Ongoing Research Projects

SE4DS: Applying Software Engineering for Improving the Development of Data Science Application

Apirak Hoonlor, Chaiyong Ragkhitwetsagul, Morakot Choetkiertikul, Thanwadee Sunetnanta, Siripen Pongpaichet

Mahidol Mini Research Cluster Funding, 2021-2022

Funding Agency: Mahidol University

There has not been a study to identify a framework for applying software engineering to better develop and maintain data science applications.  Thus, this project aims to answer the following research questions.

Effects of COVID-19 to Software Development in Thailand

Chaiyong Ragkhitwetsagul, Morakot Choetkiertikul, Thanwadee Sunetnanta, Srisupa Palakvangsa Na Ayudhya, Napaphat Satchanawakul

We study the effects of COVID-19 on Thai software developers to better understand such effects of COVID-19 in Thailand's context. Due to the different in culture and society, Thai software developers may face different challenges and may need different supports from their organizations during and after the pandemic compared to the Wester culture and companies. This research also aims to further extend the investigation of effects from COVID-19 or similar kind of phenomenon to the productivity of software development teams, and organization.   

Competency-based self-assessment model for software security engineers

Thanwadee Sunetnanta

SWITCHSEA Program, 2021-2022

Funding Agency: APNIC Foundation


Development of Deep Learning-based Models for Learning Vector Representation of Iterative Software Development

Morakot Choetkiertikul

Research Grant for New Scholar (RGNS), 2021-2023

Funding Agency: Ministry of Higher Education, Science, Research and Innovation (MHESI), Thailand


Code Similarity Applications for Improving Software Quality

Chaiyong Ragkhitwetsagul, 

Research Grant for New Scholar (RGNS), 2021-2023

Funding Agency: Ministry of Higher Education, Science, Research and Innovation (MHESI), Thailand

Software has a strong effect to people’s lives due to its prevalence in almost every aspects of living. This makes high quality software more important than ever. Software with high quality makes fast and correct computations with lower number of errors, compared to low-quality software. Furthermore, high quality software offers much lower chance of data leakage and contains fewer security vulnerabilities. This research project aims to propose a novel approach to improve software by using code similarity techniques and create an automated tool for detecting similar code and giving relevant recommendations. The projects will leverage code similarity in order to tackle several issues that lead to low- quality software. For example, by measuring code similarity, one can locate duplicated pieces of code, i.e., code clones, within a software project or across software projects, and properly refactor them. This results in lower amount of redundant code in the software, hence easier to maintain. It can also avoid software licensing violations caused by code reuse and can also recommend software developers on how to write code that are well- accepted by the community. We plan to study and adopt suitable machine learning techniques for code similarity computations and will evaluate its effectiveness. Lastly, we plan to also deploy the tool to be used by developers and evaluate its usefulness and its impact in practice.

Past Research projects

Chaiyong Ragkhitwetsagul, Jens Krinke, Morakot Choetkiertikul, Thanwadee Sunetnanta, Federica Sarro

Industry Academia Partnership Programme - 18/19 (IAPP18-19\74): April 2018 - November 2022

Funding Agencies: Newton Fund, UK, Royal Academy of Engineering (RAEng), UK and Thailand Science, Research, and Innovation (TSRI), Thailand

This project aims to study the challenges Thai software development SMEs currently face and train them to adopt ASE to tackle such challenges, the quality and quantity of software products developed in Thailand will be tremendously increased. This project provides benefits to both the UK and the Thai partners. First, it provides knowledge transfer of ASE expertise from the UK to improve the capabilities of Thailand software companies. Second, the project enables the UK researchers to study the productivity gain through applying ASE techniques into SMEs. The project will include a series of training/hands-on workshop sessions held in Thailand on topics surrounding ASE with the trainers/facilitators from both the UK and Thai partners. This project is an important milestone to establish further UK-Thailand software engineering research collaboration. More info: