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Morakot Choetkiertikul, Ph.D.
Morakot Choetkiertikul, Ph.D.
Lecture at Faculty of ICT, Mahidol University
Verified email at mahidol.ac.th
Title
Cited by
Cited by
Year
A deep learning model for estimating story points
M Choetkiertikul, HK Dam, T Tran, T Pham, A Ghose, T Menzies
IEEE Transactions on Software Engineering 45 (7), 637-656, 2018
1132018
Predicting delivery capability in iterative software development
M Choetkiertikul, HK Dam, T Tran, A Ghose, J Grundy
IEEE Transactions on Software Engineering 44 (6), 551-573, 2017
422017
Predicting delays in software projects using networked classification (t)
M Choetkiertikul, HK Dam, T Tran, A Ghose
2015 30th IEEE/ACM international conference on automated software …, 2015
392015
Predicting the delay of issues with due dates in software projects
M Choetkiertikul, HK Dam, T Tran, A Ghose
Empirical Software Engineering 22 (3), 1223-1263, 2017
362017
Characterization and prediction of issue-related risks in software projects
M Choetkiertikul, HK Dam, T Tran, A Ghose
2015 IEEE/ACM 12th Working Conference on Mining Software Repositories, 280-291, 2015
332015
Who will answer my question on Stack Overflow?
M Choetkiertikul, D Avery, HK Dam, T Tran, A Ghose
2015 24th Australasian Software Engineering Conference, 155-164, 2015
272015
Identifying design and requirement self-admitted technical debt using n-gram idf
S Wattanakriengkrai, R Maipradit, H Hata, M Choetkiertikul, T Sunetnanta, ...
2018 9th International Workshop on Empirical Software Engineering in …, 2018
232018
A risk assessment model for offshoring using CMMI quantitative approach
M Choetkiertikul, T Sunetnanta
2010 Fifth International Conference on Software Engineering Advances, 331-336, 2010
152010
Jitbot: An explainable just-in-time defect prediction bot
C Khanan, W Luewichana, K Pruktharathikoon, J Jiarpakdee, ...
Proceedings of the 35th IEEE/ACM International Conference on Automated …, 2020
132020
Predicting components for issue reports using deep learning with information retrieval
M Choetkiertikul, HK Dam, T Tran, T Pham, A Ghose
Proceedings of the 40th International Conference on Software Engineering …, 2018
62018
Teddy: Automatic Recommendation of Pythonic Idiom Usage For Pull-Based Software Projects
P Phan-udom, N Wattanakul, T Sakulniwat, C Ragkhitwetsagul, ...
2020 IEEE International Conference on Software Maintenance and Evolution …, 2020
52020
Towards team formation in software development: A case study of moodle
N Assavakamhaenghan, P Suwanworaboon, W Tanaphantaruk, S Tuarob, ...
2020 17th International Conference on Electrical Engineering/Electronics …, 2020
52020
Visualizing the Usage of Pythonic Idioms Over Time: A Case Study of the with open Idiom
T Sakulniwat, RG Kula, C Ragkhitwetsagul, M Choetkiertikul, ...
2019 10th International Workshop on Empirical Software Engineering in …, 2019
52019
Automatic team recommendation for collaborative software development
S Tuarob, N Assavakamhaenghan, W Tanaphantaruk, P Suwanworaboon, ...
Empirical Software Engineering 26 (4), 1-53, 2021
42021
Automatic classifying self-admitted technical debt using n-gram IDF
S Wattanakriengkrai, N Srisermphoak, S Sintoplertchaikul, ...
2019 26th Asia-Pacific Software Engineering Conference (APSEC), 316-322, 2019
42019
A CMMI-based automated risk assessment framework
M Choetkiertikul, HK Dam, A Ghose, TT Sunetnanta
2014 21st Asia-Pacific Software Engineering Conference 2, 63-68, 2014
42014
Improving clone detection precision using machine learning techniques
V Arammongkolvichai, R Koschke, C Ragkhitwetsagul, M Choetkiertikul, ...
2019 10th International Workshop on Empirical Software Engineering in …, 2019
32019
Software team member configurations: A study of team effectiveness in moodle
N Assavakamhaenghan, M Choetkiertikul, S Tuarob, RG Kula, H Hata, ...
2019 10th International Workshop on Empirical Software Engineering in …, 2019
32019
A Risk Assessment Tool Using a CMMI Quantitative Approach
M Choetkiertikul, T Sunetnanta
International Journal of Engineering and Technology 4 (4), 352, 2012
32012
Automatically recommending components for issue reports using deep learning
M Choetkiertikul, HK Dam, T Tran, T Pham, C Ragkhitwetsagul, A Ghose
Empirical Software Engineering 26 (2), 1-39, 2021
12021
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