Kok Wong is a software engineer with six years’ experience building robust backend and testing infrastructure, based in Singapore. He contributes to prominent open-source projects such as sqlancer—improving automated database testing and DuckDB canonicalization—and Manticore, where he enhanced server-side tooling, protobufs, and gRPC error handling. Comfortable across QA, test automation, and backend development, Kok favors tackling “cool problems” and learning new techniques to harden systems. His background includes rigorous STEM education at NUS High School and ongoing engagement with NUS communities like NUSHackers and module customization efforts. Colleagues would describe him as a pragmatic engineer who brings thoughtful improvements to reliability and observability that aren’t always obvious from product-level features. He’s equally at home iterating on low-level test logic as on shaping server behavior for symbolic execution and blockchain-focused tooling.
6 years of coding experience
University Town College Programme (UTCP), University Town College Programme (UTCP) at Residential College 4 (RC4)
NUS High School of Mathematics & Science
Dual Enrolment, Dual Enrolment at National University of Singapore
Contributions:21 commits, 5 PRs, 1 comment in 4 months
Contributions summary:Kok primarily contributes to the server-side components of the Manticore project. Their work includes implementing testing functionality, specifically for the MUI Server with both native and EVM features. They addressed Python package structure issues and modified the protobuf specifications to include features such as state parent information and hooks. They also added functionality to stop the server and integrate gRPC status code-based error handling.
Automated testing to find logic and performance bugs in database systems
Role in this project:
QA Engineer / Test Automation Engineer
Contributions:3 reviews, 15 commits, 6 PRs in 6 months
Contributions summary:Kok primarily contributed to enhancing the automated testing infrastructure within the `sqlancer/sqlancer` repository. Their work included adding and testing new methods for comparing result sets, specifically focusing on functions that allow for canonicalization of results. Furthermore, the user integrated DuckDB-specific canonicalization rules into the testing framework, enabling more robust and accurate comparison of results from the DuckDB database system. These contributions improved the testing coverage and reliability of SQLancer for various database systems.
dbms-testingdbmsmysqltidbtesting
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