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Vulnerability detection is garnering increasing attention in software engineering, since code vulnerabilities possibly pose significant security.
A metrics suite for object oriented design
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The use of summation to aggregate software metrics hinders the performance of defect prediction models
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Yaqin Zhou, Shangqing Liu, Jing Kai Siow, Xiaoning Du, and Yang Liu · 2019
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Norm-based curriculum learning for neural machine translation
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An empirical study on the effectiveness of static C code analyzers for vulnerability detection
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Regvd: Revisiting graph neural networks for vulnerability detection
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The impact of feature importance methods on the interpretation of defect classifiers
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An exploratory study on code attention in BERT
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Learning program semantics with code representations: An empirical study
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The impact of class rebalancing techniques on the performance and interpretation of defect prediction models
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Word rotator’s distance
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The rise of software vulnerability: Taxonomy of software vulnerabilities detection and machine learning approaches
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A systematic literature review on the use of deep learning in software engineering research
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Norm of word embedding encodes information gain
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Android source code vulnerability detection: A systematic literature review
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CSGVD: A deep learning approach combining sequence and graph embedding for source code vulnerability detection
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Predicting bug fix time in students’ programming with deep language models
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Deepvulseeker: A novel vulnerability identification framework via code graph structure and pre-training mechanism
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Vulnerability detection by learning from syntax-based execution paths of code
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An empirical assessment of different word embedding and deep learning models for bug assignment
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