publications

In my research area of Software Engineering (SE), it is common to publish completed research in top-tier conferences as full-length, peer-reviewed papers (10-12 pages). The top SE conferences have very low acceptance rates (<30%) and a few are even considered more prestigious, having significantly more impact and citations, than most journals. The author's order is generally based on the contribution to the publication. In the case of PhD student projects, the convention is to have the PhD student as the first author, where I will be a corresponding author in the second or third author's order.

2027

    2026

    1. When AI Takes the Wheel: Security Analysis of Framework-Constrained Program Generation
      Yue Liu, Zhenchang Xing, Shidong Pan, and Chakkrit Tantithamthavorn
      In The International Conference on Software Engineering (ICSE), 2026

    2025

    1. On the Evaluation of Large Language Models in Multilingual Vulnerability Repair
      Junji Yu, Dong Wang, Honglin Shu, Michael Fu, Chakkrit Tantithamthavorn, Yasutaka Kamei, and Junjie Chen
      ACM Transactions on Software Engineering and Methodology (TOSEM), 2025
    2. Requirements-Driven Automated Software Testing: A Systematic Review
      Fanyu Wang, Chetan Arora, Chakkrit Tantithamthavorn, Kaicheng Huang, and Aldeida Aleti
      ACM Transactions on Software Engineering and Methodology (TOSEM), 2025
    3. AI for DevSecOps: A landscape and future opportunities
      Michael Fu, Jirat Pasuksmit, and Chakkrit Tantithamthavorn
      ACM Transactions on Software Engineering and Methodology (TOSEM), 2025
    4. DeepVulMatch: Learning and Matching Latent Vulnerability Representations for Dual-Granularity Vulnerability Detection
      Michael Fu, Trung Le, Van Nguyen, Chakkrit Tantithamthavorn, and Dinh Phung
      IEEE Transactions on Reliability, 2025
    5. RAGVA: Engineering retrieval augmented generation-based virtual assistants in practice
      Rui Yang, Michael Fu, Chakkrit Tantithamthavorn, Chetan Arora, Lisa Vandenhurk, and Joey Chua
      Journal of Systems and Software (JSS), 2025
    6. Pytester: Deep reinforcement learning for text-to-testcase generation
      Wannita Takerngsaksiri, Rujikorn Charakorn, Chakkrit Tantithamthavorn, and Yuan-Fang Li
      Journal of Systems and Software (JSS), 2025
    7. Enhancing large language models for text-to-testcase generation
      Saranya Alagarsamy, Chakkrit Tantithamthavorn, Wannita Takerngsaksiri, Chetan Arora, and Aldeida Aleti
      Journal of Systems and Software (JSS), 2025
    8. Navigating Fairness: Practitioners’ Understanding, Challenges, and Strategies in AI/ML Development
      Aastha Pant, Rashina Hoda, Chakkrit Tantithamthavorn, and Burak Turhan
      Empirical Software Engineering (EMSE), 2025
    9. What do AI/ML practitioners think about AI/ML bias?
      Aastha Pant, Rashina Hoda, Burak Turhan, and Chakkrit Tantithamthavorn
      IEEE Software, 2025
    10. MLOps, LLMOps, FMOps, and Beyond
      Chakkrit Kla Tantithamthavorn, Fabio Palomba, Foutse Khomh, and Joselito Joey Chua
      IEEE Software, 2025
    11. Human-In-the-Loop Software Development Agents
      Wannita Takerngsaksiri, Jirat Pasuksmit, Patanamon Thongtanunam, Chakkrit Tantithamthavorn, Ruixiong Zhang, Fan Jiang, Jing Li, Evan Cook, Kun Chen, and Ming Wu
      In The International Conference on Software Engineering (ICSE), 2025
    12. Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs
      Fanyu Wang, Chetan Arora, Yonghui Liu, Kaicheng Huang, Kla Tantithamthavorn, Aldeida Aleti, Dishan Sambathkumar, and David Lo
      In The International Conference on Automated Software Engineering (ASE), 2025
    13. What Types of Code Review Comments Do Developers Most Frequently Resolve?
      Saul Goldman, Hong Yi Lin, Jirat Pasuksmit, Patanamon Thongtanunam, Kla Tantithamthavorn, Zhe Wang, Ray Zhang, Ali Behnaz, Fan Jiang, Michael Siers, and 4 more authors
      In The International Conference on Automated Software Engineering (ASE), 2025
    14. AdaptiveGuard: Towards Adaptive Runtime Safety for LLM-Powered Software
      Rui Yang, Michael Fu, Chakkrit Tantithamthavorn, Chetan Arora, Gunel Gulmammadova, and Joey Chua
      In The International Conference on Automated Software Engineering (ASE), 2025
    15. SEALGuard: Safeguarding the Multilingual Conversations in Southeast Asian Languages for AI-Powered Software
      Wenliang Shan, Michael Fu, Rui Yang, and Chakkrit Tantithamthavorn
      In The 2nd ACM International Conference on AI-powered Software (AIWare), 2025
    16. Protect Your Secrets: Understanding and Measuring Data Exposure in VSCode Extensions
      Yue Liu, Chakkrit Tantithamthavorn, and Li Li
      In The IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), 2025
    17. Code Readability in the Age of Large Language Models: An Industrial Case Study from Atlassian
      Wannita Takerngsaksiri, Chakkrit Tantithamthavorn, Micheal Fu, Jirat Pasuksmit, Kun Chen, and Ming Wu
      In The IEEE International Conference on Software Maintenance and Evolution (ICSME), 2025
    18. From Domain Documents to Requirements: AI-Powered Retrieval-Augmented Generation in the Space Industry
      Chetan Arora, Fanyu Wang, Chakkrit Tantithamthavorn, Aldeida Aleti, and Shaun Kenyon
      In The IEEE International Requirements Engineering Conference (RE), 2025
    19. A Preliminary Study of Large Language Models for Multilingual Vulnerability Detection
      Junji Yu, Honglin Shu, Michael Fu, Dong Wang, Chakkrit Tantithamthavorn, Yasutaka Kamei, and Junjie Chen
      In The 1st International Workshop on Large Language Model Supply Chain Analysis (LLMSC 2025), 2025
    20. Automatically Recommend Code Updates: Are We There Yet?
      Yue Liu, Chakkrit Tantithamthavorn, Yonghui Liu, Patanamon Thongtanunam, and Li Li
      ACM Transactions on Software Engineering and Methodology (TOSEM), 2025

    2024

    1. Refining ChatGPT-generated code: Characterizing and mitigating code quality issues
      Yue Liu, Thanh Le-Cong, Ratnadira Widyasari, Chakkrit Tantithamthavorn, Li Li, Xuan-Bach D Le, and David Lo
      ACM Transactions on Software Engineering and Methodology (TOSEM), 2024
    2. Vision Transformer-Inspired Automated Vulnerability Repair
      Michael Fu, Van Nguyen, Chakkrit Tantithamthavorn, Dinh Phung, and Trung Le
      ACM Transactions on Software Engineering and Methodology (TOSEM), Nov 2024
      Just Accepted
    3. On the reliability and explainability of language models for program generation
      Yue Liu, Chakkrit Tantithamthavorn, Yonghui Liu, and Li Li
      ACM Transactions on Software Engineering and Methodology (TOSEM), Nov 2024
    4. Ethics in the Age of AI: An Analysis of AI Practitioners’ Awareness and Challenges
      Aastha Pant, Rashina Hoda, Simone V Spiegler, Chakkrit Tantithamthavorn, and Burak Turhan
      ACM Transactions on Software Engineering and Methodology (TOSEM), Nov 2024
    5. A Formal Explainer for Just-In-Time Defect Predictions
      Jinqiang Yu, Michael Fu, Alexey Ignatiev, Chakkrit Tantithamthavorn, and Peter Stuckey
      ACM Transactions on Software Engineering and Methodology (TOSEM), Nov 2024
    6. Deep domain adaptation with max-margin principle for cross-project imbalanced software vulnerability detection
      Van Nguyen, Trung Le, Chakkrit Tantithamthavorn, John Grundy, and Dinh Phung
      ACM Transactions on Software Engineering and Methodology (TOSEM), Nov 2024
    7. What do AI/ML practitioners think about AI/ML bias?
      Aastha Pant, Rashina Hoda, Burak Turhan, and Chakkrit Tantithamthavorn
      IEEE Software, Nov 2024
    8. AIBugHunter: A Practical Tool for Predicting, Classifying and Repairing Software Vulnerabilities
      Michael Fu, Chakkrit Tantithamthavorn, Trung Le, Yuki Kume, Van Nguyen, Dinh Phung, and John Grundy
      Empirical Software Engineering (EMSE), Nov 2024
    9. Ethics in AI through the Practitioner’s View: A Grounded Theory Literature Review
      Aastha Pant, Rashina Hoda, Chakkrit Tantithamthavorn, and Burak Turhan
      Empirical Software Engineering, Nov 2024
    10. Don’t forget to change these functions! recommending co-changed functions in modern code review
      Yang Hong, Chakkrit Tantithamthavorn, Patanamon Thongtanunam, and Aldeida Aleti
      Information and Software Technology, Nov 2024
    11. A3Test: Assertion-Augmented Automated Test Case Generation
      S Alagarsamy, C Tantithamthavorn, and A Aleti
      Information and Software Technology, Nov 2024
    12. Syntax-aware on-the-fly code completion
      Wannita Takerngsaksiri, Chakkrit Tantithamthavorn, and Yuan-Fang Li
      Information and Software Technology, Nov 2024
    13. Fine-Tuning and Prompt Engineering for Large Language Models-based Code Review Automation
      Chanathip Pornprasit, and Chakkrit Tantithamthavorn
      Information and Software Technology, Nov 2024
    14. Challenges and opportunities in using ChatGPT as a team member to promote code review education and self-regulated learning
      Paula Barba, and Chakkrit Kla Tantithamthavorn
      ASCILITE Publications, Nov 2024
    15. Practitioners’ Challenges and Perceptions of CI Build Failure Predictions at Atlassian
      Yang Hong, Chakkrit Tantithamthavorn, Jirat Pasuksmit, Patanamon Thongtanunam, Arik Friedman, Xing Zhao, and Anton Krasikov
      In the ACM International Conference on the Foundations of Software Engineering (FSE), Nov 2024
    16. Extrapolating Coverage Rate in Greybox Fuzzing
      Danushka Liyanage, Seongmin Lee, Chakkrit Tantithamthavorn, and Marcel Böhme
      In 46th IEEE/ACM International Conference on Software Engineering, ICSE 2024, Nov 2024
    17. Students’ Perspective on AI Code Completion: Benefits and Challenges
      Wannita Takerngsaksiri, Cleshan Warusavitarne, Christian Yaacoub, Matthew Hee Keng Hou, and Chakkrit Tantithamthavorn
      In the 48th IEEE Annual Computers, Software, and Applications Conference (COMPSAC 2024), Nov 2024
    18. Code Ownership: The Principles, Differences, and Their Associations with Software Quality
      Patanamon Thongtanunam, and Chakkrit Tantithamthavorn
      In the International Symposium on Software Reliability Engineering) (ISSRE), Nov 2024

    2023

    1. VulExplainer: A Transformer-based Hierarchical Distillation for Explaining Vulnerability Types
      Michael Fu, Van Nguyen, Chakkrit Tantithamthavorn, Trung Le, and Dinh Phung
      IEEE Transactions on Software Engineering (TSE), Nov 2023
    2. DeepLineDP: Towards a Deep Learning Approach for Line-Level Defect Prediction
      Chanathip Pornprasit, and Chakkrit Tantithamthavorn
      IEEE Trans. Software Eng., Nov 2023
    3. GPT2SP: A Transformer-Based Agile Story Point Estimation Approach
      Michael Fu, and Chakkrit Tantithamthavorn
      IEEE Trans. Software Eng., Nov 2023
    4. Deep Learning for Android Malware Defenses: A Systematic Literature Review
      Yue Liu, Chakkrit Tantithamthavorn, Li Li, and Yepang Liu
      ACM Comput. Surv., Nov 2023
    5. Augmented Agile: Human-Centered AI-Assisted Software Management
      Rashina Hoda, Hoa Dam, Chakkrit Tantithamthavorn, Patanamon Thongtanunam, and Margaret-Anne Storey
      IEEE Software, Nov 2023
    6. Explainable AI for SE: Challenges and Future Directions
      Chakkrit Tantithamthavorn, Jürgen Cito, Hadi Hemmati, and Satish Chandra
      IEEE Software, Nov 2023
    7. Expert Perspectives on Explainability
      Jürgen Cito, Satish Chandra, Chakkrit Tantithamthavorn, and Hadi Hemmati
      IEEE Software, Nov 2023
    8. Reachable Coverage: Estimating Saturation in Fuzzing
      Danushka Liyanage, Marcel Böhme, Chakkrit Tantithamthavorn, and Stephan Lipp
      In 45th IEEE/ACM 45th International Conference on Software Engineering, ICSE 2023, Nov 2023
    9. What would You do? An Ethical AI Quiz
      Wei Teo, Ze Teoh, Dayang Abang Arabi, Morad Aboushadi, Khairenn Lai, Zhe Ng, Aastha Pant, Rashina Hoda, Chakkrit Tantithamthavorn, and Burak Turhan
      In 45th IEEE/ACM 45th International Conference on Software Engineering (Demo Track), ICSE 2023, Nov 2023
    10. ChatGPT for Vulnerability Detection, Classification, and Repair: How Far Are We?
      Michael Fu, Chakkrit Tantithamthavorn, Van Nguyen, and Trung Le
      In The 30th Asia-Pacific Software Engineering Conference (APSEC 2023), Nov 2023
    11. Unit Testing Challenges with Automated Marking
      Chakkrit Tantithamthavorn, and Norman Chen
      In The 30th Asia-Pacific Software Engineering Conference (APSEC 2023), Nov 2023
    12. Detecting Temporal Inconsistency in Biased Datasets for Android Malware Detection
      Haonan Hu, Yue Liu, Yanjie Zhao, Yonghui Liu, Xiaoyu Sun, Chakkrit Tantithamthavorn, and Li Li
      In The 6th International Workshop on Advances in Mobile App Analysis (A-Mobile), Nov 2023
    13. D-ACT: Towards Diff-Aware Code Transformation for Code Review Under a Time-Wise Evaluation
      Chanathip Pornprasit, Chakkrit Tantithamthavorn, Patanamon Thongtanunam, and Chunyang Chen
      In Proceedings of the International Conference on Software Analysis, Evolution and Reengineering (SANER), Nov 2023
    14. Explaining Transformer-based Code Models: What Do They Learn? When They Do Not Work?
      Ahmad Haji Mohammadkhani, Hadi Hemmati, and Chakkrit Tantithamthavorn
      In in Proceedings of the 23rd IEEE International Working Conference on Source Code Analysis and Manipulation, October 2-3, 2023 - Bogotá, Colombia., Nov 2023

    2022

    1. Search-based fairness testing for regression-based machine learning systems
      Anjana Perera, Aldeida Aleti, Chakkrit Tantithamthavorn, Jirayus Jiarpakdee, Burak Turhan, Lisa Kuhn, and Katie Walker
      Empir. Softw. Eng., Nov 2022
    2. An Empirical Study of Model-Agnostic Techniques for Defect Prediction Models
      Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, Hoa Khanh Dam, and John C. Grundy
      IEEE Trans. Software Eng., Nov 2022
    3. Predicting Defective Lines Using a Model-Agnostic Technique
      Supatsara Wattanakriengkrai, Patanamon Thongtanunam, Chakkrit Tantithamthavorn, Hideaki Hata, and Kenichi Matsumoto
      IEEE Trans. Software Eng., Nov 2022
    4. SQAPlanner: Generating Data-Informed Software Quality Improvement Plans
      Dilini Rajapaksha, Chakkrit Tantithamthavorn, Jirayus Jiarpakdee, Christoph Bergmeir, John Grundy, and Wray L. Buntine
      IEEE Trans. Software Eng., Nov 2022
    5. The Impact of Data Merging on the Interpretation of Cross-Project Just-In-Time Defect Models
      Dayi Lin, Chakkrit Tantithamthavorn, and Ahmed E. Hassan
      IEEE Trans. Software Eng., Nov 2022
    6. AutoTransform: Automated Code Transformation to Support Modern Code Review Process
      Patanamon Thongtanunam, Chanathip Pornprasit, and Chakkrit Tantithamthavorn
      In 44th IEEE/ACM 44th International Conference on Software Engineering, ICSE 2022, Pittsburgh, PA, USA, May 25-27, 2022, Nov 2022
    7. Explainable AI for Android Malware Detection: Towards Understanding Why the Models Perform So Well?
      Yue Liu, Chakkrit Tantithamthavorn, Li Li, and Yepang Liu
      In IEEE 33rd International Symposium on Software Reliability Engineering, ISSRE 2022, Charlotte, NC, USA, October 31 - Nov. 3, 2022, Nov 2022
    8. LineVul: A Transformer-based Line-Level Vulnerability Prediction
      Michael Fu, and Chakkrit Tantithamthavorn
      In 19th IEEE/ACM International Conference on Mining Software Repositories, MSR 2022, Pittsburgh, PA, USA, May 23-24, 2022, Nov 2022
    9. CommentFinder: a simpler, faster, more accurate code review comments recommendation
      Yang Hong, Chakkrit Tantithamthavorn, Patanamon Thongtanunam, and Aldeida Aleti
      In Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2022, Singapore, Singapore, November 14-18, 2022, Nov 2022
    10. VulRepair: a T5-based automated software vulnerability repair
      Michael Fu, Chakkrit Tantithamthavorn, Trung Le, Van Nguyen, and Dinh Q. Phung
      In Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2022, Singapore, Singapore, November 14-18, 2022, Nov 2022
    11. Where Should I Look at? Recommending Lines that Reviewers Should Pay Attention To
      Yang Hong, Chakkrit Tantithamthavorn, and Patanamon Thongtanunam
      In IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2022, Honolulu, HI, USA, March 15-18, 2022, Nov 2022

    2021

    1. Software Engineering in Australasia
      Sherlock A. Licorish, Christoph Treude, John C. Grundy, Kelly Blincoe, Stephen G. MacDonell, Chakkrit Tantithamthavorn, Li Li, and Jean-Guy Schneider
      ACM SIGSOFT Softw. Eng. Notes, Nov 2021
    2. Actionable Analytics: Stop Telling Me What It Is; Please Tell Me What To Do
      Chakkrit Tantithamthavorn, Jirayus Jiarpakdee, and John Grundy
      IEEE Softw., Nov 2021
    3. The Impact of Correlated Metrics on the Interpretation of Defect Models
      Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, and Ahmed E. Hassan
      IEEE Trans. Software Eng., Nov 2021
    4. Assessing the Students’ Understanding and their Mistakes in Code Review Checklists: An Experience Report of 1, 791 Code Review Checklist Questions from 394 Students
      Chun Yong Chong, Patanamon Thongtanunam, and Chakkrit Tantithamthavorn
      In 43rd IEEE/ACM International Conference on Software Engineering: Software Engineering Education and Training, ICSE (SEET) 2021, Madrid, Spain, May 25-28, 2021, Nov 2021
    5. Explainable AI for Software Engineering
      Chakkrit Tantithamthavorn, and Jirayus Jiarpakdee
      In 36th IEEE/ACM International Conference on Automated Software Engineering, ASE 2021, Melbourne, Australia, November 15-19, 2021, Nov 2021
    6. PyExplainer: Explaining the Predictions of Just-In-Time Defect Models
      Chanathip Pornprasit, Chakkrit Tantithamthavorn, Jirayus Jiarpakdee, Michael Fu, and Patanamon Thongtanunam
      In 36th IEEE/ACM International Conference on Automated Software Engineering, ASE 2021, Melbourne, Australia, November 15-19, 2021, Nov 2021
    7. JITLine: A Simpler, Better, Faster, Finer-grained Just-In-Time Defect Prediction
      Chanathip Pornprasit, and Chakkrit Tantithamthavorn
      In 18th IEEE/ACM International Conference on Mining Software Repositories, MSR 2021, Madrid, Spain, May 17-19, 2021, Nov 2021
    8. Practitioners’ Perceptions of the Goals and Visual Explanations of Defect Prediction Models
      Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, and John C. Grundy
      In 18th IEEE/ACM International Conference on Mining Software Repositories, MSR 2021, Madrid, Spain, May 17-19, 2021, Nov 2021

    2020

    1. The impact of automated feature selection techniques on the interpretation of defect models
      Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, and Christoph Treude
      Empir. Softw. Eng., Nov 2020
    2. The Impact of Class Rebalancing Techniques on the Performance and Interpretation of Defect Prediction Models
      Chakkrit Tantithamthavorn, Ahmed E. Hassan, and Kenichi Matsumoto
      IEEE Trans. Software Eng., Nov 2020
    3. JITBot: An Explainable Just-In-Time Defect Prediction Bot
      Chaiyakarn Khanan, Worawit Luewichana, Krissakorn Pruktharathikoon, Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, Morakot Choetkiertikul, Chaiyong Ragkhitwetsagul, and Thanwadee Sunetnanta
      In 35th IEEE/ACM International Conference on Automated Software Engineering, ASE 2020, Melbourne, Australia, September 21-25, 2020, Nov 2020
    4. Workload-aware reviewer recommendation using a multi-objective search-based approach
      Wisam Haitham Abbood Al-Zubaidi, Patanamon Thongtanunam, Hoa Khanh Dam, Chakkrit Tantithamthavorn, and Aditya Ghose
      In PROMISE ’20: 16th International Conference on Predictive Models and Data Analytics in Software Engineering, Virtual Event, USA, November 8-9, 2020, Nov 2020

    2019

    1. The Impact of Automated Parameter Optimization on Defect Prediction Models
      Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, and Kenichi Matsumoto
      IEEE Trans. Software Eng., Nov 2019
    2. Mining software defects: should we consider affected releases?
      Suraj Yatish, Jirayus Jiarpakdee, Patanamon Thongtanunam, and Chakkrit Tantithamthavorn
      In Proceedings of the 41st International Conference on Software Engineering, ICSE 2019, Montreal, QC, Canada, May 25-31, 2019, Nov 2019

    2018

    1. 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
      Empir. Softw. Eng., Nov 2018
    2. 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
      Inf. Softw. Technol., Nov 2018
    3. 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
      In Proceedings of the 40th International Conference on Software Engineering, ICSE 2018, Gothenburg, Sweden, May 27 - June 03, 2018, Nov 2018
    4. An experience report on defect modelling in practice: pitfalls and challenges
      Chakkrit Tantithamthavorn, and Ahmed E. Hassan
      In Proceedings of the 40th International Conference on Software Engineering: Software Engineering in Practice, ICSE (SEIP) 2018, Gothenburg, Sweden, May 27 - June 03, 2018, Nov 2018
    5. AutoSpearman: Automatically Mitigating Correlated Software Metrics for Interpreting Defect Models
      Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, and Christoph Treude
      In 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018, Madrid, Spain, September 23-29, 2018, Nov 2018
    6. Artefact: An R Implementation of the AutoSpearman Function
      Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, and Christoph Treude
      In 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018, Madrid, Spain, September 23-29, 2018, Nov 2018

    2017

    1. An Empirical Comparison of Model Validation Techniques for Defect Prediction Models
      Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, and Kenichi Matsumoto
      IEEE Trans. Software Eng., Nov 2017

    2016

    1. Comments on "Researcher Bias: The Use of Machine Learning in Software Defect Prediction"
      Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, and Kenichi Matsumoto
      IEEE Trans. Software Eng., Nov 2016
    2. Automated parameter optimization of classification techniques for defect prediction models
      Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, and Kenichi Matsumoto
      In Proceedings of the 38th International Conference on Software Engineering, ICSE 2016, Austin, TX, USA, May 14-22, 2016, Nov 2016
    3. Towards a better understanding of the impact of experimental components on defect prediction modelling
      Chakkrit Tantithamthavorn
      In Proceedings of the 38th International Conference on Software Engineering, ICSE 2016, Austin, TX, USA, May 14-22, 2016 - Companion Volume, Nov 2016
    4. A Study of Redundant Metrics in Defect Prediction Datasets
      Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, Akinori Ihara, and Kenichi Matsumoto
      In 2016 IEEE International Symposium on Software Reliability Engineering Workshops, ISSRE Workshops 2016, Ottawa, ON, Canada, October 23-27, 2016, Nov 2016

    2015

    1. The Impact of Mislabelling on the Performance and Interpretation of Defect Prediction Models
      Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, Akinori Ihara, and Ken-ichi Matsumoto
      In 37th IEEE/ACM International Conference on Software Engineering, ICSE 2015, Florence, Italy, May 16-24, 2015, Volume 1, Nov 2015
    2. 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, and Ken-ichi Matsumoto
      In 22nd IEEE International Conference on Software Analysis, Evolution, and Reengineering, SANER 2015, Montreal, QC, Canada, March 2-6, 2015, Nov 2015

    2014

    1. Impact Analysis of Granularity Levels on Feature Location Technique
      Chakkrit Tantithamthavorn, Akinori Ihara, Hideaki Hata, and Kenichi Matsumoto
      In Requirements Engineering - First Asia Pacific Requirements Engineering Symposium, APRES 2014, Auckland, New Zealand, April 28-29, 2014. Proceedings, Nov 2014

    2013

    1. Mining A change history to quickly identify bug locations : A case study of the Eclipse project
      Chakkrit Tantithamthavorn, Rattamont Teekavanich, Akinori Ihara, and Ken-ichi Matsumoto
      In IEEE 24th International Symposium on Software Reliability Engineering, ISSRE 2013, Pasadena, CA, USA, November 4-7, 2013 - Supplemental Proceedings, Nov 2013
    2. Using Co-change Histories to Improve Bug Localization Performance
      Chakkrit Tantithamthavorn, Akinori Ihara, and Ken-ichi Matsumoto
      In 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2013, Honolulu, Hawaii, USA, 1-3 July, 2013, Nov 2013