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Название: Generative AI for Effective Software Development
Автор: Anh Nguyen-Duc, Pekka Abrahamsson, Foutse Khomh
Издательство: Springer
Год: 2024
Страниц: 346
Язык: английский
Формат: pdf (true), epub
Размер: 31.4 MB
The purpose of this book—Generative AI for Effective Software Development—is to provide a comprehensive, empirically grounded exploration of how generative AI is reshaping the landscape of software development across diverse environments and geographies. This book emphasizes the empirical evaluation of generative AI tools in real-world scenarios, offering insights into their practical efficacy, limitations, and impact on various aspects of software engineering. It focuses on the human aspect, examining how generative AI influences the roles, collaborations, and decision-making processes of developers from different countries and cultures. By presenting case studies, surveys, and interviews from various software development contexts, the book aims to offer a global perspective on the integration of generative AI, highlighting how these advanced tools are adapted to and influence diverse cultural, organizational, and technological environments. This multifaceted approach not only showcases the technological advancements in generative AI but also deeply considers the human element, ensuring that the narrative remains grounded in the practical realities of software developers worldwide. While Generative AI technologies encompass a wide range of data types, our cases focus mainly on LLMs with text and code generation. The evaluation is done with current models, such as Llama 2 or ChatGPT-4, acknowledging the current limitations associated with them.
Автор: Anh Nguyen-Duc, Pekka Abrahamsson, Foutse Khomh
Издательство: Springer
Год: 2024
Страниц: 346
Язык: английский
Формат: pdf (true), epub
Размер: 31.4 MB
The purpose of this book—Generative AI for Effective Software Development—is to provide a comprehensive, empirically grounded exploration of how generative AI is reshaping the landscape of software development across diverse environments and geographies. This book emphasizes the empirical evaluation of generative AI tools in real-world scenarios, offering insights into their practical efficacy, limitations, and impact on various aspects of software engineering. It focuses on the human aspect, examining how generative AI influences the roles, collaborations, and decision-making processes of developers from different countries and cultures. By presenting case studies, surveys, and interviews from various software development contexts, the book aims to offer a global perspective on the integration of generative AI, highlighting how these advanced tools are adapted to and influence diverse cultural, organizational, and technological environments. This multifaceted approach not only showcases the technological advancements in generative AI but also deeply considers the human element, ensuring that the narrative remains grounded in the practical realities of software developers worldwide. While Generative AI technologies encompass a wide range of data types, our cases focus mainly on LLMs with text and code generation. The evaluation is done with current models, such as Llama 2 or ChatGPT-4, acknowledging the current limitations associated with them.