Research Hub
Analyzing and documenting internet health and trustworthy AI to help shape a human-centered internet.
Latest Research
-
A Comparison of Conversational Models and Humans in Answering Technical Questions: the Firefox Case
16 gener de 2026Marco Castelluccio, Daniel Coutinho, Anita Sarma, Marco Gerosa, Caio Barbosa, Alessandro Garcia, Igor Steinmacher, Joao CorreiaThe study evaluates Retrieval-Augmented Generation (RAG) with LLMs for assisting Mozilla Firefox developers by comparing human responses, standard LLM, and RAG-enhanced LLM on real developer queries.
-
Using LLMs to Bridge the Gaps in QA Test Plans at Firefox
16 gener de 2026Suhaib Mujahid, Marco Castelluccio, John Pangas, Ahmad AbdellatifThe study explores using LLMs to automatically generate test plans for Firefox features, aiming to reduce the manual effort and blind spots in traditional QA planning.
-
A Dataset of Performance Measurements and Alerts from Mozilla (Data Artifact)
16 gener de 2026Diego Elias Costa, Suhaib Mujahid, Marco Castelluccio, Gregory Mierzwinski, Mohamed Bilel BesbesThe paper introduces a publicly available dataset from Mozilla Firefox that addresses the lack of real-world data for studying performance regressions, combining performance measurements, expert-validated alerts, and rich metadata.
