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This 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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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., Merlo, E., Guéhéneuc, Y.-G., & Sahraoui, H. (2005, November). On feature traceability in object oriented programs [Paper]. 3rd international workshop on Traceability in emerging forms of software engineering (TEFSE 2005), Long Beach, California, USA. External link
Bouktif, S., Sahraoui, H., & Antoniol, G. (2006, July). Simulated annealing for improving software quality prediction [Paper]. 8th Annual Genetic and Evolutionary Computation Conference (GECCO 2006), Seattle, WA, United States. External link
Jeanmart, S., Guéhéneuc, Y.-G., Sahraoui, H., & Habra, N. (2009, October). Impact of the visitor pattern on program comprehension and maintenance [Paper]. 3rd International Symposium on Empirical Software Engineering and Measurement, Lake Buena Vista, FL, USA. External link
Khomh, F., Vaucher, S., Guéhéneuc, Y.-G., & Sahraoui, H. (2009, August). A Bayesian approach for the detection of code and design smells [Paper]. 9th International Conference on Quality Software (QSIC 2009), Jeju, South Korea. External link
Oakes, B., Famelis, M., & Sahraoui, H. (2024). Building Domain-Specific Machine Learning Workflows: A Conceptual Framework for the State-of-the-Practice. ACM Transactions on Software Engineering and Methodology, 33(4), 1-50. Available
Sahraoui, H., Briand, L. C., Guéhéneuc, Y.-G., & Beaurepaire, O. (2010). Investigating the impact of a measurement program on software quality. Information and Software Technology, 52(9), 923-933. External link
Varaminybahnemiry, Z., Galasso, J., Oakes, B., & Sahraoui, H. (2024). Improving repair of semantic ATL errors using a social diversity metric. Software and Systems Modeling, 22-22. External link