Chakkrit Tantithamthavorn

Orcid: 0000-0002-5516-9984

According to our database1, Chakkrit Tantithamthavorn authored at least 89 papers between 2013 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
What Do AI/ML Practitioners Think About AI/ML Bias?
IEEE Softw., 2025

2024
Scoping Software Engineering for AI: The TSE Perspective.
IEEE Trans. Software Eng., November, 2024

Deep Domain Adaptation With Max-Margin Principle for Cross-Project Imbalanced Software Vulnerability Detection.
ACM Trans. Softw. Eng. Methodol., July, 2024

On the Reliability and Explainability of Language Models for Program Generation.
ACM Trans. Softw. Eng. Methodol., June, 2024

Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues.
ACM Trans. Softw. Eng. Methodol., June, 2024

Ethics in AI through the practitioner's view: a grounded theory literature review.
Empir. Softw. Eng., May, 2024

Ethics in the Age of AI: An Analysis of AI Practitioners' Awareness and Challenges.
ACM Trans. Softw. Eng. Methodol., March, 2024

Vision Transformer Inspired Automated Vulnerability Repair.
ACM Trans. Softw. Eng. Methodol., March, 2024

AIBugHunter: A Practical tool for predicting, classifying and repairing software vulnerabilities.
Empir. Softw. Eng., February, 2024

Syntax-aware on-the-fly code completion.
Inf. Softw. Technol., January, 2024

Fine-tuning and prompt engineering for large language models-based code review automation.
Inf. Softw. Technol., 2024

Don't forget to change these functions! recommending co-changed functions in modern code review.
Inf. Softw. Technol., 2024

A3Test: Assertion-Augmented Automated Test case generation.
Inf. Softw. Technol., 2024

AI for DevSecOps: A Landscape and Future Opportunities.
CoRR, 2024

Navigating Fairness: Practitioners' Understanding, Challenges, and Strategies in AI/ML Development.
CoRR, 2024

Enhancing Large Language Models for Text-to-Testcase Generation.
CoRR, 2024

GPT-3.5 for Code Review Automation: How Do Few-Shot Learning, Prompt Design, and Model Fine-Tuning Impact Their Performance?
CoRR, 2024

TDD Without Tears: Towards Test Case Generation from Requirements through Deep Reinforcement Learning.
CoRR, 2024

Practitioners' Challenges and Perceptions of CI Build Failure Predictions at Atlassian.
Proceedings of the Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering, 2024

Code Ownership: The Principles, Differences, and Their Associations with Software Quality.
Proceedings of the 35th IEEE International Symposium on Software Reliability Engineering, 2024

Extrapolating Coverage Rate in Greybox Fuzzing.
Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, 2024

Students' Perspectives on AI Code Completion: Benefits and Challenges.
Proceedings of the 48th IEEE Annual Computers, Software, and Applications Conference, 2024

2023
VulExplainer: A Transformer-Based Hierarchical Distillation for Explaining Vulnerability Types.
IEEE Trans. Software Eng., October, 2023

GPT2SP: A Transformer-Based Agile Story Point Estimation Approach.
IEEE Trans. Software Eng., February, 2023

DeepLineDP: Towards a Deep Learning Approach for Line-Level Defect Prediction.
IEEE Trans. Software Eng., January, 2023

Explainable AI for SE: Challenges and Future Directions.
IEEE Softw., 2023

Augmented Agile: Human-Centered AI-Assisted Software Management.
IEEE Softw., 2023

Expert Perspectives on Explainability.
IEEE Softw., 2023

Deep Learning for Android Malware Defenses: A Systematic Literature Review.
ACM Comput. Surv., 2023

Students' Perspective on AI Code Completion: Benefits and Challenges.
CoRR, 2023

Pitfalls in Language Models for Code Intelligence: A Taxonomy and Survey.
CoRR, 2023

Learning to Quantize Vulnerability Patterns and Match to Locate Statement-Level Vulnerabilities.
CoRR, 2023

On the Reliability and Explainability of Automated Code Generation Approaches.
CoRR, 2023

A Systematic Literature Review of Explainable AI for Software Engineering.
CoRR, 2023

D-ACT: Towards Diff-Aware Code Transformation for Code Review Under a Time-Wise Evaluation.
Proceedings of the IEEE International Conference on Software Analysis, 2023

Explaining Transformer-based Code Models: What Do They Learn? When They Do Not Work?
Proceedings of the 23rd IEEE International Working Conference on Source Code Analysis and Manipulation, 2023

Detecting Temporal Inconsistency in Biased Datasets for Android Malware Detection.
Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering, ASE 2023, 2023

What Would You do? An Ethical AI Quiz.
Proceedings of the 45th IEEE/ACM International Conference on Software Engineering: ICSE 2023 Companion Proceedings, 2023

Reachable Coverage: Estimating Saturation in Fuzzing.
Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, 2023

Unit Testing Challenges with Automated Marking.
Proceedings of the 30th Asia-Pacific Software Engineering Conference, 2023

ChatGPT for Vulnerability Detection, Classification, and Repair: How Far Are We?
Proceedings of the 30th Asia-Pacific Software Engineering Conference, 2023

2022
Predicting Defective Lines Using a Model-Agnostic Technique.
IEEE Trans. Software Eng., 2022

SQAPlanner: Generating Data-Informed Software Quality Improvement Plans.
IEEE Trans. Software Eng., 2022

The Impact of Data Merging on the Interpretation of Cross-Project Just-In-Time Defect Models.
IEEE Trans. Software Eng., 2022

An Empirical Study of Model-Agnostic Techniques for Defect Prediction Models.
IEEE Trans. Software Eng., 2022

Search-based fairness testing for regression-based machine learning systems.
Empir. Softw. Eng., 2022

Explainable AI for Pre-Trained Code Models: What Do They Learn? When They Do Not Work?
CoRR, 2022

An Information-Theoretic and Contrastive Learning-based Approach for Identifying Code Statements Causing Software Vulnerability.
CoRR, 2022

Cross Project Software Vulnerability Detection via Domain Adaptation and Max-Margin Principle.
CoRR, 2022

AutoUpdate: Automatically Recommend Code Updates for Android Apps.
CoRR, 2022

Ethics in AI through the Developer's Prism: A Socio-Technical Grounded Theory Literature Review and Guidelines.
CoRR, 2022

Where Should I Look at? Recommending Lines that Reviewers Should Pay Attention To.
Proceedings of the IEEE International Conference on Software Analysis, 2022

CommentFinder: a simpler, faster, more accurate code review comments recommendation.
Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022

VulRepair: a T5-based automated software vulnerability repair.
Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022

LineVul: A Transformer-based Line-Level Vulnerability Prediction.
Proceedings of the 19th IEEE/ACM International Conference on Mining Software Repositories, 2022

Explainable AI for Android Malware Detection: Towards Understanding Why the Models Perform So Well?
Proceedings of the IEEE 33rd International Symposium on Software Reliability Engineering, 2022

AutoTransform: Automated Code Transformation to Support Modern Code Review Process.
Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering, 2022

2021
The Impact of Correlated Metrics on the Interpretation of Defect Models.
IEEE Trans. Software Eng., 2021

Actionable Analytics: Stop Telling Me What It Is; Please Tell Me What To Do.
IEEE Softw., 2021

Software Engineering in Australasia.
ACM SIGSOFT Softw. Eng. Notes, 2021

JITLine: A Simpler, Better, Faster, Finer-grained Just-In-Time Defect Prediction.
Proceedings of the 18th IEEE/ACM International Conference on Mining Software Repositories, 2021

Practitioners' Perceptions of the Goals and Visual Explanations of Defect Prediction Models.
Proceedings of the 18th IEEE/ACM International Conference on Mining Software Repositories, 2021

Explainable AI for Software Engineering.
Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering, 2021

PyExplainer: Explaining the Predictions of Just-In-Time Defect Models.
Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering, 2021

Assessing the Students' Understanding and their Mistakes in Code Review Checklists: An Experience Report of 1, 791 Code Review Checklist Questions from 394 Students.
Proceedings of the 43rd IEEE/ACM International Conference on Software Engineering: Software Engineering Education and Training, 2021

2020
The Impact of Class Rebalancing Techniques on the Performance and Interpretation of Defect Prediction Models.
IEEE Trans. Software Eng., 2020

The impact of automated feature selection techniques on the interpretation of defect models.
Empir. Softw. Eng., 2020

Explainable AI for Software Engineering.
CoRR, 2020

Workload-aware reviewer recommendation using a multi-objective search-based approach.
Proceedings of the PROMISE '20: 16th International Conference on Predictive Models and Data Analytics in Software Engineering, 2020

JITBot: An Explainable Just-In-Time Defect Prediction Bot.
Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering, 2020

2019
The Impact of Automated Parameter Optimization on Defect Prediction Models.
IEEE Trans. Software Eng., 2019

Mining software defects: should we consider affected releases?
Proceedings of the 41st International Conference on Software Engineering, 2019

2018
The impact of IR-based classifier configuration on the performance and the effort of method-level bug localization.
Inf. Softw. Technol., 2018

Studying the dialogue between users and developers of free apps in the Google Play Store.
Empir. Softw. Eng., 2018

AutoSpearman: Automatically Mitigating Correlated Metrics for Interpreting Defect Models.
CoRR, 2018

The Impact of Correlated Metrics on Defect Models.
CoRR, 2018

Artefact: An R Implementation of the AutoSpearman Function.
Proceedings of the 2018 IEEE International Conference on Software Maintenance and Evolution, 2018

AutoSpearman: Automatically Mitigating Correlated Software Metrics for Interpreting Defect Models.
Proceedings of the 2018 IEEE International Conference on Software Maintenance and Evolution, 2018

An experience report on defect modelling in practice: pitfalls and challenges.
Proceedings of the 40th International Conference on Software Engineering: Software Engineering in Practice, 2018

2017
An Empirical Comparison of Model Validation Techniques for Defect Prediction Models.
IEEE Trans. Software Eng., 2017

2016
Comments on "Researcher Bias: The Use of Machine Learning in Software Defect Prediction".
IEEE Trans. Software Eng., 2016

A Study of Redundant Metrics in Defect Prediction Datasets.
Proceedings of the 2016 IEEE International Symposium on Software Reliability Engineering Workshops, 2016

Towards a better understanding of the impact of experimental components on defect prediction modelling.
Proceedings of the 38th International Conference on Software Engineering, 2016

Automated parameter optimization of classification techniques for defect prediction models.
Proceedings of the 38th International Conference on Software Engineering, 2016

2015
Who should review my code? A file location-based code-reviewer recommendation approach for Modern Code Review.
Proceedings of the 22nd IEEE International Conference on Software Analysis, 2015

The Impact of Mislabelling on the Performance and Interpretation of Defect Prediction Models.
Proceedings of the 37th IEEE/ACM International Conference on Software Engineering, 2015

2014
Impact Analysis of Granularity Levels on Feature Location Technique.
Proceedings of the Requirements Engineering, 2014

2013
Using Co-change Histories to Improve Bug Localization Performance.
Proceedings of the 14th ACIS International Conference on Software Engineering, 2013

Mining A change history to quickly identify bug locations : A case study of the Eclipse project.
Proceedings of the IEEE 24th International Symposium on Software Reliability Engineering, 2013


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