Generative AI for Effective Software Development

Anh Nguyen-Duc is a Full Professor of Software Engineering at University of South Eastern Norway. He has more than 150 peer-reviewed publications in high-ranked journals, conferences, and workshops in software engineering field, including software startups, software engineering education and AI Ethics. He leads several works on generative AI for software development and education. Currently, he spearheads multiple national initiatives focusing on generative AI for both software development and education.

Pekka Abrahamsson is a Full Professor of Software Engineering at Tampere University, Finland. He heads the Applied AI Research Centre (AI HUB) and directs GPT-labs, where large language models are developed and tested. He is a pioneer in the field of agile software development and his current research interests focus on advancing software engineering through generative AI technologies. He is a member of the Finnish Academy of Science and Letters and has an h-index of 64.

Foutse Khomh is a Full Professor of Software Engineering at Polytechnique Montréal, a Canada CIFAR AI Chair on Trustworthy Machine Learning Software Systems, an NSERC Arthur B. McDonald Fellow, and an FRQ-IVADO Research Chair on Software Quality Assurance for Machine Learning Applications. He has conducted pioneer work on improving the trustworthiness of artificial intelligence-based software systems and exercised strong leadership in bringing together the software engineering community and the industry, to develop novel theories, techniques, and tools for improving the quality assurance of artificial intelligence-based software systems.

Part 1: Fundamental on Generative AI.- 1. An Overview of Large Language Models by.- Part 2: Patterns and Tools for the Adoption of Generative AI in Software Engineering.- 2. Comparing Proficiency of ChatGPT and Bard in Software Development .- 3. DAnTE: a taxonomy for the automation degree of software engineering tasks.- 4. ChatGPT Prompt Patterns for Improving Code Quality, Refactoring, Requirements Elicitation, and Software Design.- 5. Requirements Engineering using GenAI: Prompts and Prompting Patterns.- 6. Advancing Requirements Engineering through Generative AI: Assessing the Role of LLMs.- Part 3: Generative AI in Software Development: Case Studies.- 7. Generative AI for Software Development: A Family of Case Studies on Code Generation Tasks.- 8. On the adoption of CodeBERT for automated vulnerability code repair.- 9. ChatGPT as a fullstack web developer.- Part 4: Generative AI in Software Engineering Processes.- 10. Transforming Software Development with Generative AI: Empirical Insights on Collaboration and Workflow.- 11. How Can Generative AI Enhance Software Management? Is it better done than perfect?.- 12. Value-based Adoption of ChatGPT in Agile Software Development: A Survey Study of Nordic Software Experts.- 13. Early results from a study of GenAI adoption in a large Brazilian company: the case of Globo.- Part 5: Future Directions and Education.- 14. Generating Explanations for AI-powered Delay Prediction in Software Projects.- 15. Classifying User Intent for Effective Prompt Engineering: A Case of a Chatbot for Startup Teams.- 16. Toward Guiding Students: Exploring Effective Approaches to Utilize AI Tools in Programming Courses.