📄📄📄 3 Papers accepted @ FLoC 2026!! 🎉🎉🎉
Excited to share that three of our papers have been accepted at FLoC 2026, covering automated feedback for Prolog education, data-driven mutation testing for Prolog, and …
Solving MaxSAT Problems from Natural Language Descriptions with LLMs and PySAT
In this paper, we study a neuro-symbolic approach in which an LLM translates a natural language description of an optimisation problem into executable Python code using PySAT. The …
MENTOR: Fixing Introductory Programming Assignments With Formula-Based Fault Localization and LLM-Driven Program Repair @ INESC-ID
In this talk, I will present my PhD work on MENTOR, a semantic automated program repair framework designed to provide meaningful feedback for introductory programming assignments.
Honored to Receive the INESC-ID Best PhD Student 2025 Award!! 🏆
I am thrilled to share that I was the recipient of the INESC-ID Best PhD Student 2025 Award, which recognises my PhD research conducted at INESC-ID (2020 -- 2024).
From Logic to Learning: Rethinking Programming for the AI Era @ DEI, IST-UL
In this talk, I will present approaches that leverage the precision of formal logic and the adaptability of learning-based models to enable intelligent code generation, automated …
Counterexample Guided Program Repair Using Large Language Models and MaxSAT-based Fault Localization @ IIIA-CSIC
In this talk I will present a hybrid method to automated repair of C code, using Maximum Satisfiability (MaxSAT)-based fault localization, CFaults, to localize bugs and LLMs to …
MENTOR: Automated Feedback for Introductory Programming Exercises @ FCT-UNL
In my talk, I will present MENTOR, a semantic automated program repair (APR) framework designed to provide Automated Feedback for Introductory Programming Exercises.
MENTOR: Feedback Automático para ExercĂcios IntrodutĂłrios de Programação (Portuguese) @ VoA 2025
Nesta palestra, irei apresentar o sistema MENTOR, uma ferramenta de reparação automática de programas orientada para fornecer feedback automatizado para exercĂcios introdutĂłrios de …
🏆 Honored to Receive the Vencer o Adamastor (VoA) Award 2025!! 🏆
I am thrilled to share that I was the recipient of the Vencer o Adamastor 2025 prize, which acknowledges innovative contributions by young scientists in Portugal. 🎉 🎉
MENTOR: Automated Feedback for Introductory Programming Exercises
This PhD thesis presents MENTOR, a semantic automated program repair (APR) framework designed to provide Automated Feedback for Introductory Programming Exercises.
Counterexample Guided Program Repair Using Zero-Shot Learning and MaxSAT-based Fault Localization @ OutSystems
In this talk I will present our novel approach that combines the strengths of both FM-based fault localization and LLMs, via zero-shot learning, to enhance Automated Program …
Counterexample Guided Program Repair Using Zero-Shot Learning and MaxSAT-based Fault Localization
In this paper, we propose a novel approach that combines the strengths of both FM-based fault localization and LLMs, via zero-shot learning, to enhance APR for IPAs. Our method …
📄 Paper accepted @ AAAI 2025!! 🎉
I am very happy to share that our paper that combines the strengths of both MaxSAT-based fault localisation and Large Language Models, via zero-shot learning, to enhance automated …
LLM-Driven Automated Program Repair Using MaxSAT-based Fault Localization @ Oxford
In this talk I will present a hybrid method to automated repair of C code, using Maximum Satisfiability (MaxSAT)-based fault localization, CFaults, to localize bugs and LLMs to …
Automated Feedback for Introductory Programming Exercises
Delivering valuable and personalised feedback to students remains one of the greatest challenges in programming education, particularly in courses with large enrollments. Providing …