Fault Persistency and Fault Prediction in Optimization of Software Release
Автор: Maurizio Pighin, Anna Marzona
Журнал: International Journal of Information Technology and Computer Science(IJITCS) @ijitcs
Статья в выпуске: 8 Vol. 5, 2013 года.
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This article serves two purposes: firstly, it presents an innovative methodology that increases the accuracy of fault prediction measurements. This method is based on the novel concept of "fault persistency", which enables to correct prediction metrics with a weighted value related to the module’s history. Secondly, it aims to develop operational processes from the aforesaid prediction metrics that may contribute to software construction and validation. It presents an example of an allocation methodology for resources used for testing purposes. The theoretical part is followed by an extensive experimental phase.
Fault Prediction, Fault Persistency, Software Release, Software Metrics, Software Testing
Короткий адрес: https://sciup.org/15011935
IDR: 15011935
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