1. Predicting Defective Lines Using a Model-Agnostic Technique

    Supatsara Wattanakriengkrai, Patanamon Thongtanunam, Chakkrit Tantithamthavorn, Hideaki Hata, and Kenichi Matsumoto
    IEEE Transactions on Software Engineering (TSE)
    2020
    PDF
  2. The Impact of Automated Feature Selection Techniques on the Interpretation of Defect Models

    Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, Christoph Treude
    International Journal of Empirical Software Engineering (EMSE)
    2020
    PDF
  3. An Empirical Study of Model-Agnostics Techniques for Defect Prediction Models

    Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, Hoa Khanh Dam, John Grundy
    IEEE Transactions on Software Engineering (TSE)
    2020
    PDF
  4. The Impact of Correlated Metrics on the Interpretation of Defect Models

    Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, and Ahmed E. Hassan
    IEEE Transactions on Software Engineering (TSE)
    2019
    PDF
  5. The Impact of Class Rebalancing Techniques on the Performance and Interpretation of Defect Prediction Models

    Chakkrit Tantithamthavorn, Ahmed E. Hassan, and Kenichi Matsumoto
    IEEE Transactions on Software Engineering (TSE)
    2019
    PDF
  6. The Impact of IR-based Classifier Configuration on the Performance and the Effort of Method-Level Bug Localization

    Chakkrit Tantithamthavorn, Surafel Lemma Abebe, Ahmed E. Hassan, Akinori Ihara, and Kenichi Matsumoto
    Information and Software Technology (IST)
    2018
    PDF
  7. The Impact of Automated Parameter Optimization on Defect Prediction Models

    Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, and Kenichi Matsumoto
    IEEE Transactions on Software Engineering (TSE)
    2019
    PDF
  8. Studying the Dialogue Between Users and Developers of Free Apps in the Google Play Store


    Safwat Hassan, Chakkrit Tantithamthavorn, Cor-Paul Bezemer, and Ahmed E. Hassan
    International Journal of Empirical Software Engineering (EMSE)
    2018
    PDF
  9. An Empirical Comparison of Model Validation Techniques for Defect Prediction Models


    Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, and Kenichi Matsumoto
    IEEE Transactions on Software Engineering (TSE)
    2017
    PDF
  10. Comments on "Researcher Bias: The Use of Machine Learning in Software Defect Prediction"

    Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, and Kenichi Matsumoto
    IEEE Transactions on Software Engineering (TSE)
    2016
    PDF
  1. JITLine: A Simpler, Better, Faster, Finer-grained Just-In-Time Defect Prediction

    Chanathip Pornprasit, Chakkrit Tantithamthavorn
    International Conference on Mining Software Repositories (MSR)
    2021
  2. Practitioners Perceptions of the Goals and Visual Explanations of Defect Prediction Models

    Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, John Grundy
    International Conference on Mining Software Repositories (MSR)
    2021
    PDF
  3. Assessing the Students Understanding and their Mistakes in Code Review Checklists--An Experience Report of 1,791 Code Review Checklists from 394 Students

    Chun Yong Chong, Patanamon Thongtanunam, Chakkrit Tantithamthavorn
    International Conference on Software Engineering: Joint Software Engineering Education and Training track (ICSE-JSEET)
    2021
    PDF
  4. Workload-Aware Reviewer Recommendation using a Multi-objective Search-Based Approach

    Wisam Haitham Abbood Al-Zubaidi, Patanamon Thongtanunam, Hoa Khanh Dam, Chakkrit Tantithamthavorn, Aditya Ghose
    International Conference on Predictive Modelling in Software Engineering (PROMISE)
    2020
    PDF
  5. JITBot: An Explainable Just-In-Time Defect Prediction Bot

    Chaiyakarn Khanan, Worawit Luewichana, Krissakorn Pruktharathikoon, Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, Morakot Choetkiertikul, Chaiyong Ragkhitwetsagul, Thanwadee Sunetnanta
    International Conference on Automated Software Engineering (ASE)
    2020
    PDF
  6. Mining Software Defects: Should We Consider Affected Releases?

    Suraj Yatish, Jirayus Jiarpakdee, Patanamon Thongtanunam, Chakkrit Tantithamthavorn
    The International Conference on Software Engineering (ICSE)
    2019
    21% (109/529)
    PDF
  7. AutoSpearman: Automatically Mitigating Correlated Metrics for Interpreting Defect Models

    Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, Christoph Treude
    International Conference on Software Maintenance and Evolution (ICSME)
    2018
    22% (37/174)
    PDF
  8. Artefact: An R Implementation of the AutoSpearman Function

    Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, Christoph Treude
    International Conference on Software Maintenance and Evolution (ICSME)
    2018
    PDF
  9. An Experience Report on Defect Modelling in Practice: Pitfalls and Challenges

    Chakkrit Tantithamthavorn and Ahmed E. Hassan
    The International Conference on Software Engineering: Software Engineering in Practice Track (ICSE-SEIP)
    2018
    24% (31/131)
    PDF
  10. Automated Parameter Optimization of Classification Techniques for Defect Prediction Models

    Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, and Kenichi Matsumoto
    The International Conference on Software Engineering (ICSE)
    2016
    19% (101/530)
    PDF
  11. Towards a Better Understanding of the Impact of Experimental Components on Defect Prediction Modelling

    Chakkrit Tantithamthavorn
    The International Conference on Software Engineering: Doctoral Symposium Track (ICSE-DS)
    2016
    22% (8/36) for paper presentation
    PDF
  12. The Impact of Mislabelling on the Performance and Interpretation of Defect Prediction Models


    Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, Akinori Ihara, and Kenichi Matsumoto
    The International Conference on Software Engineering (ICSE)
    2015
    18.5% (89/455)
    PDF
  13. Who Should Review My Code? A File Location-Based Code-Reviewer Recommendation Approach for Modern Code Review

    Patanamon Thongtanunam, Chakkrit Tantithamthavorn, Raula Gaikovina Kula, Norihiro Yoshida, Hajimu Iida, Kenichi Matsumoto
    The International Conference on Software Analysis, Evolution, and Reengineering (SANER)
    2015
    32% (46/144)
    PDF
  14. Impact Analysis of Granularity Levels on Feature Location Technique

    Chakkrit Tantithamthavorn, Akinori Ihara, Hideaki Hata, Kenichi Matsumoto
    The First Asia Pacific Requirements Engineering Symposium (APRES)
    2014
    PDF
  15. Using Co-Change Histories to Improve Bug Localization Performance

    Chakkrit Tantithamthavorn, Akinori Ihara, Kenichi Matsumoto
    Proceedings of the International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)
    2013
    PDF
  16. Mining A Change History to Quickly Identify Bug Locations: A Case Study of the Eclipse Project

    Chakkrit Tantithamthavorn, Rattamont Teekavanich, Akinori Ihara, Kenichi Matsumoto
    Proceedings of the International Symposium on Software Reliability Engineering (ISSRE)
    2013
    PDF
  17. Knowledge Discovery in Web Traffic Log: A Case Study of Facebook Usage in Kasetsart University

    Chakkrit Tantithamthavorn and Arnon Rungsawang
    Proceedings of the International Joint Conference on Computer Science and Software Engineering (JCSSE)
    2012
    PDF
  1. Leveraging HPC Resources to Improve the Experimental Design of Software Analytics

    Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, and Kenichi Matsumoto
    Proceedings of the High Performance Computing Symposium (HPCS)
    2017
    PDF
  2. A Study of Redundant Metrics in Defect Prediction Datasets

    Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, Akinori Ihara, Kenichi Matsumoto
    Proceedings of the International Symposium on Software Reliability Engineering (ISSRE)
    2016
    PDF
  3. A Tool for Collaborative Guitar Chords Creation based on The Concept of The Distributed Version Control

    Chakkrit Tantithamthavorn, Papon Yongpisanpop, Masao Ohira, Arnon Rungsawang, Kenichi Matsumoto
    Proceedings of the International Workshop on Empirical Software Engineering in Practice (IWESEP)
    2011
    PDF
  1. (PhD Thesis) Towards a Better Understanding of the Impact of Experimental Components on Defect Prediction Models


    Chakkrit Tantithamthavorn
    Nara Institute of Science and Technology
    2016
    PDF
  2. (Master Thesis) The Impact of Granularity Levels in Program Elements on IR-based Bug Localization

    Chakkrit Tantithamthavorn
    Nara Institute of Science and Technology
    2014