This paper introduces MENTOR, a semantic automated program repair (APR) framework designed to fix faulty student programs. MENTOR validates repairs through execution on a test …
Thrilled to share that our paper on MENTOR, a semantic automated program repair (APR) framework that fixes student programs and highlights faulty statements, has been accepted by …
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 …
This paper proposes InvAASTCluster, a novel approach for program clustering that uses dynamically generated program invariants to cluster semantically equivalent IPAs.
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 …
I am very happy to share that our paper on program clustering has been accepted at the JSS December 2025!! 🎉
In my talk, I will present MENTOR, a semantic automated program repair (APR) framework designed to provide Automated Feedback for Introductory Programming Exercises.
Nesta palestra, irei apresentar o sistema MENTOR, uma ferramenta de reparação automática de programas orientada para fornecer feedback automatizado para exercícios introdutórios de …
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. 🎉 🎉
This PhD thesis presents MENTOR, a semantic automated program repair (APR) framework designed to provide Automated Feedback for Introductory Programming Exercises.
I am extremely happy to share that, I have been awarded my PhD summa cum laude in Computer Science and Engineering!
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 …
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 …
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 …
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 …