69 citations · 132 across the 12 of their papers we have counts for
8 papers · 1 filter
LeakageDetector 2.0: Analyzing Data Leakage in Jupyter-Driven Machine Learning Pipelines
Owen Truong, Terrence Zhang, Arnav Marchareddy +4
In software development environments, code quality is crucial. This study aims to assist Machine Learning (ML) engineers in enhancing their code by identifying and correcting Data…
ChatGPT for Code Refactoring: Analyzing Topics, Interaction, and Effective Prompts
Eman Abdullah AlOmar, Luo Xu, Sofia Martinez +4
Large Language Models (LLMs), such as ChatGPT, have become widely popular and widely used in various software engineering tasks such as refactoring, testing, code review, and progr…
Exploring Prompt Patterns in AI-Assisted Code Generation: Towards Faster and More Effective Developer-AI Collaboration
Sophia DiCuffa, Amanda Zambrana, Priyanshi Yadav +3
The growing integration of AI tools in software development, particularly Large Language Models (LLMs) such as ChatGPT, has revolutionized how developers approach coding tasks. How…
On the Structure and Semantics of Identifier Names Containing Closed Syntactic Category Words
Christian D. Newman, Anthony Peruma, Eman Abdullah AlOmar +8
Identifier names are crucial components of code, serving as primary clues for developers to understand program behavior. This paper investigates the linguistic structure of identif…
10 quick tips for making your software outlive your job
Richard Littauer, Greg Wilson, Jan Ainali +19
Loss of key personnel has always been a risk for research software projects. Key members of the team may have to step away due to illness or burnout, to care for a family member, f…
SCALAR: A Part-of-speech Tagger for Identifiers
Christian D. Newman, Brandon Scholten, Sophia Testa +10
The paper presents the Source Code Analysis and Lexical Annotation Runtime (SCALAR), a tool specialized for mapping (annotating) source code identifier names to their corresponding…