"You're on a bicycle with a little motor": Benefits and Challenges of Using AI Code Assistants

Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, Bryan Wilie, Holy Lovenia, Ziwei Ji, Tiezheng Yu, Willy Chung, Quyet V. Do, Yan Xu, and Pascale Fung. 2023. A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity. arXiv:2302.04023 [cs.CL]

Shraddha Barke, Michael B James, and Nadia Polikarpova. 2023. Grounded copilot: How programmers interact with code-generating models. Proceedings of the ACM on Programming Languages 7, OOPSLA1 (2023), 85--111.

Christian Bird, Denae Ford, Thomas Zimmermann, Nicole Forsgren, Eirini Kalliamvakou, Travis Lowdermilk, and Idan Gazit. 2023. Taking Flight with Copilot: Early Insights and Opportunities of AI-Powered Pair-Programming Tools. Queue 20, 6 (jan 2023), 35--57.

Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020. Language models are few-shot learners. Advances in neural information processing systems 33 (2020), 1877--1901.

Margaret Burnett, Scott D Fleming, Shamsi Iqbal, Gina Venolia, Vidya Rajaram, Umer Farooq, Valentina Grigoreanu, and Mary Czerwinski. 2010. Gender differences and programming environments: across programming populations. In Proceedings of the 2010 ACM-IEEE international symposium on empirical software engineering and measurement. 1--10.

Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Kaijie Zhu, Hao Chen, Linyi Yang, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, et al. 2023. A survey on evaluation of large language models. arXiv preprint arXiv:2307.03109 (2023).

Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Josh Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, and Wojciech Zaremba. 2021. Evaluating large language models trained on code. arXiv preprint arXiv:2107.03374 (2021).

Cleidson R. B. de Souza, Geema Rodríguez-Pérez, Manaal Basha, Dongwook Yoon, and Ivan Beschastnikh. 2024. The fine balance between helping with your job and taking it: AI Code Assistants come to the fore (To appear). IEEE Software (2024), 6.

Jianyang Deng and Yijia Lin. 2022. The benefits and challenges of ChatGPT: An overview. Frontiers in Computing and Intelligent Systems 2, 2 (2022), 81--83.

Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Wen tau Yih, Luke Zettlemoyer, and Mike Lewis. 2023. InCoder: A Generative Model for Code Infilling and Synthesis. arXiv:2204.05999 [cs.SE]

Nat Friedman. 2021. Introducing GitHub Copilot: your AI pair programmer. URL https://github.blog/2021-06-29-introducing-github-copilot-ai-pair-programmer (2021).

Muhammad Usman Hadi, R Qureshi, A Shah, M Irfan, A Zafar, MB Shaikh, N Akhtar, J Wu, and S Mirjalili. 2023. A survey on large language models: Applications, challenges, limitations, and practical usage. TechRxiv (2023).

Ellen Jiang, Edwin Toh, Alejandra Molina, Kristen Olson, Claire Kayacik, Aaron Donsbach, Carrie J Cai, and Michael Terry. 2022. Discovering the syntax and strategies of natural language programming with generative language models. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. 1--19.

Nelson F. Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang. 2023. Lost in the Middle: How Language Models Use Long Contexts. arXiv:2307.03172 [cs.CL]

JOSEPH E. MCGRATH. 1995. METHODOLOGY MATTERS: DOING RESEARCH IN THE BEHAVIORAL and SOCIAL SCIENCES. In Readings in Human-Computer Interaction, RONALD M. BAECKER, JONATHAN GRUDIN, WILLIAM A.S. BUXTON, and SAUL GREENBERG (Eds.). Morgan Kaufmann, 152--169.

Arghavan Moradi Dakhel, Vahid Majdinasab, Amin Nikanjam, Foutse Khomh, Michel C. Desmarais, and Zhen Ming (Jack) Jiang. 2023. GitHub Copilot AI pair programmer: Asset or Liability? Journal of Systems and Software 203 (2023), 111734.

Nhan Nguyen and Sarah Nadi. 2022. An Empirical Evaluation of GitHub Copilot's Code Suggestions. In Proceedings of the 19th International Conference on Mining Software Repositories (Pittsburgh, Pennsylvania) (MSR '22). Association for Computing Machinery, New York, NY, USA, 1--5.

Hammond Pearce, Baleegh Ahmad, Benjamin Tan, Brendan Dolan-Gavitt, and Ramesh Karri. 2022. Asleep at the Keyboard? Assessing the Security of GitHub Copilot's Code Contributions. In 2022 IEEE Symposium on Security and Privacy (SP). 754--768.

Everett M. Rogers. 2003. Diffusion of innovations (5th ed.). Free Press, New York, NY [u.a.]. 576 pages.

Mohammed Latif Siddiq and Joanna C. S. Santos. 2022. SecurityEval Dataset: Mining Vulnerability Examples to Evaluate Machine Learning-Based Code Generation Techniques. In Proceedings of the 1st International Workshop on Mining Software Repositories Applications for Privacy and Security (Singapore, Singapore) (MSR4P&S 2022). Association for Computing Machinery, New York, NY, USA, 29--33.

Anselm Strauss and Juliet Corbin. 1998. Basics of qualitative research techniques. (1998).

Priyan Vaithilingam, Tianyi Zhang, and Elena L Glassman. 2022. Expectation vs. experience: Evaluating the usability of code generation tools powered by large language models. In Chi conference on human factors in computing systems extended abstracts. 1--7.

Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems 30 (2017).

Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, and Denny Zhou. 2023. Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. arXiv:2201.11903 [cs.CL]

Justin D. Weisz, Michael Muller, Stephanie Houde, John Richards, Steven I. Ross, Fernando Martinez, Mayank Agarwal, and Kartik Talamadupula. 2021. Perfection Not Required? Human-AI Partnerships in Code Translation. In 26th International Conference on Intelligent User Interfaces (College Station, TX, USA) (IUI '21). Association for Computing Machinery, New York, NY, USA, 402--412.

Frank F. Xu, Bogdan Vasilescu, and Graham Neubig. 2022. In-IDE Code Generation from Natural Language: Promise and Challenges. ACM Trans. Softw. Eng. Methodol. 31, 2, Article 29 (mar 2022), 47 pages.

Burak Yetistiren, Isik Ozsoy, and Eray Tuzun. 2022. Assessing the Quality of GitHub Copilot's Code Generation. In Proceedings of the 18th International Conference on Predictive Models and Data Analytics in Software Engineering (Singapore, Singapore) (PROMISE 2022). Association for Computing Machinery, New York, NY, USA, 62--71.

Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al. 2023. A survey of large language models. arXiv preprint arXiv:2303.18223 (2023).

Albert Ziegler, Eirini Kalliamvakou, X Alice Li, Andrew Rice, Devon Rifkin, Shawn Simister, Ganesh Sittampalam, and Edward Aftandilian. 2022. Productivity assessment of neural code completion. In Proceedings of the 6th ACM SIGPLAN International Symposium on Machine Programming. 21--29.