Stebėti
Tim Menzies
Tim Menzies
North Carolina State University, Computer Science, ACM Fellow, IEEE Fellow, ASE Fellow
Patvirtintas el. paštas ncsu.edu - Pagrindinis puslapis
Pavadinimas
Cituota
Cituota
Metai
Data mining static code attributes to learn defect predictors
T Menzies, J Greenwald, A Frank
IEEE transactions on software engineering 33 (1), 2-13, 2006
19192006
The promise repository of empirical software engineering data
T Menzies, B Caglayan, E Kocaguneli, J Krall, F Peters, B Turhan
June, 2012
1239*2012
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, 540-578, 2009
8732009
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, 375-407, 2010
6002010
Heterogeneous defect prediction
J Nam, S Kim
Proceedings of the 2015 10th joint meeting on foundations of software …, 2015
5982015
Automated severity assessment of software defect reports
T Menzies, A Marcus
2008 IEEE International Conference on Software Maintenance, 346-355, 2008
4322008
Problems with Precision: A Response to" comments on'data mining static code attributes to learn defect predictors'"
T Menzies, A Dekhtyar, J Distefano, J Greenwald
IEEE Transactions on Software Engineering 33 (9), 637-640, 2007
3482007
Selecting best practices for effort estimation
T Menzies, Z Chen, J Hihn, K Lum
IEEE Transactions on Software Engineering 32 (11), 883-895, 2006
3342006
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
3312012
On the value of ensemble effort estimation
E Kocaguneli, T Menzies, JW Keung
IEEE Transactions on Software Engineering 38 (6), 1403-1416, 2011
3312011
What is wrong with topic modeling?(and how to fix it using search-based se)
A Agrawal, W Fu, T Menzies
Information and Software Technology 98 (June), 74-88, 2018
3022018
Automatic query reformulations for text retrieval in software engineering
S Haiduc, G Bavota, A Marcus, R Oliveto, A De Lucia, T Menzies
2013 35th International Conference on Software Engineering (ICSE), 842-851, 2013
2792013
On the value of user preferences in search-based software engineering: A case study in software product lines
AS Sayyad, T Menzies, H Ammar
2013 35Th international conference on software engineering (ICSE), 492-501, 2013
2782013
Better cross company defect prediction
F Peters, T Menzies, A Marcus
2013 10th working conference on mining software repositories (MSR), 409-418, 2013
2742013
Tuning for software analytics: Is it really necessary?
W Fu, T Menzies, X Shen
Information and Software Technology 76, 135-146, 2016
2562016
On the use of relevance feedback in IR-based concept location
G Gay, S Haiduc, A Marcus, T Menzies
2009 IEEE international conference on software maintenance, 351-360, 2009
2542009
Easy over Hard: A Case Study on Deep Learning
W Fu, T Menzies
ESEC/SIGSOFT FSE 2017, 49-60, 2017
2512017
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
2502008
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
2492011
" Better Data" is Better than" Better Data Miners"(Benefits of Tuning SMOTE for Defect Prediction)
A Agrawal, T Menzies
International Conference on Software Engineering, 2018, 2018
2462018
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Straipsniai 1–20