Max


Simula Research Laboratory
Oslo, Norway
Email: maxh[at]simula.no

GitHub • LinkedIn

About

I am an MSCA Research Fellow at Simula Research Laboratory, supervised by Professor Leon Moonen.

My research interests lie on the intersection of machine learning and software engineering, non-functional optimization, and fairness. In particular, I focus on the use of large language models trained on source code to detect and repair software vulnerabilities.

Publications

  • Enhanced Fairness Testing via Generating Effective Initial Individual Discriminatory Instances (TOSEM’25)
  • The Art of Repair: Optimizing Iterative Program Repair with Instruction-Tuned Models (EASE’25) [pdf]
  • Semantic-Preserving Transformations as Mutation Operators: A Study on Their Effectiveness in Defect Detection (MUTATION’25) [pdf]
  • Codehacks: A Dataset of Adversarial Tests For Competitive Programming Problems Obtained From Codeforces (ICST’25) [pdf]
  • Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey (JRC’24) [pdf]
  • Fairness Testing: A Comprehensive Survey and Analysis of Trends (TOSEM’24) [pdf]
  • A Novel Approach for Automatic Program Repair using Round-Trip Translation with Large Language Models (arXiv’24) [pdf]
  • A Comparative Study on Large Language Models for Log Parsing (ESEM’24) [pdf]
  • An Exploratory Study on How Non-Determinism in Large Language Models Affects Log Parsing (InteNSE’24) [pdf]
  • Search-based Automatic Repair for Fairness and Accuracy in Decision-making Software (EMSE’24) [pdf]
  • An Exploratory Literature Study on Sharing and Energy Use of Language Models for Source Code (ESEM'23) [pdf]
  • The EarlyBIRD Catches the Bug: On Exploiting Early Layers of Encoder Models for More Efficient Code Classification (FSE'23) [pdf]
  • Multi-objective Search for Gender-Fair and Semantically Correct Word Embeddings HOP (GECCO'23) [pdf]
  • Multi-objective Search for Gender-Fair and Semantically Correct Word Embeddings (Appl.SoftComput.'23) [pdf]
  • An Empirical Study on the Fairness of Pre-trained Word Embeddings (GEBNLP'22) [pdf]
  • Py2Cy: A Genetic Improvement Tool To Speed Up Python (GI@GECCO'22) [pdf]
  • Privileged and Unprivileged Groups: An Empirical Study on the Impact of the Age Attribute on Fairness (Fairware'22) [pdf]
  • Did You Do Your Homework? Raising Awareness on Software Fairness and Discrimination (ASE'22) [pdf]
  • Fairea: A Model Behaviour Mutation Approach to Benchmarking Bias Mitigation Methods (FSE'21) [pdf]
  • The Effect of Offspring Population Size on NSGA-II: A Preliminary Study (GECCO'21) [pdf]
  • A Survey of Performance Optimization for Mobile Applications (TSE'21) [pdf]
  • Optimising Word Embeddings With Search-Based Approaches (GECCO'20) [pdf]

Master Thesis

  • Using Deep Learning to Improve Proof-Number Search in Two-Player Board Games [pdf]

Service