79 citations · 388 across the 25 of their papers we have counts for
27 papers
Getting Python Types Right with RightTyper
Juan Altmayer Pizzorno, Emery D. Berger
Python type annotations enable static type checking, but most code remains untyped because manual annotation is time-consuming and tedious. Past approaches to automatic type infere…
Flowco: Rethinking Data Analysis in the Age of LLMs
Stephen N. Freund, Brooke Simon, Emery D. Berger +1
Conducting data analysis typically involves authoring code to transform, visualize, analyze, and interpret data. Large language models (LLMs) are now capable of generating such cod…
Effective LLM-Driven Code Generation with Pythoness
Kyla H. Levin, Kyle Gwilt, Emery D. Berger +1
The advent of large language models (LLMs) has paved the way for a new era of programming tools with both significant capabilities and risks, as the generated code lacks guarantees…
It's Not Easy Being Green: On the Energy Efficiency of Programming Languages
Nicolas van Kempen, Hyuk-Je Kwon, Dung Tuan Nguyen +1
Does the choice of programming language affect energy consumption? Previous highly visible studies have established associations between certain programming languages and energy co…
From Perception to Decision: Assessing the Role of Chart Types Affordances in High-Level Decision Tasks
Yixuan Li, Emery D. Berger, Minsuk Kahng +1
Visualization design influences how people perceive data patterns, yet most research focuses on low-level analytic tasks, such as finding correlations. The extent to which these pe…
ChatDBG: Augmenting Debugging with Large Language Models
Kyla H. Levin, Nicolas van Kempen, Emery D. Berger +1
Debugging is a critical but challenging task for programmers. This paper proposes ChatDBG, an AI-powered debugging assistant. ChatDBG integrates large language models (LLMs) to sig…