Our team
We are part of the Trustworthy Software Systems group from the
National Unviersity of Singapore's School of Computing. In our
research, we strive to enable
secure and
trustworthy software systems.
In line with this, we focus on software testing and analysis,
and in particular have contributed to the areas of Automated
Program Repair, Fuzzing and Symbolic Execution. We believe
that this knowledge can be utilised to ensure that Language
Model based agents can create code that developers can use
with confidence.
Ridwan Shariffdeen
Ridwan Shariffdeen holds a Ph.D from the the National
University of Singapore. He has more than 8 years of
experience working on the industry and academia focusing on
software and system security.
His research focus on software security, automated program
repair, software testing and trustworthy software systems. His
research have been published on top-tier conferences and
journals such as ICSE, PLDI, TOSEM and IEEE CLOUD.
Yuntong Zhang
Yuntong Zhang is currently a third-year PhD student at National University of Singapore. He is generally interested in topics related to improving quality and security guarantees of software systems. His current research focuses on fostering evidence and practicality in automated programming, where code is generated by automated tools or machine learning models. He is actively working on Language Model agents for code generation and program improvements. Previously, he has worked on analysis-based program repair for security vulnerabilities, as well as software sanitizers for vulnerability detection.
Haifeng Ruan
Ruan Haifeng is a third-year PhD student at School of Computing, National University of Singapore. His research focuses on program testing and repair and trustworthy auto-programming.
Martin Mirchev
Martin Mirchev is currently a second-year PhD student at National University of Singapore. He is interested in topics related to providing trust and certification guarantees of software systems. His current research focuses on providing such certifications in automated programming, where code is generated by automated tools or machine learning models.
Abhik Roychoudhury
Abhik Roychoudhury is a Provost’s Chair Professor of Computer
Science at the National University of Singapore. Abhik’s
research focuses on software testing and analysis, software
security and trust-worthy software construction.
His research was honored with IEEE TCSE New Directions Award
in 2022 (jointly with Cristian Cadar) for contributions to
symbolic execution, as well as with International Conference
on Software Engineering (ICSE) 2023 Most Influential Paper
Award for an ICSE 2013 paper suggesting semantic approaches
towards program repair. His research group is known for
contributions to automatic programming, program repair,
fuzzing and symbolic execution.
