商品描述
This book provides a comprehensive, empirically grounded exploration of how Generative AI is reshaping the landscape of software development. It emphasizes the empirical evaluation of Generative AI tools in real-world scenarios, offering insights into their practical efficacy, limitations, and impact. By presenting case studies, surveys, and interviews from various software development contexts, the book offers 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 book is structured to provide a comprehensive understanding of Generative AI and its transformative impact on the field of software engineering. The book is divided into five parts, each focusing on different aspects of Generative AI in software development. As an introduction, Part 1 presents the fundamentals of Generative AI adoption. Part 2 is a collection of empirical studies and delves into the practical aspects of integrating Generative AI tools in software engineering, with a focus on patterns, methodologies, and comparative analyses. Next, Part 3 presents case studies that showcase the application and impact of Generative AI in various software development contexts. Part 4 then examines how Generative AI is reshaping software engineering processes, from collaboration and workflow to management and agile development. Finally, Part 5 looks towards the future, exploring emerging trends, future directions, and the role of education in the context of Generative AI.
The book offers diverse perspectives as it compiles research and experiences from various countries and software development environments. It also offers non-technical discussions about Generative AI in management, teamwork, business and education. This way, it is intended for both researchers in software engineering and for professionals in industry who want to learn about the impactof Generative AI on software development.
商品描述(中文翻譯)
本書提供了一個全面且以實證為基礎的探索，探討生成式人工智慧（Generative AI）如何重塑軟體開發的格局。它強調在真實世界情境中對生成式人工智慧工具的實證評估，提供對其實際效能、限制和影響的見解。透過展示來自各種軟體開發背景的案例研究、調查和訪談，本書提供了全球視角，突顯這些先進工具如何適應並影響多元的文化、組織和技術環境。
本書的結構旨在提供對生成式人工智慧及其對軟體工程領域變革性影響的全面理解。全書分為五個部分，每個部分聚焦於生成式人工智慧在軟體開發中的不同面向。作為引言，第一部分介紹了生成式人工智慧採用的基本原則。第二部分則是實證研究的彙編，深入探討在軟體工程中整合生成式人工智慧工具的實際面向，重點在於模式、方法論和比較分析。接下來，第三部分展示了案例研究，展示生成式人工智慧在各種軟體開發情境中的應用和影響。第四部分則檢視生成式人工智慧如何重塑軟體工程流程，從協作和工作流程到管理和敏捷開發。最後，第五部分展望未來，探討新興趨勢、未來方向以及教育在生成式人工智慧背景下的角色。
本書匯集了來自不同國家和軟體開發環境的研究和經驗，提供多元的觀點。它還針對管理、團隊合作、商業和教育中的生成式人工智慧進行非技術性的討論。因此，本書旨在為軟體工程的研究者以及希望了解生成式人工智慧對軟體開發影響的業界專業人士提供參考。
作者簡介
Pekka Abrahamsson is a Full Professor of Software Engineering at Tampere University, Finland. He heads the Applied AI Research Centre (AI HUB) and directs GPT-labs, where large language models are developed and tested. He is a pioneer in the field of agile software development and his current research interests focus on advancing software engineering through generative AI technologies. He is a member of the Finnish Academy of Science and Letters and has an h-index of 64.
Foutse Khomh is a Full Professor of Software Engineering at Polytechnique Montréal, a Canada CIFAR AI Chair on Trustworthy Machine Learning Software Systems, an NSERC Arthur B. McDonald Fellow, and an FRQ-IVADO Research Chair on Software Quality Assurance for Machine Learning Applications. He has conducted pioneer work on improving the trustworthiness of artificial intelligence-based software systems and exercised strong leadership in bringing together the software engineering community and the industry, to develop novel theories, techniques, and tools for improving the quality assurance of artificial intelligence-based software systems.
作者簡介(中文翻譯)
Anh Nguyen-Duc 是南東挪威大學的軟體工程全職教授。他在軟體工程領域的高排名期刊、會議和研討會上發表了超過150篇經過同行評審的論文，涵蓋了軟體創業、軟體工程教育和人工智慧倫理等主題。他領導多個關於生成式人工智慧在軟體開發和教育中的應用的研究。目前，他正在推動多項全國性倡議，專注於生成式人工智慧在軟體開發和教育中的應用。
Pekka Abrahamsson 是芬蘭坦佩雷大學的軟體工程全職教授。他負責應用人工智慧研究中心（AI HUB），並指導 GPT-labs，該實驗室專注於大型語言模型的開發和測試。他是敏捷軟體開發領域的先驅，目前的研究興趣集中在通過生成式人工智慧技術推進軟體工程。他是芬蘭科學與文學院的成員，並擁有64的 h-index。
Foutse Khomh 是蒙特婁理工學院的軟體工程全職教授，加拿大 CIFAR 人工智慧信任機器學習軟體系統主席，NSERC Arthur B. McDonald Fellow，以及 FRQ-IVADO 機器學習應用軟體質量保證研究主席。他在提高基於人工智慧的軟體系統的可信度方面進行了開創性工作，並在將軟體工程社群與產業結合方面展現了強大的領導力，以發展新理論、新技術和新工具，改善基於人工智慧的軟體系統的質量保證。
