AI and Software Engineering: Rapid Process Improvement through Advanced Techniques

Authors

  • Meghasai Bodimani Department of Computer Science, University of Missouri, Kansas City, USA Author

Keywords:

Artificial Intelligence, Machine Learning, Privacy Mechanisms, Network

Abstract

In recent years, a variety of research have effectively applied machine learning approaches across a broad range of industries. This led to the creation of a large range of deep learning models, each adapted to a specific purpose in software development. There are various ways in which the software development business may benefit from employing deep learning models. Nowadays, nothing is more vital than consistently testing and maintaining software. Software engineers are responsible for a broad variety of duties during the lifespan of a software system, from original design to final delivery to clients via cloud-based platforms. It is evident from this list that all jobs involve meticulous planning and the availability of a range of materials. A developer may study a range of resources, including internal corporate resources, external websites with important programming material, and code repositories, before creating and testing a solution to the current issue. Finding out what went into building the  recommended is what this inquiry is all about. Based on user feedback, this system examines the  recommended's effectiveness and proposes methods to enhance the programme.

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Published

13-03-2021

How to Cite

“AI and Software Engineering: Rapid Process Improvement through Advanced Techniques”. Journal of Science & Technology, vol. 2, no. 1, Mar. 2021, pp. 95-119, https://www.thesciencebrigade.com/jst/article/view/69.

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