This book investigates the potential and limitations of using Generative AI (GenAI) in terms of quality and capability in agile web development projects using React. For this purpose, the Pipeline for Automated Code Generation from Backlog Items (PACGBI) was implemented and used in a case study to analyse the AI-generated code with a mix-method approach. The findings demonstrated the ability of GenAI to rapidly generate syntactically correct and functional code with Zero-Shot prompting. The PACGBI showcases the potential for GenAI to automate the development process, especially for tasks with low complexity. However, this research also identified challenges with code formatting, maintainability, and user interface implementation, attributed to the lack of detailed functional descriptions of the task and the appearance of hallucinations. Despite these limitations, the book underscores the significant potential of GenAI to accelerate the software development process and highlights the need for a hybrid approach that combines GenAI’s strengths with human expertise for complex tasks. Further, the findings provide valuable insights for practitioners considering GenAI integration into their development processes and set a foundation for future research in this field. The results regarding the quality and capability of AI-generated code, along with their practical implications, aim to aid practitioners in the decision-making process of adapting GenAI into their software development life cycle and further provide reference points for future research.

Pipeline for Automated Code Generation from Backlog Items (PACGBI): Analysis of Potentials and Limitations of Generative AI for Web Development (BestMasters)

Pipeline for Automated Code Generation from Backlog Items (PACGBI): Analysis of Potentials and Limitations of Generative AI for Web Development (BestMasters) PDF

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