Exploring the influence of AI on software engineering practice

Topic Description

Generative AI (Gen AI) is starting to have an impact on software engineering practice. This doctoral project aims to answer one of more of the following research questions:

How do software engineers use Gen AI to solve real world problems?
What problems do they face when using these tools?
How do they go about overcoming the problems that they meet?
How does the use of Gen AI affect team collaboration and knowledge sharing?
Do developers become overly dependent on AI for solutions, potentially reducing skill sharing and collective problem-solving?
In which phases of software engineering do developers most frequently integrate Gen AI, and what specific impacts does it have on productivity, code quality, and project outcomes in each phase?

Accompanying questions are: what are the attitudes that engineers have towards the current generation of tools, and what risks do they perceive with using them?

This project aims to carry out in depth qualitative research of software engineering across one or more workplaces or setting. Working with an experienced supervision team, research students may also wish to carry out quantitative research to complements any qualitative study that may be carried out.

Skills Required

Although ideally you should have a first degree in Computer Science or Software Engineering, you may have also completed a postgraduate conversion degree in Computing or a closely related subject. Ideally, you should be familiar with, or be able to become familiar with current software engineering practices. Applicants who are currently working within industry, or have significant industrial experience are particularly welcome to apply.

You should have an understanding and appreciation of quantitative and qualitative research methods. You should also be willing to study topics that are outside of your discipline.

Background Reading

This is an emerging and fast moving topic. Some early articles and surveys which relate to this subject are as follows:

Adams, B. and Zimmermann, T. (2024) Proceedings of the 1st ACM International Conference on AI-Powered Software. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3664646.3664773

Choudhuri, R. et al. (2024) How Far Are We? The Triumphs and Trials of Generative AI in Learning Software Engineering. In Proceedings of the IEEE/ACM 46th International Conference on Software Engineering (ICSE '24). Association for Computing Machinery, New York, NY, USA, Article 184, 1–13. https://doi.org/10.1145/3597503.3639201

GitHub (2024) Survey: AI in software development https://opencode.md/en/news/github-2024-survey-ai-in-software-development/

Klemmer, J.H. et al. (2024) Using AI Assistants in Software Development: A Qualitative Study on Security Practices and Concerns. Available at: https://doi.org/10.48550/arxiv.2405.06371

Mendes, W., Souza, S. and De Souza, C. (2024) "You're on a bicycle with a little motor": Benefits and Challenges of Using AI Code Assistants. In Proceedings of the 2024 IEEE/ACM 17th International Conference on Cooperative and Human Aspects of Software Engineering (CHASE '24). Association for Computing Machinery, New York, NY, USA, 144–152. https://doi.org/10.1145/3641822.3641882

Nguyen, N. and Nadi, S. (2022) An empirical evaluation of GitHub copilot's code suggestions. In Proceedings of the 19th International Conference on Mining Software Repositories (MSR '22). Association for Computing Machinery, New York, NY, USA, 1–5. https://doi.org/10.1145/3524842.3528470