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.

2024

  1. 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), 2024
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  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. 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
  15. 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
  16. 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
  17. 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