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Empirical Software Engineering, ISSN 1382-3256, 10/2009, Volume 14, Issue 5, pp. 540 - 578
We propose a practical defect prediction approach for companies that do not track defect related data. Specifically, we investigate the applicability of... 
Learning | Nearest-neighbor filtering | Within-company | Metrics (product metrics) | Defect prediction | Cross-company | COMPUTER SCIENCE, SOFTWARE ENGINEERING | INSPECTIONS | STATIC CODE ATTRIBUTES | SOFTWARE | Computer science | Studies | Construction | Filtering | Filtration | Neural networks | Switches | Mathematical models | Defects
Journal Article
2010, 1st Simon & Schuster hardcover ed., ISBN 1439102120, 372 pages, 8 unnumbered pages of plates
How did a nineteen-year-old Harvard student create a company that has transformed the Internet and how did he grow it to its current enormous size? In half a... 
Facebook (Firm) | Internet industry | History | Online social networks
Book
Information and Software Technology, ISSN 0950-5849, 2012, Volume 54, Issue 3, pp. 248 - 256
Software defect prediction studies usually built models using within-company data, but very few focused on the prediction models trained with cross-company... 
Naive Bayes | Different distribution | Software defect prediction | Transfer learning | Machine learning | COMPUTER SCIENCE, SOFTWARE ENGINEERING | NEURAL-NETWORKS | MODELS | METRICS | COMPUTER SCIENCE, INFORMATION SYSTEMS | CLASSIFICATION | Computer science | Software | Learning | Training | Classifiers | Construction | Mathematical models | Computer programs | Defects
Journal Article
Journal of Toxicology and Environmental Health, Part A, ISSN 1528-7394, 04/2012, Volume 75, Issue 8-10, pp. 414 - 422
Journal Article
IEEE Transactions on Software Engineering, ISSN 0098-5589, 05/2007, Volume 33, Issue 5, pp. 316 - 329
Journal Article
Information and Software Technology, ISSN 0950-5849, 06/2015, Volume 62, Issue 1, pp. 67 - 77
Software defect prediction has been widely studied based on various machine-learning algorithms. Previous studies usually focus on within-company defects... 
Transfer learning | Cross-company defects prediction | Software fault prediction | COMPUTER SCIENCE, SOFTWARE ENGINEERING | COMPUTER SCIENCE, INFORMATION SYSTEMS | STATIC CODE ATTRIBUTES | Computer software industry | Data mining | Machine learning
Journal Article
IEEE Transactions on Software Engineering, ISSN 0098-5589, 6/2019, pp. 1 - 1
The majority of contributions to community open source software (OSS) projects are made by practitioners acting on behalf of companies and other organisations.... 
Technological innovation | Collaboration | work practices | Companies | Licenses | company contribution | Software | Interviews | Open source software
Journal Article
IEEE Transactions on Software Engineering, ISSN 0098-5589, 08/2013, Volume 39, Issue 8, pp. 1054 - 1068
Background: Cross-company defect prediction (CCDP) is a field of study where an organization lacking enough local data can use data from other organizations... 
Privacy | Sociology | defect prediction | Search problems | Software | Arrays | classification | Statistics | Testing | Genetic algorithms | COMPUTER SCIENCE, SOFTWARE ENGINEERING | STATIC CODE ATTRIBUTES | K-ANONYMITY | MODEL | ENGINEERING, ELECTRICAL & ELECTRONIC | Prediction theory | Usage | Data security | Analysis
Journal Article