Titlebook: Generative AI for Effective Software Development; Anh Nguyen-Duc,Pekka Abrahamsson,Foutse Khomh Book 2024 The Editor(s) (if applicable) an

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ChatGPT Prompt Patterns for Improving Code Quality, Refactoring, Requirements Elicitation, and Softw language models (LLMs) to automate common software engineering activities, such as ensuring code is decoupled from third-party libraries and creating API specifications from lists of requirements. This chapter provides two contributions to research on using LLMs for software engineering. First, it

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Advancing Requirements Engineering Through Generative AI: Assessing the Role of LLMsre requirements. Despite the importance of RE, it remains a challenging process due to the complexities of communication, uncertainty in the early stages, and inadequate automation support. In recent years, large language models (LLMs) have shown significant promise in diverse domains, including nat

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Generative AI for Software Development: A Family of Studies on Code Generationare engineering (SE). This chapter explores the benefits and challenges of utilizing generative AI for different activities in the software development cycle that involve code generation. We review different approaches leveraging generative AI, either independently or in combination with traditional

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BERTVRepair: On the Adoption of CodeBERT for Automated Vulnerability Code Repairnd threats to national security. Traditional methods of detecting and addressing software security issues are often time-consuming and resource-intensive. This research aims to examine the effectiveness of generative-based methods, particularly those leveraging generative (DL) models like CodeBERT,

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ChatGPT as a Full-Stack Web Developers of ChatGPT to actually implement a complete system rather than a few code snippets. This chapter reports the firsthand experiences from a graduate-level student project where a real-life software platform for financial sector was implemented from scratch by using ChatGPT for all possible software

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How Can Generative AI Enhance Software Management? Is It Better Done than Perfect?rent impact levels if the adaptations are not tailored for the specific teams’ needs and circumstances. For instance, agile developers sometimes oversimplify crucial Agile steps, such as estimating needed effort for a specific task or lack of explicit assessment of the criteria for “Definition of Do

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