Max Hort

M. Hort, J. M. Zhang, F. Sarro and M. Harman

Search-based Automatic Repair for Fairness and Accuracy in Decision-making Software

Empirical Software Engineering

M. Hort and L. Moonen

On a Sustainable Training of Large Language Models for Source Code

International Conference on Information and Communications Technology for Sustainability (ICT4S)

M. Astekin, M. Hort and L. Moonen

A Comparative Study on Large Language Models for Log Parsing

18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)

M. Astekin, M. Hort and L. Moonen

An Exploratory Study on How Non-Determinism in Large Language Models Affects Log Parsing

2nd International Workshop on Interpretability, Robustness, and Benchmarking in Neural Software Engineering (InteNSE)

F. V. Ruiz, A. Grishina, M. Hort and L. Moonen

A Novel Approach for Automatic Program Repair using Round-Trip Translation with Large Language Models

M. Hort, Z. Chen, J. M. Zhang, F. Sarro and M. Harman

Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey

ACM Journal on Responsible Computing

M. Hort, R. Moussa and F. Sarro

Multi-objective Search for Gender-fair and Semantically Correct Word Embeddings (HOP GECCO’23)

The Genetic and Evolutionary Computation Conference

M. Hort, A. Grishina and L. Moonen

An Exploratory Literature Study on Sharing and Energy Use of Language Models for Source Code

2023 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)

A. Grishina, M. Hort and L. Moonen

The EarlyBIRD Catches the Bug: On Exploiting Early Layers of Encoder Models for More Efficient Code Classification

ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2023)

A. Grishina, M. Hort and L. Moonen

The EarlyBIRD Catches the Bug: On Exploiting Early Layers of Encoder Models for More Efficient Code Classification