Chakkrit (Kla) Tantithamthavorn

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defect prediction software quality assurance machine learning mining software repositories software analytics data science empirical software engineering software engineering prediction model data mining data analytics introduction cuda gpu open data data intelligence feature location google app engine data quality noise parameter tuning automated parameter optimization bug-prediction defect-prediction software-analytics explainable-ai continuous integration devops artificial intelligence high performance computing experimental design predictive analytics predictive model bootstrap validation k-fold cross validation bug prediction model validation scottknott-esd holdout validation model evaluation statistics software development classification techniques software quality

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Chakkrit (Kla) Tantithamthavorn

Presentations

Example Application of GPU

Introduction to GPU Programming

Introduction to Google App Engine

Open Data in Asia: An Overview of Open Data Policies and Practices in 13 Countries

Impact Analysis of Granularity Levels on Feature Location Technique

The Impact of Mislabelling on the Performance and Interpretation of Defect Prediction Models

Automated parameter optimization should be included in future  defect prediction studies

Towards a Better Understanding of the Impact of Experimental Components on Defect Prediction Models

An Empirical Comparison of Model Validation Techniques for Defect Prediction Models

Leveraging HPC Resources to Improve the Experimental Design of Software Analytics

AI-Driven Software Quality Assurance in the Age of DevOps

Software Analytics In Action: A Hands-on Tutorial on Mining, Analyzing, Modelling, and Explaining Software Data

Mining Software Defects: Should We Consider Affected Releases?

The Impact of Class Rebalancing Techniques on the Performance and Interpretation of Defect Prediction Models

Explainable Artificial Intelligence (XAI)  to Predict and Explain Future Software Defects

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Toward Structured Location of Features