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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Côté, P.-O., Nikanjam, A., Ahmed, N., Humeniuk, D., & Khomh, F. (2024). Data cleaning and machine learning: a systematic literature review. Automated Software Engineering, 31(2), 54 (75 pages). External link
Humeniuk, D., Braiek, H. B., Reid, T., & Khomh, F. (2024). In-Simulation Testing of Deep Learning Vision Models in Autonomous Robotic Manipulators. External link
Humeniuk, D., Khomh, F., & Antoniol, G. (2024). Reinforcement Learning Informed Evolutionary Search for Autonomous Systems Testing. ACM Transactions on Software Engineering and Methodology. External link
Humeniuk, D., & Khomh, F. (2024, April). AmbieGenVAE at the SBFT 2024 Tool Competition - Cyber-Physical Systems Track [Paper]. 17th ACM/IEEE International Workshop on Search-Based and Fuzz Testing, Lisbon, Portugal. External link
Humeniuk, D., & Khomh, F. (2024, April). AmbieGen at the SBFT 2024 Tool Competition-CPS-UAV Track [Paper]. 17th International Workshop on Search-Based and Fuzz Testing (SBFT 2024), Lisbon, Portugal. External link
Humeniuk, D., Khomh, F., & Antoniol, G. (2023). AmbieGen: A search-based framework for autonomous systems testing. Science of Computer Programming, 230, 102990 (10 pages). External link
Humeniuk, D., Khomh, F., & Antoniol, G. RIGAA at the SBFT 2023 Tool Competition - Cyber-Physical Systems Track [Paper]. 2023 IEEE/ACM International Workshop on Search-Based and Fuzz Testing (SBFT 2023), Melbourne, Australia. External link
Humeniuk, D., Antoniol, G., & Khomh, F. (2022, May). ***AmbieGen tool at the SBST 2022 Tool Competition [Paper]. 15th Search-Based Software Testing Workshop (SBST 2022). External link
Humeniuk, D., Khomh, F., & Antoniol, G. (2022). A search-based framework for automatic generation of testing environments for cyber-physical systems. Information and Software Technology, 149, 106936 (17 pages). External link
Humeniuk, D. (2021). A Search-Based Framework for Automatic Generation of Testing Environments for Cyber-Physical Systems [Master's thesis, Polytechnique Montréal]. Available
Humeniuk, D., Antoniol, G., & Khomh, F. (2021, May). Data Driven Testing of Cyber Physical Systems [Paper]. 14th IEEE/ACM International Workshop on Search-Based Software Testing (SBST 2021), Madrid, Spain. External link
Humeniuk, D., Antoniol, G., & Khomh, F. (2021, May). SWAT tool at the SBST 2021 Tool Competition [Paper]. 14th IEEE/ACM International Workshop on Search-Based Software Testing (SBST 2021), Madrid, Spain. External link
Khatiri, S., Zohdinasab, T., Saurabh, P., Humeniuk, D., & Panichella, S. (2025). ICST 2025 UAV Testing Competition: Evaluation Artifacts [Dataset]. External link
Zid, C., Humeniuk, D., Khomh, F., & Antoniol, G. (2020, June). Double cycle hybrid testing of hybrid distributed IoT system [Paper]. IEEE/ACM 42nd International Conference on Software Engineering Workshops (ICSEW 2020), Seoul, Republic of Korea. External link
