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- W1993764100 abstract "In this paper, we explore two new approaches for software defect prediction. The similarity-based approach predicts the number of latent defects of a software module from those of modules most similar to it. The rank-based approach uses machine learning models specially trained to predict the ranks of software modules based on their actual number of latent defects. In both approaches, we use technical concerns/functionalities recovered by topic modeling techniques as features to represent software modules. Empirical evaluation with five real software systems shows that the proposed approaches outperform the traditional one and a recently introduced defect prediction method." @default.
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- W1993764100 date "2014-10-01" @default.
- W1993764100 modified "2023-09-23" @default.
- W1993764100 title "Similarity-based and rank-based defect prediction" @default.
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- W1993764100 doi "https://doi.org/10.1109/atc.2014.7043405" @default.
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