Burak Turhan
Burak Turhan
Professor, University of Oulu, Finland
Verified email at - Homepage
Cited by
Cited by
On the relative value of cross-company and within-company data for defect prediction
B Turhan, T Menzies, AB Bener, J Di Stefano
Empirical Software Engineering 14 (5), 540-578, 2009
Defect prediction from static code features: current results, limitations, new approaches
T Menzies, Z Milton, B Turhan, B Cukic, Y Jiang, A Bener
Automated software engineering 17 (4), 375-407, 2010
The promise repository of empirical software engineering data
T Menzies, B Caglayan, E Kocaguneli, J Krall, F Peters, B Turhan
West Virginia University, Department of Computer Science, 2012
Pandemic Programming: How COVID-19 affects software developers and how their organizations can help
P Ralph, S Baltes, G Adisaputri, R Torkar, V Kovalenko, M Kalinowski, ...
Empirical Software Engineering 25, 4927-4961, 2020
Local versus global lessons for defect prediction and effort estimation
T Menzies, A Butcher, D Cok, A Marcus, L Layman, F Shull, B Turhan, ...
IEEE Transactions on software engineering 39 (6), 822-834, 2012
A Systematic Literature Review and Meta-analysis on Cross Project Defect Prediction
R Hosseini, B Turhan, D Gunarathna
IEEE Transactions on Software Engineering 45 (2), 111-147, 2019
Implications of ceiling effects in defect predictors
T Menzies, B Turhan, A Bener, G Gay, B Cukic, Y Jiang
Proceedings of the 4th international workshop on Predictor models in …, 2008
Empirical software engineering experts on the use of students and professionals in experiments
D Falessi, N Juristo, C Wohlin, B Turhan, J Münch, A Jedlitschka, M Oivo
Empirical Software Engineering 23, 452-489, 2018
Analysis of Naive Bayes’ assumptions on software fault data: An empirical study
B Turhan, A Bener
Data & Knowledge Engineering 68 (2), 278-290, 2009
Cognitive biases in software engineering: a systematic mapping study
R Mohanani, I Salman, B Turhan, P Rodríguez, P Ralph
IEEE Transactions on Software Engineering 46 (12), 1318-1339, 2020
Empirical standards for software engineering research
P Ralph, N Ali, S Baltes, D Bianculli, J Diaz, Y Dittrich, N Ernst, M Felderer, ...
arXiv preprint arXiv:2010.03525, 2020
Empirical evaluation of the effects of mixed project data on learning defect predictors
B Turhan, AT Mısırlı, A Bener
Information and Software Technology 55 (6), 1101-1118, 2013
On the dataset shift problem in software engineering prediction models
B Turhan
Empirical Software Engineering 17 (1), 62-74, 2012
A dissection of the test-driven development process: does it really matter to test-first or to test-last?
D Fucci, H Erdogmus, B Turhan, M Oivo, N Juristo
IEEE Transactions on Software Engineering 43 (7), 597-614, 2016
A benchmark study on the effectiveness of search-based data selection and feature selection for cross project defect prediction
S Hosseini, B Turhan, M Mäntylä
Information and Software Technology 95, 296-312, 2018
What do we know about test-driven development?
F Shull, G Melnik, B Turhan, L Layman, M Diep, H Erdogmus
Software, IEEE 27 (6), 16-19, 2010
Validation of network measures as indicators of defective modules in software systems
A Tosun, B Turhan, A Bener
Proceedings of the 5th international conference on predictor models in …, 2009
Practical considerations in deploying statistical methods for defect prediction: A case study within the Turkish telecommunications industry
A Tosun, A Bener, B Turhan, T Menzies
Information and Software Technology 52 (11), 1242-1257, 2010
Software effort estimation using machine learning methods
B Başkeleş, B Turhan, A Bener
Computer and information sciences, 2007. iscis 2007. 22nd international …, 2007
Sharing data and models in software engineering
T Menzies, E Kocaguneli, B Turhan, L Minku, F Peters
Morgan Kaufmann, 2014
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