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Generative AI for Effective Software Development

Overview of attention for book
Generative AI for Effective Software Development
Springer Nature Switzerland

Table of Contents

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    Book Overview
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    Chapter 1 An Overview on Large Language Models
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    Chapter 2 Comparing Proficiency of ChatGPT and Bard in Software Development
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    Chapter 3 DAnTE: A Taxonomy for the Automation Degree of Software Engineering Tasks
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    Chapter 4 ChatGPT Prompt Patterns for Improving Code Quality, Refactoring, Requirements Elicitation, and Software Design
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    Chapter 5 Requirements Engineering Using Generative AI: Prompts and Prompting Patterns
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    Chapter 6 Advancing Requirements Engineering Through Generative AI: Assessing the Role of LLMs
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    Chapter 7 Generative AI for Software Development: A Family of Studies on Code Generation
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    Chapter 8 BERTVRepair: On the Adoption of CodeBERT for Automated Vulnerability Code Repair
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    Chapter 9 ChatGPT as a Full-Stack Web Developer
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    Chapter 10 Transforming Software Development with Generative AI: Empirical Insights on Collaboration and Workflow
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    Chapter 11 How Can Generative AI Enhance Software Management? Is It Better Done than Perfect?
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    Chapter 12 Value-Based Adoption of ChatGPT in Agile Software Development: A Survey Study of Nordic Software Experts
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    Chapter 13 Early Results from a Study of GenAI Adoption in a Large Brazilian Company: The Case of Globo
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    Chapter 14 Generating Explanations for AI-Powered Delay Prediction in Software Projects
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    Chapter 15 Classifying User Intent for Effective Prompt Engineering: A Case of a Chatbot for Startup Teams
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    Chapter 16 Toward Guiding Students: Exploring Effective Approaches for Utilizing AI Tools in Programming Courses
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