He is a lecturer (a.k.a. Assistant Professor) in Faculty of Information Technology, Monash University. My current research focuses on AI-Driven Software Quality Assurance in the Age of DevOps. His research has been published at top-tier software engineering venues, such as IEEE Transactions on Software Engineering (TSE), Empirical Software Engineering (EMSE), and the International Conference on Software Engineering (ICSE). During his Ph.D. study, he won one of the most prestigious and selective sources of national funding in Japan, i.e., a JSPS Research Fellowship for Young Researchers and a Grants-in-Aid for JSPS Fellow, and won a "Best Ph.D. Student Award".

Interests: Empirical Software Engineering, Software Quality Assurance, Mining Software Repository

Address: Faculty of Information Technology, Monash University, Australia.
Email: chakkrit.tantithamthavorn@monash.edu

January 01, 2019
I am super excited to announce that I will join a lecturer in Faculty of Information Technology, Monash University, Australia.
December 12, 2018
Our paper on "Mining Software Defects: Should We Consider Affected Releases" co-authored with Suraj Yatish, Jirayus Jiarpakdee, and Pick has been accepted at the International Conference on Software Engineering (ICSE 2019), Montreal, Canada with an acceptance rate of 21% (109/529)!
October 15, 2018
My paper on The Impact of Class Rebalancing Techniques on the Performance and Interpretation of Defect Prediction Models has been accepted at IEEE Transactions on Software Engineering (TSE)!
October 08, 2018
According to Google Scholar, my work on automated parameter optimization for defect prediction models is the 3rd highly-cited ICSE 2016 paper.
September 26, 2018
I was invited to be a member of the Open Science Board of Empirical Software Engineering Journal (ERA A).
September 11, 2018
I was invited to be a program committee of the ROSE (Recognizing and Rewarding Open Science in Software Engineering) for ESEC/FSE 2018.
August 27, 2018
I was invited to be a journal referee for Journal of Software Testing, Verification and Reliability (STVR) (Impact Factor: 1.556).
July 30, 2018
I was invited to be a program committee member for the Early Research Achievements (ERA) Track of the International Conference on Software Analysis, Evolution, and Reengineering (SANER 2019).
July 08, 2018
I was invited to give a seminar talk at the University of Wollongong, hosted by Dr. Hoa Dam during 8-15 July 2018.
July 03, 2018
I was invited to give a seminar talk at the University of Melbourne.
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With the rise of software systems ranging from personal assistance to the nation's facilities, software defects become more critical concerns as they can cost millions of dollar as well as impact human lives. Yet, at the breakneck pace of rapid software development settings (like DevOps paradigm), the Quality Assurance (QA) practices nowadays are still time-consuming. Continuous Analytics for Software Quality (i.e., defect prediction models) can help development teams prioritize their QA resources and chart better quality improvement plan to avoid pitfalls in the past that lead to future software defects. Due to the need of specialists to design and configure a large number of configurations (e.g., data quality, data preprocessing, classification techniques, interpretation techniques), a set of practical guidelines for developing accurate and interpretable defect models has not been well-developed. My current research focuses on AI-Driven Software Quality Assurance in the Age of DevOps.
The ultimate goal of my research aims to (1) provide practical guidelines on how to develop accurate and interpretable defect models for non-specialists; (2) develop an intelligible defect model that offer suggestions how to improve both software quality and processes; and (3) integrate defect models into a real-world practice of rapid development cycles like CI/CD settings. My research project is expected to provide significant benefits including the reduction of software defects and operating costs, while accelerating development productivity for building software systems in many of Australia's critical domains such as Smart Cities and e-Health.
  1. 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)
    2018
    PDF
  2. 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
  3. Artefact: An R Implementation of the AutoSpearman Function

    Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, Christoph Treude
    International Conference on Software Maintenance and Evolution (ICSME)
    2018
    PDF
  4. 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
  5. 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)
    2018
    PDF
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. 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
  12. 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
  13. See more...

Google Scholar released the 2018 version of Scholar Metrics with h5-index and h5-median for the top-20 Conferences and Journals in each area of research! In the area of Software Systems the International Conference on Software Engineering (ICSE) and IEEE Transactions on Software Engineering (TSE) are in the top two positions.

Current Supervision

Semester 1, 2018

  • (Undergraduates) COMP SCI 3303: Engineering Software as a Service 1
  • (Master) COMP SCI 7096A: Master of Software Engineering Projects A

Semester 2, 2018

  • (Undergraduates) COMP SCI 2206: Software Engineering Workshop 2
  • (Undergraduates) COMP SCI 3006: Software Engineering & Project
  • (Undergraduates) COMP SCI 4409: Search-Based Software Engineering (Assessor only)
  • (Master) COMP SCI 7096B: Master of Software Engineering Projects B
  1. Journal Referee

    • IEEE Access, Impact Factor (2016): 3.22.
       2017: 1 manuscript.
  2. Program Committee (PC)

    • The International Conference on Software Maintenance and Evolution (ICSME), 2017, 2018
    • The International Conference on Program Comprehension (ICPC), 2018 Tool Track
  3. Additional Reviewer

    • The International Conference on Software Engineering (ICSE), 2018
    • The Working Conference on Mining Software Repositories (MSR), 2015
    • The India Software Engineering Conference (ISEC), 2015
    • The IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM), 2014
  4. Web (Co)-Chair

    • The International Workshop on Empirical Software Engineering in Practice (IWESEP), 2017
    • The Japan Summer School in Mining Software Repositories (MSR Asia Summit), 2015
    • The Thailand-Japan International Academic Conference (TJIA), 2013
  5. Student Volunteer

    • The International Conference on Software Analysis, Evolution, and Reengineering (SANER), 2016
    • The International Workshop on Empirical Software Engineering in Practice (IWESEP), 2012