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Yann-Gaël Guéhéneuc
Researcher at Concordia University
Publications - 284
Citations - 9377
Yann-Gaël Guéhéneuc is an academic researcher from Concordia University. The author has contributed to research in topics: Software design pattern & Software maintenance. The author has an hindex of 48, co-authored 268 publications receiving 8061 citations. Previous affiliations of Yann-Gaël Guéhéneuc include École des mines de Nantes & Concordia University Wisconsin.
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Journal ArticleDOI
DECOR: A Method for the Specification and Detection of Code and Design Smells
TL;DR: DETEX is proposed, a method that embodies and defines all the steps necessary for the specification and detection of code and design smells, and a detection technique that instantiates this method, and an empirical validation in terms of precision and recall of DETEX.
Journal ArticleDOI
Feature Location Using Probabilistic Ranking of Methods Based on Execution Scenarios and Information Retrieval
TL;DR: The results show that the combination of experts significantly improves the effectiveness of feature location as compared to each of the experts used independently.
Proceedings ArticleDOI
Is it a bug or an enhancement?: a text-based approach to classify change requests
TL;DR: This paper investigates whether the text of the issues posted in bug tracking systems is enough to classify them into corrective maintenance and other kinds of activities and shows that alternating decision trees, naive Bayes classifiers, and logistic regression can be used to accurately distinguish bugs from other kinds.
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An exploratory study of the impact of antipatterns on class change- and fault-proneness
TL;DR: It is shown that, in almost all releases of the four systems, classes participating in antipatterns are more change-and fault-prone than others and size alone cannot explain the higher odds of classes with antip atterns to underwent a (fault-fixing) change than other classes.
Proceedings ArticleDOI
An Exploratory Study of the Impact of Code Smells on Software Change-proneness
TL;DR: It is shown that, in almost all releases of Azureus and Eclipse, classes with code smelling are more change-prone than others, and that specific smells are more correlated than others to change-proneness.