Publications

For a full list of publications, please check Google Scholar and DBLP.

Publications

• “Evaluating LLMs for One-Shot Patching of Real and Artificial Vulnerabilities.”
  Aayush Garg, Zanis Ali Khan, Renzo Degiovanni, Qiang Tang.
  ACM/SIGAPP Symposium on Applied Computing (SAC) Smarter Engineering - Building AI and Building with AI (SEAI) 2026
  Preprint

• “Evaluation of Multi-Language Vulnerability Patching with Pre-Trained Models.”
  Zanis Ali Khan, Aayush Garg, Yuejun Guo, Qiang Tang.
  ACM/SIGAPP Symposium on Applied Computing (SAC) Computer Security (SEC) 2026
  PDF | arXiv

• “A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair.”
  Zanis Ali Khan, Aayush Garg, Qiang Tang.
  International Workshop on Artificial Intelligence, Cyber and Cyber-Physical Security (AI&CCPS) ARES, 2025
  link | PDF

• “On the Coupling between Vulnerabilities and LLM-generated Mutants: A Study on Vul4J dataset.”
  Aayush Garg, Renzo Degiovanni, Mike Papadakis, Yves Le Traon.
  IEEE International Conference on Software Testing, Verification and Validation (ICST), 2024
  link | PDF | Github

• “AI-Driven Software Security: Vulnerability Detection, Patching, and Anti-Fuzzing.”
  Aayush Garg, Yuejun Guo, Qiang Tang.
  The 139th European Research Consortium for Informatics and Mathematics (ERCIM) News, Special Theme: Software Security, 2024
  link

• “Enabling Efficient Assertion Inference.”
  Aayush Garg, Renzo Degiovanni, Facundo Molina, Mike Papadakis, Nazareno Aguirre, Maxime Cordy, Yves Le Traon.
  IEEE International Symposium on Software Reliability Engineering (ISSRE), 2023
  link | PDF | Github

• “On Comparing Mutation Testing Tools through Learning-based Mutant Selection.”
  Milos Ojdanic, Ahmed Khanfir, Aayush Garg, Renzo Degiovanni, Mike Papadakis, Yves Le Traon.
  ACM/IEEE International Conference on Automation of Software Test (AST), 2023
  link | PDF | Github

• “Syntactic Vs. Semantic similarity of Artificial and Real Faults in Mutation Testing Studies.”
  Milos Ojdanic, Aayush Garg, Ahmed Khanfir, Renzo Degiovanni, Mike Papadakis, Yves Le Traon.
  IEEE Transactions on Software Engineering Journal (TSE), 2023
  link | Github

• “Learning from What We Know: How to Perform Vulnerability Prediction using Noisy Historical Data.”
  Aayush Garg, Renzo Degiovanni, Matthieu Jimenez, Maxime Cordy, Mike Papadakis, Yves Le Traon.
  Empirical Software Engineering (EMSE), 2022
  link | Github

• “Cerebro: Static subsuming mutant selection.”
  Aayush Garg, Milos Ojdanic, Renzo Degiovanni, Thierry Titcheu Chekam, Mike Papadakis Yves Le Traon.
  IEEE Transactions on Software Engineering (TSE), 2021
  link | Github

Thesis

• “Guiding Quality Assurance Through Context Aware Learning.”
  Aayush Garg.
  PhD Dissertation (2023), University of Luxembourg.
  link | PDF

Preprints

• “Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus.”
  Aayush Garg, Orlando Amaral Cejas.
  preprint

• “A Survey of Cyber Range Training Exercise Scenario Description Generation and Execution.”
  Aayush Garg, Abdelwahab Boualouache, Adnan Imeri, Uwe Roth.
  preprint | PDF

• “Payload Analysis of Adversaries’ Tooling: Automated Identification of Fuzzers.”
  Aayush Garg, Constantinos Patsakis, Zanis Ali Khan, Qiang Tang.
  preprint | Github

• “Vulnerability Mimicking Mutants.”
  Aayush Garg, Renzo Degiovanni, Mike Papadakis, Yves Le Traon.
  preprint | PDF GitHub

• “Learning to predict vulnerabilities from vulnerability-fixes: A machine translation approach.”
  Aayush Garg, Renzo Degiovanni, Matthieu Jimenez, Maxime Cordy, Mike Papadakis, Yves Le Traon.
  preprint | PDF