collaborators

7 papers

cs.SE2026

Evaluating Language Models on Cross-Language Code Functional Equivalence

Hui Sun, Anderson Uchôa, Rohit Gheyi +1

Background: Large Language Models (LLMs) have demonstrated strong performance across a variety of code-understanding tasks, leading many to believe that they can reason about progr…

cs.SE2026

Vulnerability Detection with Interprocedural Context in Multiple Languages: Assessing Effectiveness and Cost of Modern LLMs

Kevin Lira, Baldoino Fonseca, Davy Baía +2

Large Language Models (LLMs) have been a promising way for automated vulnerability detection. However, most prior studies have explored the use of LLMs to detect vulnerabilities on…

cs.SE2026

Beyond Resolution Rates: Behavioral Drivers of Coding Agent Success and Failure

Tural Mehtiyev, Wesley Assunção

Coding agents represent a new paradigm in automated software engineering, combining the reasoning capabilities of Large Language Models (LLMs) with tool-augmented interaction loops…

cs.SE2026

Where are the Hidden Gems? Applying Transformer Models for Design Discussion Detection

Lawrence Arkoh, Daniel Feitosa, Wesley K. G. Assunção

Design decisions are at the core of software engineering and appear in Q\&A forums, mailing lists, pull requests, issue trackers, and commit messages. Design discussions spanning a…

cs.SE2026

Test Code Review in the Era of GitHub Actions: A Replication Study

Hui Sun, Yinan Wu, Wesley K. G. Assunção +1

Test code is indispensable in software development, ensuring the correctness of production code and supporting maintainability. Nonetheless, errors or omissions in the test code ca…

cs.SE2025

Refactoring Bug-Inducing: Improving Defect Prediction with Code Change Tactics Analysis

Feifei Niu, Junqian Shao, Christoph Mayr-Dorn +5

Just-in-time defect prediction (JIT-DP) aims to predict the likelihood of code changes resulting in software defects at an early stage. Although code change metrics and semantic fe…