1,721,016 research outputs found
How Beginning Programmers and Code LLMs (Mis)read Each Other
No full textSupplemental Materials for:
Sydney Nguyen, Hannah McLean Babe, Yangtian Zi, Arjun Guha, Carolyn Jane Anderson, and Molly Q Feldman. 2024. How Beginning Programmers and Code LLMs (Mis)read Each Other. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI ’24), May 11–16, 2024, Honolulu, HI, USA. ACM, New York, NY, USA. https://doi.org/10.1145/3613904.364270
StudentEval Dataset
No full textProject for the StudentEval benchmark.
The paper associated with this benchmark is:
Hannah McLean Babe, Sydney Nguyen, Yangtian Zi, Arjun Guha, Molly Q. Feldman, and Carolyn Jane Anderson. 2024. StudentEval: A Benchmark of Student-Written Prompts for Large Language Models of Code. In Findings of the Association for Computational Linguistics.
Associated analysis code can be found here: https://github.com/Wellesley-EASEL-lab/StudentEval.
model_results contains the results of benchmarking 5 code generation models on this dataset: StarCoderBase, SantaCoder, StarChat-Alpha, Replit-Code-V1, and GPT-3.5-Turbo-0301
[CODE] WasmFX OOPSLA23 Artifact
No full textThis artifact contains the instructions and source code to reproduce the experiments in Section 5.1 of the paper: Luna Phipps-Costin, Andreas Rossberg, Arjun Guha, Daan Leijen, Daniel Hillerström, KC Sivaramakrishnan, Matija Pretnar, Sam Lindley, "Continuing WebAssembly with Effect Handlers", Proc. ACM Program. Lang. 7(OOPSLA2), 2023.Hillerström, D. (2023). WasmFX OOPSLA23 Artifact. Zenodo. https://doi.org/10.5281/zenodo.833296
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
``I Would Have Written My Code Differently'': Beginners Struggle to Understand LLM-Generated Code
No full textSupplemental Materials for: Yangtian Zi, Luisa Li, Arjun Guha, Carolyn Jane Anderson, and Molly Q
Feldman. 2025. “I Would Have Written My Code Differently”: Beginners
Struggle to Understand LLM-Generated Code. In 33rd ACM International
Conference on the Foundations of Software Engineering (FSE Companion ’25),
June 23–28, 2025, Trondheim, Norway. ACM, New York, NY, USA, 14 pages.
https://doi.org/10.1145/3696630.373166
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Do Machine Learning Models Produce TypeScript Types That Type Check? (Artifact)
Get PDFType migration is the process of adding types to untyped code to gain assurance at compile time. TypeScript and other gradual type systems facilitate type migration by allowing programmers to start with imprecise types and gradually strengthen them. However, adding types is a manual effort and several migrations on large, industry codebases have been reported to have taken several years. In the research community, there has been significant interest in using machine learning to automate TypeScript type migration. Existing machine learning models report a high degree of accuracy in predicting individual TypeScript type annotations. However, in this paper we argue that accuracy can be misleading, and we should address a different question: can an automatic type migration tool produce code that passes the TypeScript type checker?
We present TypeWeaver, a TypeScript type migration tool that can be used with an arbitrary type prediction model. We evaluate TypeWeaver with three models from the literature: DeepTyper, a recurrent neural network; LambdaNet, a graph neural network; and InCoder, a general-purpose, multi-language transformer that supports fill-in-the-middle tasks. Our tool automates several steps that are necessary for using a type prediction model, including (1) importing types for a project’s dependencies; (2) migrating JavaScript modules to TypeScript notation; (3) inserting predicted type annotations into the program to produce TypeScript when needed; and (4) rejecting non-type predictions when needed.
We evaluate TypeWeaver on a dataset of 513 JavaScript packages, including packages that have never been typed before. With the best type prediction model, we find that only 21% of packages type check, but more encouragingly, 69% of files type check successfully
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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