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A 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.
Antoniol, G., Di Penta, M., Zid, C., & Nardone, V. (2021). An Empirical Study on the Usage and Availability of Machine Learning Libraries in Open-Source Python Projects - Dataset [Dataset]. External link
Zampetti, F., Zid, C., Antoniol, G., & Penta, M. D. (2025). The downside of functional constructs: a quantitative and qualitative analysis of their fix-inducing effects. Empirical Software Engineering, 30(1), 9 (43 pages). External link
Zid, C. (2024). The Effect of Pythonic Constructs on the Software Development Process [Ph.D. thesis, Polytechnique Montréal]. Restricted access
Zid, C., Zampetti, F., Antoniol, G., & Di Penta, M. (2024). "Replication package for the paper: ""A Study on the Pythonic Functional Constructs' Understandability""" [Dataset]. External link
Zid, C., Belias, F., Di Penta, M., Khomh, F., & Antoniol, G. (2024, March). List Comprehension Versus for Loops Performance in Real Python Projects: Should we Care? [Paper]. 31st IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2024), Rovaniemi, Finland. External link
Zid, C., Zampetti, F., Antoniol, G., & Di Penta, M. (2024). Replication package for the paper: "A Study on the Pythonic Functional Constructs' Understandability" [Dataset]. External link
Zid, C., Zampetti, F., Antoniol, G., & Di Penta, M. (2024, April). A study on the pythonic functional constructs' understandability [Presentation]. In 2024 IEEE/ACM 46th International Conference on Software Engineering (ICSE 2024), Lisbon, Portugal (13 pages). External link
Zampetti, F., Belias, F., Zid, C., Antoniol, G., & Penta, M. D. (2022, October). An Empirical Study on the Fault-Inducing Effect of Functional Constructs in Python [Paper]. IEEE International Conference on Software Maintenance and Evolution (ICSME 2022), Limassol, Cyprus. 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
Zid, C. (2020). Analyse et détection des anomalies dans un système IOT distribué hybride [Master's thesis, Polytechnique Montréal]. Available