Software Anti-patterns Detection Under Uncertainty Using a Possibilistic Evolutionary Approach

[1]  C. Holmes,et al.  A probabilistic nearest neighbour method for statistical pattern recognition , 2002 .

[2]  Houari A. Sahraoui,et al.  Maintainability defects detection and correction: a multi-objective approach , 2013, Automated Software Engineering.

[3]  Yann-Gaël Guéhéneuc,et al.  DECOR: A Method for the Specification and Detection of Code and Design Smells , 2010, IEEE Transactions on Software Engineering.

[4]  Alexander Chatzigeorgiou,et al.  Identification of Move Method Refactoring Opportunities , 2009, IEEE Transactions on Software Engineering.

[5]  Mathieu Serrurier,et al.  Naive possibilistic classifiers for imprecise or uncertain numerical data , 2014, Fuzzy Sets Syst..

[6]  Gang Yuan,et al.  Parameter-Free Extreme Learning Machine for Imbalanced Classification , 2020, Neural Processing Letters.

[7]  Kalyanmoy Deb,et al.  Code-Smell Detection as a Bilevel Problem , 2014, TSEM.

[8]  Didier Dubois,et al.  Possibility Theory - An Approach to Computerized Processing of Uncertainty , 1988 .

[9]  Khaled Mellouli,et al.  Information Affinity: A New Similarity Measure for Possibilistic Uncertain Information , 2007, ECSQARU.

[10]  J. R. Quinlan.  DECISION TREES AS PROBABILISTIC CLASSIFIERS , 1987 .

[11]  Nir Friedman,et al.  Bayesian Network Classifiers , 1997, Machine Learning.

[12]  Véronique Prinet,et al.  Towards Optimal Naive Bayes Nearest Neighbor , 2010, ECCV.

[13]  Lalit M. Patnaik,et al.  Genetic algorithms: a survey , 1994, Computer.