Akito Monden
Cited by
Cited by
Mahakil: Diversity based oversampling approach to alleviate the class imbalance issue in software defect prediction
KE Bennin, J Keung, P Phannachitta, A Monden, S Mensah
IEEE Transactions on Software Engineering 44 (6), 534-550, 2017
Revisiting common bug prediction findings using effort-aware models
Y Kamei, S Matsumoto, A Monden, K Matsumoto, B Adams, AE Hassan
2010 IEEE international conference on software maintenance, 1-10, 2010
Software quality analysis by code clones in industrial legacy software
A Monden, D Nakae, T Kamiya, S Sato, K Matsumoto
Proceedings Eighth IEEE Symposium on Software Metrics, 87-94, 2002
Analyzing individual performance of source code review using reviewers' eye movement
H Uwano, M Nakamura, A Monden, K Matsumoto
Proceedings of the 2006 symposium on Eye tracking research & applications …, 2006
The effects of over and under sampling on fault-prone module detection
Y Kamei, A Monden, S Matsumoto, T Kakimoto, K Matsumoto
First international symposium on empirical software engineering and …, 2007
Design and evaluation of birthmarks for detecting theft of java programs.
H Tamada, M Nakamura, A Monden, K Matsumoto
IASTED Conf. on Software Engineering, 569-574, 2004
A practical method for watermarking Java programs
A Monden, H Iida, K Matsumoto, K Inoue, K Torii
Computer Software and Applications Conference, 2000. COMPSAC 2000. The 24th …, 2000
An analysis of developer metrics for fault prediction
S Matsumoto, Y Kamei, A Monden, K Matsumoto, M Nakamura
Proceedings of the 6th International Conference on Predictive Models in …, 2010
Dynamic software birthmarks to detect the theft of windows applications
H Tamada, K Okamoto, M Nakamura, A Monden, K Matsumoto
International Symposium on Future Software Technology 20 (22), 2004
Java Birthmarks--Detecting the Software Theft--
H Tamada, M Nakamura, A Monden, K Matsumoto
IEICE transactions on information and systems 88 (9), 2148-2158, 2005
Exploiting self-modification mechanism for program protection
Y Kanzaki, A Monden, M Nakamura, K Matsumoto
Proceedings 27th Annual International Computer Software and Applications …, 2003
Quantifying programmers' mental workload during program comprehension based on cerebral blood flow measurement: A controlled experiment
T Nakagawa, Y Kamei, H Uwano, A Monden, K Matsumoto, DM German
Companion proceedings of the 36th international conference on software …, 2014
Assessing the cost effectiveness of fault prediction in acceptance testing
A Monden, T Hayashi, S Shinoda, K Shirai, J Yoshida, M Barker, ...
IEEE Transactions on Software Engineering 39 (10), 1345-1357, 2013
On the relative value of data resampling approaches for software defect prediction
KE Bennin, JW Keung, A Monden
Empirical Software Engineering 24, 602-636, 2019
Empirical evaluation of cross-release effort-aware defect prediction models
KE Bennin, K Toda, Y Kamei, J Keung, A Monden, N Ubayashi
2016 IEEE international conference on software quality, reliability and …, 2016
Design and evaluation of dynamic software birthmarks based on API calls
H Tamada, K Okamoto, M Nakamura, A Monden, K Matsumoto
Info. Science Technical Report NAIST-IS-TR2007011, ISSN, 0919-9527, 2007
Investigating the effects of balanced training and testing datasets on effort-aware fault prediction models
KE Bennin, J Keung, A Monden, Y Kamei, N Ubayashi
2016 IEEE 40th annual Computer software and applications conference (COMPSAC …, 2016
A hybrid faulty module prediction using association rule mining and logistic regression analysis
Y Kamei, A Monden, S Morisaki, K Matsumoto
Proceedings of the Second ACM-IEEE international symposium on Empirical …, 2008
Effort estimation based on collaborative filtering
N Ohsugi, M Tsunoda, A Monden, K Matsumoto
5th International Conference on Product Focused Software Process Improvement …, 2004
Defect data analysis based on extended association rule mining
S Morisaki, A Monden, T Matsumura, H Tamada, K Matsumoto
Fourth International Workshop on Mining Software Repositories (MSR'07: ICSE …, 2007
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