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.

• What software engineering modeling, methods, techniques, and standards have been applied in the creation of data science applications (or projects) as recorded in the literature (ACM Digital Library, IEEE Xplore, and Scopus)? 

• What software engineering modeling, methods, and techniques have been directly applied to develop and maintain data science applications by professionals (as seen from the GitHub repositories and the interviews/survey)? And what is their effectiveness?

• What are the software engineering techniques used to develop and maintain data science applications? What SE framework can be used to better the management and maintenance of the DS projects?

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.