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    "https://arxiv.org/abs/2312.14262",
    "arxiv:2312.14262"
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  "dcterms:title": [
    "Exploring the intersection of Generative AI and Software Development"
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  "dcterms:creator": [
    "Filipe Calegario",
    "Vanilson Burégio",
    "Francisco Erivaldo",
    "Daniel Moraes Costa Andrade",
    "Kailane Felix",
    "Nathalia Barbosa",
    "Pedro Lucas da Silva Lucena",
    "César França"
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  "dcterms:description": [
    "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."
  ],
  "dcterms:subject": [
    "cs.SE (arxiv)",
    "cs.AI (arxiv)"
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  "dcterms:language": [
    "en"
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  "dcterms:issued": [
    "2023-12-21"
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    "Retrieved from arXiv on 2026-10-09 in response to the search string “(all:\"artificial intelligence\" OR all:\"machine learning\" OR all:\"generative AI\" OR all:\"deep learning\" OR all:\"reinforcement learning\" OR all:\"large language model\") AND (all:\"AI concepts\" OR all:\"types of AI\" OR all:\"AI fundamentals\" OR all:\"recognizing AI\" OR all:\"recognising AI\" OR all:\"general versus narrow AI\" OR all:\"narrow AI\" OR all:\"general AI\" OR all:\"machine intelligence\" OR all:\"AI strengths and weaknesses\" OR all:\"traditional software\" OR all:\"rule-based systems\" OR all:\"introduction to AI\" OR all:\"introduction to artificial intelligence\" OR all:\"artificial intelligence introduction\" OR all:\"AI primer\" OR all:\"foundations of artificial intelligence\" OR all:\"overview of AI\" OR all:\"understanding AI\" OR all:\"history of AI\" OR all:\"AI essentials\" OR all:\"AI terminology\" OR all:\"metaphors for AI\" OR all:\"AI fundamental concepts\" OR all:\"AI key concepts\" OR all:\"philosophy of AI\" OR all:\"critical AI literacy\")”. arXiv served the resource and is not asserted to be its publisher or author.",
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