leverage machine learning,natural language processing,and other AI technologies to automate the testing process,improve test coverage,and enhance the accuracy of test results.This paper provides an overview of AI-based software testing,including its beneﬁts and limitations,and discusses various techniques and tools used in this ﬁeld.The paper also highlights some of the current research and development eﬀorts in AI based software testing,as well as future directions and challenges.	en_US
dc.publisher	Independent University, Bangladesh	en_US
dc.subject	AI	en_US
dc.subject	software testing	en_US
dc.subject	machine learning	en_US
dc.subject	natural language processing	en_US
dc.subject	test automation	en_US
dc.subject	test coverage	en_US
dc.title	AI based Software Testing	en_US
dc.type	Article	en_US