2 citations · 2 across the 2 of their papers we have counts for
4 papers · 1 filter
A Framework for Identifying, Categorizing, and Explaining Bias in AI-Generated Code
Manaal Basha, Aimee M. Ribeiro, Gema Rodriguez-Perez
As Large Language Models (LLMs) become integrated into software development workflows, concerns regarding unintentional biases in AI-generated code. Although evidence suggests thes…
CodeWatcher: IDE Telemetry Data Extraction Tool for Understanding Coding Interactions with LLMs
Manaal Basha, Aimeê M. Ribeiro, Jeena Javahar +2
Understanding how developers interact with code generation tools (CGTs) requires detailed, real-time data on programming behavior which is often difficult to collect without disrup…
Towards Understanding Barriers and Mitigation Strategies of Software Engineers with Non-traditional Educational and Occupational Backgrounds
Tavian Barnes, Ken Jen Lee, Cristina Tavares +2
The traditional path to a software engineering career usually involves a post-secondary diploma in Software Engineering, Computer Science, or a related field. However, many individ…
A Fine-grained Data Set and Analysis of Tangling in Bug Fixing Commits
Steffen Herbold, Alexander Trautsch, Benjamin Ledel +45
Context: Tangled commits are changes to software that address multiple concerns at once. For researchers interested in bugs, tangled commits mean that they actually study not only…