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How to Adapt Machine Learning into Software Testing

Authors:
Mesut Durukal

Keywords: artificial intelligence; machine learning; software testing; test automation.

Abstract:
Software testing cycles have several difficulties, such as coverage of a dense scope in a limited time, due to dynamic product development approaches. Researchers try to use new techniques to overcome these difficulties. This paper presents the utilization of Machine Learning (ML) in software testing stages with its effects and outcomes. Practical applications and advantages are analyzed. The main goal is to make insights about what can be done in different stages of software testing by employing ML and discuss benefits and risks.

Pages: 44 to 50

Copyright: Copyright (c) IARIA, 2019

Publication date: November 24, 2019

Published in: conference

ISSN: 2308-4316

ISBN: 978-1-61208-755-9

Location: Valencia, Spain

Dates: from November 24, 2019 to November 28, 2019