From the 1 of 14 linked papers with an AI index.
14 papers
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
The paper reports on using a customized AI system (MyGPT) to conduct short, self‑administered, voice‑based interviews in empirical software engineering studies, evaluating particip…
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…
An Empirical Study of Gemini 3 for Detecting Natural Language Test Smells in Manual Test Cases
Keila Lucas, Rohit Gheyi, Márcio Ribeiro +4
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…
Vulnerability Detection with Interprocedural Context in Multiple Languages: Assessing Effectiveness and Cost of Modern LLMs
Kevin Lira, Baldoino Fonseca, Davy BaÃa +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…