Generative Ai In Software Engineering
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Generative AI in Software Engineering
Author: Aguilar-Calderón, José Alfonso
language: en
Publisher: IGI Global
Release Date: 2025-06-13
Generative AI transforms the landscape of software engineering, enabling automation, creativity, and efficiency throughout development. By leveraging advanced machine learning models, like large language models and code generation tools, developers can automate code generation, streamline testing, and design software architectures. This shift accelerates development timelines and redefines the roles of engineers and the skills required in modern software teams. As generative AI evolves, its integration into software engineering raises important questions around reliability, security, and human-AI collaboration. Generative AI in Software Engineering explores the evolving role of generative AI in the software engineering landscape. It examines how AI accelerates software development, reduces costs, and enhances creativity, offering real-world benefits for businesses. This book covers topics such as quantum computing, visual intelligence, and environment science, and is a useful resource for business owners, computer engineers, academicians, researchers, and data scientists.
Generative AI for Effective Software Development
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.
Generative Analysis
Author: Jim Arlow
language: en
Publisher: Addison-Wesley Professional
Release Date: 2025-06-30
Learn Generative Analysis--a New Method of Object-Oriented Analysis--to Keep Pace with How Generative AI Is Transforming the Face of Software Engineering Generative AI is revolutionizing software engineering--many aspects of manual coding are becoming automated, and the skills needed by software engineers, developers, and analysts are evolving. Anyone who writes or works with code will need to produce precise analysis artifacts to feed the AI code-generation process. Enter generative analysis: a precise, structured way for software engineers, programmers, and analysts to transition to this new, AI-enhanced software engineering world. In Generative Analysis, experts Jim Arlow and Ila Neustadt leverage Literate Modeling, M++, and multivalent logic to lay out a step-by-step approach to object-oriented analysis that produces clear and unambiguous results suitable for further processing into code by generative AI systems such as Copilot, ChatGPT, and Gemini. Prepare for the challenge of the future by understanding the flexibility you already have at hand using generative analysis. Gain a new perspective on the shift to generative AI-based programming models Understand how generative analysis artifacts feed generative AIs to generate code and UML models Explore techniques that feed into and refine each other until a precise analysis definition of a software system is achieved Recognize milestones and end points to eliminate "analysis paralysis" Learn to work at the right level of abstraction to leverage the most power from generative AI Gain understanding from real-world, detailed examples of prompts and AI responses This guide teaches advanced, precise, and sophisticated analysis techniques that will allow you to thrive in the new world of software engineering with generative AI. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.