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With ongoing software development, artificial intelligence (AI) is transforming the software development lifecycle (SDLC). The transformation improves decision-making and automation of processes in all stages of development, from planning to maintenance, especially for technologically advanced projects. This review synthesizes evidence from twelve studies on applying AI and generative AI in software development models.
The following experiments duly demonstrate the implementation of AI in software development activities, from providing code support to executing testing, security improvement, process management tasks of project management, creating much documentation, and automating the deployment process. One of the surprising discoveries is that the prediction and generation function greatly boosts the productivity of a project with fewer human task-centric errors and quicker product release timing for technology projects. Despite significant progress in this field, persistent challenges remain. These challenges range from maintaining ethical standards to effectively managing large, interconnected data, ensuring consistent accuracy across diverse contexts, and enhancing model transparency.
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"AI-Powered Software Development: A Systematic Review of Artificial Intelligence in the Software Development Lifecycle", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 10, page no.b174-b178, October-2025, Available :http://www.ijrti.org/papers/IJRTI2510120.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator