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AI-Driven Software Development Lifecycle Optimization
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Author(s): Pawan Kumar Goel (Raj Kumar Goel Institute of Technology, Ghaziabad, India), Km Komal (Meerut Institute of Technology, India)and Nitish Vashishth (Raj Kumar Goel Institute of Technology, Ghaziabad, India)
Copyright: 2024
Pages: 17
Source title:
Advancing Software Engineering Through AI, Federated Learning, and Large Language Models
Source Author(s)/Editor(s): Avinash Kumar Sharma (Sharda University, India), Nitin Chanderwal (University of Cincinnati, USA), Amarjeet Prajapati (Jaypee Institute of Information Technology, India), Pancham Singh (Ajay Kumar Garg Engineering College, Ghaziabad, India)and Mrignainy Kansal (Netaji Subhas University of Technology (NSUT), Delhi, India)
DOI: 10.4018/979-8-3693-3502-4.ch005
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Abstract
This research explores the integration of artificial intelligence (AI) into the software development lifecycle (SDLC) to optimize processes and address evolving industry demands. Against a backdrop of increased complexity in software projects, the study investigates historical context, emphasizing the imperative for AI infusion in SDLC. The primary objective is to illuminate how AI strategically enhances various SDLC stages, elucidating specific challenges it addresses. Employing a multifaceted approach, including literature reviews, case studies, and empirical analyses, the research showcases AI's role in automated code generation, intelligent code reviews, predictive maintenance, AI-powered testing, and dynamic resource allocation. Results demonstrate increased development speed, improved code quality, proactive issue identification, and efficient resource utilization. The chapter synthesizes key insights, underscoring AI's transformative impact on software development efficiency and product quality.
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