activity
20202026
most citedAcceptance Test Generation with Large Language Models: An Industrial Case Study

8 citations · 11 across the 7 of their papers we have counts for

collaborators

7 papers

cs.SE2026

ARIA - An Agentic Framework for Autonomous Testing of Infotainment Systems

António Azevedo, Bruno Lima, João Pascoal Faria

Automotive infotainment validation still relies on manual testing, slow, costly, and incompatible with agile releases and OTA updates. Scripted automation only partly helps: it cou…

cs.SE2026

APITestGenie: Generating Web API Tests from Requirements and API Specifications with LLMs

André Pereira, Bruno Lima, João Pascoal Faria

Modern software systems rely heavily on Web APIs, yet creating meaningful and executable test scripts remains a largely manual, time-consuming, and error-prone task. In this paper,…

cs.AI2026

AI in Insurance: Adaptive Questionnaires for Improved Risk Profiling

Diogo Silva, João Teixeira, Bruno Lima

Insurance application processes often rely on lengthy and standardized questionnaires that struggle to capture individual differences. Moreover, insurers must blindly trust users'…

cs.SE2025★ 2 cited

Streamlining Acceptance Test Generation for Mobile Applications Through Large Language Models: An Industrial Case Study

Pedro Luís Fonseca, Bruno Lima, João Pascoal Faria

Mobile acceptance testing remains a bottleneck in modern software development, particularly for cross-platform mobile development using frameworks like Flutter. While developers in…

cs.SE2025★ 8 cited

Acceptance Test Generation with Large Language Models: An Industrial Case Study

Margarida Ferreira, Luis Viegas, Joao Pascoal Faria +1

Large language model (LLM)-powered assistants are increasingly used for generating program code and unit tests, but their application in acceptance testing remains underexplored. T…

cs.SE2024★ 1 cited

APITestGenie: Automated API Test Generation through Generative AI

André Pereira, Bruno Lima, João Pascoal Faria

Intelligent assistants powered by Large Language Models (LLMs) can generate program and test code with high accuracy, boosting developers' and testers' productivity. However, there…

cs.SE2020

DCO Analyzer: Local Controllability and Observability Analysis and Enforcement of Distributed Test Scenarios

Bruno Lima, João Pascoal Faria

To ensure interoperability and the correct behavior of heterogeneous distributed systems in key scenarios, it is important to conduct automated integration tests, based on distribu…