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- research-articleOctober 2024
Knowledge Transfer from High-Resource to Low-Resource Programming Languages for Code LLMs
- Federico Cassano,
- John Gouwar,
- Francesca Lucchetti,
- Claire Schlesinger,
- Anders Freeman,
- Carolyn Jane Anderson,
- Molly Q Feldman,
- Michael Greenberg,
- Abhinav Jangda,
- Arjun Guha
Proceedings of the ACM on Programming Languages (PACMPL), Volume 8, Issue OOPSLA2Article No.: 295, Pages 677–708https://doi.org/10.1145/3689735Over the past few years, Large Language Models of Code (Code LLMs) have started to have a significant impact on programming practice. Code LLMs are also emerging as building blocks for research in programming languages and software engineering. However, ...
- research-articleJune 2024
Non-Expert Programmers in the Generative AI Future
CHIWORK '24: Proceedings of the 3rd Annual Meeting of the Symposium on Human-Computer Interaction for WorkArticle No.: 15, Pages 1–19https://doi.org/10.1145/3663384.3663393Generative AI is rapidly transforming the practice of programming. At the same time, our understanding of who writes programs, for what purposes, and how they program, has been evolving. By facilitating natural-language-to-code interactions, large ...
- research-articleMay 2024
How Beginning Programmers and Code LLMs (Mis)read Each Other
CHI '24: Proceedings of the 2024 CHI Conference on Human Factors in Computing SystemsArticle No.: 651, Pages 1–26https://doi.org/10.1145/3613904.3642706Generative AI models, specifically large language models (LLMs), have made strides towards the long-standing goal of text-to-code generation. This progress has invited numerous studies of user interaction. However, less is known about the struggles and ...
- proceedingOctober 2023
SPLASH-E 2023: Proceedings of the 2023 ACM SIGPLAN International Symposium on SPLASH-E
The SPLASH-E symposium is a forum for researchers and educators to discuss the intersection of education and the core SPLASH research areas: systems, programming languages, and their applications. We investigate how to deliver systems and programming ...
- research-articleJuly 2023
MultiPL-E: A Scalable and Polyglot Approach to Benchmarking Neural Code Generation
- Federico Cassano,
- John Gouwar,
- Daniel Nguyen,
- Sydney Nguyen,
- Luna Phipps-Costin,
- Donald Pinckney,
- Ming-Ho Yee,
- Yangtian Zi,
- Carolyn Jane Anderson,
- Molly Q Feldman,
- Arjun Guha,
- Michael Greenberg,
- Abhinav Jangda
IEEE Transactions on Software Engineering (ISOF), Volume 49, Issue 7Pages 3675–3691https://doi.org/10.1109/TSE.2023.3267446Large language models have demonstrated the ability to generate both natural language and programming language text. Although contemporary code generation models are trained on corpora with several programming languages, they are tested using benchmarks ...
- research-articleJanuary 2021
How We Write with Crowds
Proceedings of the ACM on Human-Computer Interaction (PACMHCI), Volume 4, Issue CSCW3Article No.: 229, Pages 1–31https://doi.org/10.1145/3432928Writing is a common task for crowdsourcing researchers exploring complex and creative work. To better understand how we write with crowds, we conducted both a literature review of crowd-writing systems and structured interviews with designers of such ...
- research-articleOctober 2019
Towards answering “Am I on the right track?” automatically using program synthesis
SPLASH-E 2019: Proceedings of the 2019 ACM SIGPLAN Symposium on SPLASH-EPages 13–24https://doi.org/10.1145/3358711.3361626Students learning to program often need help completing assignments and understanding why their code does not work as they expect it to. One common place where they seek such help is at teaching assistant office hours. We found that teaching assistants ...
- research-articleApril 2018
Automatic Diagnosis of Students' Misconceptions in K-8 Mathematics
CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing SystemsPaper No.: 264, Pages 1–12https://doi.org/10.1145/3173574.3173838K-8 mathematics students must learn many procedures, such as addition and subtraction. Students frequently learn "buggy' variations of these procedures, which we ideally could identify automatically. This is challenging because there are many possible ...
