Ekrem Kocaguneli
Ekrem Kocaguneli
Software Development Engineer 2, Microsoft
Verified email at - Homepage
Cited by
Cited by
The promise repository of empirical software engineering data
T Menzies, B Caglayan, E Kocaguneli, J Krall, F Peters, B Turhan
June, 2012
On the value of ensemble effort estimation
E Kocaguneli, T Menzies, JW Keung
IEEE Transactions on Software Engineering 38 (6), 1403-1416, 2011
Exploiting the essential assumptions of analogy-based effort estimation
E Kocaguneli, T Menzies, A Bener, JW Keung
IEEE transactions on software engineering 38 (2), 425-438, 2011
Software effort models should be assessed via leave-one-out validation
E Kocaguneli, T Menzies
Journal of Systems and Software 86 (7), 1879-1890, 2013
Software effort models should be assessed via leave-one-out validation
E Kocaguneli, T Menzies
Submitted to Empirical Software Engineering, 2011
Active learning and effort estimation: Finding the essential content of software effort estimation data
E Kocaguneli, T Menzies, J Keung, D Cok, R Madachy
IEEE Transactions on software engineering 39 (8), 1040-1053, 2012
Transfer learning in effort estimation
E Kocaguneli, T Menzies, E Mendes
Empirical Software Engineering 20, 813-843, 2015
Defect prediction between software versions with active learning and dimensionality reduction
H Lu, E Kocaguneli, B Cukic
2014 IEEE 25th International Symposium on Software Reliability Engineering†…, 2014
Sharing data and models in software engineering
T Menzies, E Kocaguneli, B Turhan, L Minku, F Peters
Morgan Kaufmann, 2014
Finding conclusion stability for selecting the best effort predictor in software effort estimation
J Keung, E Kocaguneli, T Menzies
Automated Software Engineering, 1-25, 2012
When to use data from other projects for effort estimation
E Kocaguneli, G Gay, T Menzies, Y Yang, JW Keung
Proceedings of the 25th IEEE/ACM International Conference on Automated†…, 2010
How to find relevant data for effort estimation?
E Kocaguneli, T Menzies
2011 International Symposium on Empirical Software Engineering and†…, 2011
Kernel methods for software effort estimation: Effects of different kernel functions and bandwidths on estimation accuracy
E Kocaguneli, T Menzies, JW Keung
Empirical Software Engineering 18, 1-24, 2013
Prest: An Intelligent Software Metrics Extraction, Analysis and Defect Prediction Tool.
E Kocaguneli, A Tosun, AB Bener, B Turhan, B Caglayan
SEKE, 637-642, 2009
Distributed development considered harmful?
E Kocaguneli, T Zimmermann, C Bird, N Nagappan, T Menzies
2013 35th International Conference on Software Engineering (ICSE), 882-890, 2013
Combining multiple learners induced on multiple datasets for software effort prediction
E Kocaguneli, Y Kultur, A Bener
International symposium on software reliability engineering (ISSRE), 2009
Using goals in model-based reasoning
T Menzies, E KocagŁneli, L Minku, F Peters, B Turhan
Sharing Data and Models in Software Engineering 1, 321-353, 2015
Ai-based models for software effort estimation
E Kocaguneli, A Tosun, A Bener
2010 36th EUROMICRO Conference on Software Engineering and Advanced†…, 2010
The inductive software engineering manifesto: principles for industrial data mining
T Menzies, C Bird, T Zimmermann, W Schulte, E Kocaganeli
Proceedings of the International Workshop on Machine Learning Technologies†…, 2011
Building a second opinion: learning cross-company data
E Kocaguneli, B Cukic, T Menzies, H Lu
Proceedings of the 9th International Conference on Predictive Models in†…, 2013
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