15 citations · 16 across the 3 of their papers we have counts for
5 papers
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…
Investigating the Performance of Small Language Models in Detecting 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 crucial for uncovering issues not easily captured by automation. However,…
Agentic LMs: Hunting Down Test Smells
Rian Melo, Pedro Simões, Rohit Gheyi +5
Test smells reduce test suite reliability and complicate maintenance. While many methods detect test smells, few support automated removal, and most rely on static analysis or mach…
Evaluating Large Language Models in Detecting Test Smells
Keila Lucas, Rohit Gheyi, Elvys Soares +2
Test smells are coding issues that typically arise from inadequate practices, a lack of knowledge about effective testing, or deadline pressures to complete projects. The presence…
A Catalog of Transformations to Remove Smells From Natural Language Tests
Manoel Aranda, Naelson Oliveira, Elvys Soares +6
Test smells can pose difficulties during testing activities, such as poor maintainability, non-deterministic behavior, and incomplete verification. Existing research has extensivel…