Exploring the intersection of Generative AI and Software Development
December 21, 2023 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Filipe Calegario, Vanilson BurΓ©gio, Francisco Erivaldo, Daniel Moraes Costa Andrade, Kailane Felix, Nathalia Barbosa, Pedro Lucas da Silva Lucena, CΓ©sar FranΓ§a
arXiv ID
2312.14262
Category
cs.SE: Software Engineering
Cross-listed
cs.AI
Citations
5
Venue
arXiv.org
Last Checked
4 months ago
Abstract
In the ever-evolving landscape of Artificial Intelligence (AI), the synergy between generative AI and Software Engineering emerges as a transformative frontier. This whitepaper delves into the unexplored realm, elucidating how generative AI techniques can revolutionize software development. Spanning from project management to support and updates, we meticulously map the demands of each development stage and unveil the potential of generative AI in addressing them. Techniques such as zero-shot prompting, self-consistency, and multimodal chain-of-thought are explored, showcasing their unique capabilities in enhancing generative AI models. The significance of vector embeddings, context, plugins, tools, and code assistants is underscored, emphasizing their role in capturing semantic information and amplifying generative AI capabilities. Looking ahead, this intersection promises to elevate productivity, improve code quality, and streamline the software development process. This whitepaper serves as a guide for stakeholders, urging discussions and experiments in the application of generative AI in Software Engineering, fostering innovation and collaboration for a qualitative leap in the efficiency and effectiveness of software development.
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