World's Best Scientists 2026 revealed!
Giuliano Antoniol

Giuliano Antoniol

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Computer Science
Canada
2025

D-Index & Metrics

Computer Science

D-Index
70
Citations
16237
World Ranking
1900
National Ranking
69

Research.com Recognitions

  • 2025 - Research.com Computer Science in Canada Leader Award
  • 2023 - Research.com Computer Science in Canada Leader Award
  • 2022 - Research.com Computer Science in Canada Leader Award

Overview

Giuliano Antoniol is affiliated with Polytechnique Montréal in Canada and specializes in computer science with a focus on software engineering and related subfields. Their research primarily addresses areas within software engineering research, software testing and debugging techniques, and software system performance and reliability.

The main fields of study covered by their work include:

  • Computer Science

Within this broad discipline, Antoniol's contributions span several subfields of study:

  • Information Systems
  • Artificial Intelligence
  • Software
  • Computer Networks and Communications
  • Signal Processing

Their research topics highlight various aspects of software engineering and machine learning, specifically:

  • Software Engineering Research
  • Software Testing and Debugging Techniques
  • Software System Performance and Reliability
  • Computational Physics and Python Applications
  • Adversarial Robustness in Machine Learning
  • Software Reliability and Analysis Research
  • Advanced Malware Detection Techniques

Antoniol has published extensively in multiple venues. Some of the frequent publication venues include:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Empirical Software Engineering
  • PolyPublie (École Polytechnique de Montréal)
  • ACM Transactions on Software Engineering and Methodology

Recent papers authored or coauthored by Antoniol span important topics related to software bugs, mutation testing, and cancer prognosis with a computational component. Notable recent publications include:

  • "Silent bugs in deep learning frameworks: an empirical study of Keras and TensorFlow," 2023, Empirical Software Engineering
  • "A search-based framework for automatic generation of testing environments for cyber-physical systems," 2022, Information and Software Technology
  • "Bugs in large language models generated code: an empirical study," 2025, Empirical Software Engineering
  • "A probabilistic framework for mutation testing in deep neural networks," 2022, Information and Software Technology
  • "Expression of c-MET in Estrogen Receptor Positive and HER2 Negative Resected Breast Cancer Correlated with a Poor Prognosis," 2022, Journal of Clinical Medicine

Frequent collaborators in Antoniol's research include:

  • Foutse Khomh
  • Florian Tambon
  • Massimiliano Di Penta
  • Fiorella Zampetti
  • Cyrine Zid

Best Publications

  • Recovering traceability links between code and documentation

    G. Antoniol;G. Canfora;G. Casazza;A. De Lucia

  • Comparison and Evaluation of Clone Detection Tools

    S. Bellon;R. Koschke;G. Antoniol;J. Krinke

  • Feature Location Using Probabilistic Ranking of Methods Based on Execution Scenarios and Information Retrieval

    D. Poshyvanyk;Y.-G. Gueheneuc;A. Marcus;G. Antoniol

  • Is it a bug or an enhancement?: a text-based approach to classify change requests

    Giuliano Antoniol;Kamel Ayari;Massimiliano Di Penta;Foutse Khomh

  • An exploratory study of the impact of antipatterns on class change- and fault-proneness

    Foutse Khomh;Massimiliano Di Penta;Yann-Gaël Guéhéneuc;Giuliano Antoniol

  • An Empirical Study of the Impact of Two Antipatterns, Blob and Spaghetti Code, on Program Comprehension

    Marwen Abbes;Foutse Khomh;Yann-Gael Gueheneuc;Giuliano Antoniol

  • DeMIMA: A Multilayered Approach for Design Pattern Identification

    Y.-G. Gueheneuc;G. Antoniol

  • EEG data compression techniques

    G. Antoniol;P. Tonella

  • CERBERUS: Tracing Requirements to Source Code Using Information Retrieval, Dynamic Analysis, and Program Analysis

    M. Eaddy;A.V. Aho;G. Antoniol;Y.-G. Gueheneuc

  • Design pattern recovery in object-oriented software

    G. Antoniol;R. Fiutem;L. Cristoforetti

  • Analyzing cloning evolution in the Linux kernel

    G. Antoniol;U. Villano;E. Merlo;M. Di Penta

  • AURA: a hybrid approach to identify framework evolution

    Wei Wu;Yann-Gaël Guéhéneuc;Giuliano Antoniol;Miryung Kim

  • Information retrieval models for recovering traceability links between code and documentation

    Unknown

  • Combining Probabilistic Ranking and Latent Semantic Indexing for Feature Identification

    D. Poshyvanyk;A. Marcus;V. Rajlich;Y.-G. Gueheneuc

  • Feature identification: a novel approach and a case study

    G. Antoniol;Y.-G. Gueheneuc

  • Object oriented design pattern inference

    P. Tonella;G. Antoniol

  • Search-based techniques applied to optimization of project planning for a massive maintenance project

    G. Antoniol;M. Di Penta;M. Harman

  • Automatic mutation test input data generation via ant colony

    Kamel Ayari;Salah Bouktif;Giuliano Antoniol

  • Trustrace: Mining Software Repositories to Improve the Accuracy of Requirement Traceability Links

    Nasir Ali;Yann-Ga #x Eb

  • Using metrics to identify design patterns in object-oriented software

    G. Antoniol;R. Fiutem;L. Cristoforetti

  • Feature Identification: An Epidemiological Metaphor

    G. Antoniol;Y.-G. Gueheneuc

Frequent Co-Authors

Yann-Gaël Guéhéneuc
Yann-Gaël Guéhéneuc Concordia University
Ettore Merlo
Ettore Merlo Polytechnique Montréal
Foutse Khomh
Foutse Khomh Polytechnique Montréal
Massimiliano Di Penta
Massimiliano Di Penta University of Sannio
Paolo Tonella
Paolo Tonella Universita della Svizzera Italiana
Marcello Federico
Marcello Federico Amazon (United States)
Jane Huffman Hayes
Jane Huffman Hayes University of Kentucky
Rocco Oliveto
Rocco Oliveto University of Molise
Gerardo Canfora
Gerardo Canfora University of Sannio
Filippo Ricca
Filippo Ricca University of Genoa

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