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pro vyhledávání: '"Rachel Harrison"'
Publikováno v:
Data in Brief, Vol 18, Iss, Pp 840-845 (2018)
Data in Brief
Addi. Archivo Digital para la Docencia y la Investigación
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Data in Brief
Addi. Archivo Digital para la Docencia y la Investigación
instname
Classifying software defects according to any defined taxonomy is not straightforward. In order to be used for automatizing the classification of software defects, two sets of defect reports were collected from public issue tracking systems from two
Autor:
Celso G. Camilo-Junior, Plinio S. Leitao-Junior, Diogo M. de Freitas, Silvia Regina Vergilio, Rachel Harrison
Publikováno v:
Information and Software Technology. 123:106295
Context Software Fault Localisation (FL) refers to finding faulty software elements related to failures produced as a result of test case execution. This is a laborious and time consuming task. To allow FL automation search-based algorithms have been
Publikováno v:
EASE
Semi-Supervised Learning (SSL) is a data mining technique which comes between supervised and unsupervised techniques, and is useful when a small number of instances in a dataset are labelled but a lot of unlabelled data is also available. This is the
Publikováno v:
CEC
In this short paper, we compare well-known rule/tree classifiers in software defect prediction with the CTC decision tree classifier designed to deal with class imbalanced. It is well-known that most software defect prediction datasets are highly imb