15 citations · 21 across the 17 of their papers we have counts for
7 papers · 1 filter
Detecting Behavioral Changes in Python Refactoring Implementations with Foundation Models
Jonhnanthan Oliveira, Rohit Gheyi, Márcio Ribeiro +1
Python is a widely adopted programming language, valued for its simplicity and flexibility. However, automated refactoring for Python remains challenging, even though refactoring i…
Comprehending Python Repetition Structures: An Eye-Tracking Study with Novice Developers
José Júnior Silva da Costa, Rohit Gheyi, José Aldo Silva da Costa +1
Code comprehension is central to software maintenance and evolution, yet different Python repetition structures may impose distinct cognitive demands. We conducted a controlled eye…
AI-Conducted Interviews in Empirical Software Engineering: An Experience Report
Rohit Gheyi, Danyllo Albuquerque, Márcio Ribeiro +1
Semi-structured interviews are widely used in empirical software engineering (ESE), but they are resource-intensive and difficult to coordinate across schedules, locations, and nat…
An Empirical Study of Gemini 3 for Detecting Natural Language Test Smells in Manual Test Cases
Keila Lucas, Rohit Gheyi, Márcio Ribeiro +3
Manual testing, in which testers follow natural language instructions to validate system behavior, remains essential for uncovering issues that are difficult to capture with automa…
Foundation Models as Oracles for Refactoring Correctness Detection
Rohit Gheyi, Rian Melo, Jonhnanthan Oliveira +2
Refactoring tools in popular Integrated Development Environments (IDEs) can introduce unintended behavioral changes or compilation errors, a persistent challenge that undermines de…
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…
An Empirical Study of Foundation Models for Variability-Induced Compilation Errors in Configurable C Code
Rohit Gheyi, Lucas Albuquerque, Márcio Ribeiro +3
In configurable systems, conditional compilation can hide compilation errors under untested feature combinations. We investigate foundation models for detecting such errors and, in…