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Generative Analysis
Jim Arlow, Ila Neustadt
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Naturwissenschaften, Medizin, Informatik, Technik / Anwendungs-Software
Beschreibung
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 "e;analysis paralysis"e; 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.
![Cover "e;Looks Good to Me"e;](https://cdn.libreka.de/cover/796438d1-f461-4add-878c-3933b75dc776/m ""e;Looks Good to Me"e;")
