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 | 61 | 2018 |
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 | 32 | 2015 |
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 | 28 | 2017 |
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 | 28 | 2015 |
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 | 25 | 2017 |
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 | 16 | 2015 |
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 | 14 | 2018 |
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 | 13 | 2010 |
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 | 4 | 2014 |
A Risk Assessment Tool Using a CMMI Quantitative Approach M Choetkiertikul, T Sunetnanta International Journal of Engineering and Technology 4 (4), 352, 2012 | 3 | 2012 |
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 | 1 | 2019 |
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 | 1 | 2019 |
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 | 1 | 2019 |
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 | 1 | 2019 |
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 | 1 | 2018 |
Developing analytics models for software project management M Choetkiertikul | 1 | 2018 |
Quantitative CMMI Assessment for Software Process Quality and Risk Monitoring in Software Process Improvement TT Sunetnanta, M Choetkiertikul IACSIT International Journal of Engineering and Technology 4 (2), 2012 | 1 | 2012 |
A Taxonomy for Mining and Classifying Privacy Requirements in Issue Reports P Sangaroonsilp, HK Dam, M Choetkiertikul, C Ragkhitwetsagul, A Ghose arXiv preprint arXiv:2101.01298, 2021 | | 2021 |
JITBot: An Explainable Just-In-Time Defect Prediction Bot C Khanan, W Luewichana, K Pruktharathikoon, J Jiarpakdee, ... 2020 35th IEEE/ACM International Conference on Automated Software …, 2020 | | 2020 |
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 | | 2020 |