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Comparing Fine-Grained Source Code Changes And Code Churn For Bug Prediction
Giger, E. (author), Pinzger, M. (author), Gall, H.C. (author)
A significant amount of research effort has been dedicated to learning prediction models that allow project managers to efficiently allocate resources to those parts of a software system that most likely are bug-prone and therefore critical. Prominent measures for building bug prediction models are product measures, e.g., complexity or process...
report 2011

Source URL (retrieved on 2019-02-24 00:41): https://repository.tudelft.nl/islandora/search/TUD-SERG-2011-007?collection=research