Thanwadee Sunetnanta (PI), Morakot Choetkiertikul, Chaiyong Ragkhitwetsagul, Srisupa Palakvangsa Na Ayudhya

ICT SDG Funding 2024

Funding Agency: Faculty of ICT, Mahidol University

This project aims to

• Study the existing body of knowledge about green software development

• Study the awareness of the Thai software industry regarding green software development

• Provide a suggestion or framework for supporting green 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.   

Thanwadee Sunetnanta

SWITCHSEA Program, 2021-2022

Funding Agency: APNIC Foundation

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Morakot Choetkiertikul

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

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

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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.