Abstract
Nowadays, there are many methods and good practices in software engineering that aim to provide high quality software. However, despite the efforts of software developers, there are often defects in projects, the removal of which is often associated with a large financial effort and time. The article presents an example approach to defect prediction in IT projects based on prediction models built on historical information and product metrics collected from various data repositories.
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Czyczyn-Egird, D., Slowik, A. (2019). Defect Prediction in Software Using Predictive Models Based on Historical Data. In: RodrÃguez, S., et al. Distributed Computing and Artificial Intelligence, Special Sessions, 15th International Conference. DCAI 2018. Advances in Intelligent Systems and Computing, vol 801. Springer, Cham. https://doi.org/10.1007/978-3-319-99608-0_11
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DOI: https://doi.org/10.1007/978-3-319-99608-0_11
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