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A Framework for Leveraging Artificial Intelligence in Software Development

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Detalhes bibliográficos
Resumo:Due to recent breakthroughs in Artificial Intelligence, we have seen an increase in its capabilities, which has also bolstered an unprecedent potential for automation, as these technologies can also automate or assist in tasks innate to human intellect and creativity. As a result, these technologies are expected to redefine many professional occupations, increasing their overall productivity, along with numerous other advantages elucidated in this study. This has fueled an increase in enthusiasm for AI, both from academia and corporations, as can be seen in the contemporary increase in articles investigating the inclusion of AI in many fields, and in AI-based products available on the market, respectively. However, there is a shortage of prescriptive tools that advise entities on their inclusion in the software development process. To address this gap, this study employs a thorough literature review along with Design Science Research to uncover the way these two fields mutually interact. The main result of this dissertation is a novel framework that advises on the most appropriate algorithms for the different phases of the software development life cycle.
Autores principais:Martins, Diogo de Oliveira Bento
Assunto:Artificial Intelligence Software Development Software Development Lifecycle Machine Learning Automation SDG 9 - Industry, innovation and infrastructure
Ano:2024
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso aberto
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL
Descrição
Resumo:Due to recent breakthroughs in Artificial Intelligence, we have seen an increase in its capabilities, which has also bolstered an unprecedent potential for automation, as these technologies can also automate or assist in tasks innate to human intellect and creativity. As a result, these technologies are expected to redefine many professional occupations, increasing their overall productivity, along with numerous other advantages elucidated in this study. This has fueled an increase in enthusiasm for AI, both from academia and corporations, as can be seen in the contemporary increase in articles investigating the inclusion of AI in many fields, and in AI-based products available on the market, respectively. However, there is a shortage of prescriptive tools that advise entities on their inclusion in the software development process. To address this gap, this study employs a thorough literature review along with Design Science Research to uncover the way these two fields mutually interact. The main result of this dissertation is a novel framework that advises on the most appropriate algorithms for the different phases of the software development life cycle.