Data selection for cross-project defect prediction

Data selection for cross-project defect prediction

Abstract Context: This study contributes to the understanding of the current state of cross-project defect prediction (CPDP) by investigating the topic in themes, with special focus on data approaches and covering search-based training data selection, by proposing data selection methods and investi...

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Bibliographic Details
Main Author: Hosseini, S. (Seyedrebvar)
Other Authors: Turhan, B. (Burak)
Format: Doctoral Thesis
Language:English
Published: Oulun yliopisto 2019
Subjects:
Search-Based Methods
cross-project defect prediction
data selection
meta-analysis
systematic literature review
datan valinta
hakuperusteiset menetelmät
meta-analyysi
projektienvälisten virheiden ennustaminen
systemaattinen kirjallisuuskatsaus
Online Access:http://urn.fi/urn:isbn:9789526224480
http://nbn-resolving.de/urn:isbn:9789526224480

Internet

http://urn.fi/urn:isbn:9789526224480
http://nbn-resolving.de/urn:isbn:9789526224480

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