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Collaboration networkThis graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
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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.
Aghili, R. (2025). Improving the Infrastructures of AIOps by Bridging the Data Gap [Ph.D. thesis, Polytechnique Montréal]. Available
Aghili, R., Li, H., & Khomh, F. (2025, June). Protecting Privacy in Software Logs: What Should Be Anonymized? [Paper]. ACM International Conference on the Foundations of Software Engineering (FSE 2025), Trondheim, Norway. Published in Proceedings of the ACM on Software Engineering, 2(FSE). External link
Aghili, R., Li, H., & Khomh, F. (2025). Protecting Privacy in Software Logs: What Should Be Anonymized? Proceedings of the ACM on software engineering., 2(FSE), 1317-1338. External link
Aghili, R., Qin, Q., Li, H., & Khomh, F. (2024, October). Understanding Web Application Workloads and Their Applications: Systematic Literature Review and Characterization [Paper]. IEEE International Conference on Software Maintenance and Evolution (ICSME 2024), Flagstaff, AZ, USA. External link
Aghili, R., Li, H., & Khomh, F. (2023). Studying the characteristics of AIOps projects on GitHub. Empirical Software Engineering, 28(6), 143 (49 pages). External link
Batoun, M. A., Sayagh, M., Aghili, R., Ouni, A., & Li, H. (2024). A literature review and existing challenges on software logging practices: From the creation to the analysis of software logs. Empirical Software Engineering, 29, 103 (61 pages). External link
Qin, Q., Aghili, R., Li, H., & Merlo, E. (2025, March). Preprocessing is All You Need: Boosting the Performance of Log Parsers with a General Preprocessing Framework [Paper]. IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2025), Montreal, QC, Canada. External link
