activity
20212024
most citedMASC: A Tool for Mutation-Based Evaluation of Static Crypto-API Misuse Detectors

6 citations · 17 across the 12 of their papers we have counts for

collaborators

12 papers

cs.SE20241 cited

When Quantum Meets Classical: Characterizing Hybrid Quantum-Classical Issues Discussed in Developer Forums

Jake Zappin, Trevor Stalnaker, Oscar Chaparro +1

Recent advances in quantum computing have sparked excitement that this new computing paradigm could solve previously intractable problems. However, due to the faulty nature of curr…

cs.SE20241 cited

Measuring Emergent Capabilities of LLMs for Software Engineering: How Far Are We?

Conor O'Brien, Daniel Rodriguez-Cardenas, Alejandro Velasco +2

The adoption of Large Language Models (LLMs) across multiple contexts has sparked interest in understanding how scaling model size might lead to behavioral changes, as LLMs can exh…

cs.SE2024

Semantic GUI Scene Learning and Video Alignment for Detecting Duplicate Video-based Bug Reports

Yanfu Yan, Nathan Cooper, Oscar Chaparro +2

Video-based bug reports are increasingly being used to document bugs for programs centered around a graphical user interface (GUI). However, developing automated techniques to mana…

cs.SE2024

"The Law Doesn't Work Like a Computer": Exploring Software Licensing Issues Faced by Legal Practitioners

Nathan Wintersgill, Trevor Stalnaker, Laura A. Heymann +2

Most modern software products incorporate open source components, which requires compliance with each component's licenses. As noncompliance can lead to significant repercussions,…

cs.SE20244 cited

Which Syntactic Capabilities Are Statistically Learned by Masked Language Models for Code?

Alejandro Velasco, David N. Palacio, Daniel Rodriguez-Cardenas +1

This paper discusses the limitations of evaluating Masked Language Models (MLMs) in code completion tasks. We highlight that relying on accuracy-based measurements may lead to an o…

cs.SE2023

ACER: An AST-based Call Graph Generator Framework

Andrew Chen, Yanfu Yan, Denys Poshyvanyk

We introduce ACER, an AST-based call graph generator framework. ACER leverages tree-sitter to interface with any language. We opted to focus on generators that operate on abstract…