Songlin Jia is a Ph.D. student since 2021 at Purdue CS. Interested in programming languages, he currently works with Prof. Tiark Rompf. He has been working on a performant, full-fledged symbolic execution engine by staging, and recently its underlying graph IR, and reachability type systems.
Songlin used to be a teaching assistant for CS502 Compiling and Programming Systems and CS565 Programming Languages.
Songlin got his bachelor’s degree at Shanghai Jiao Tong University, where he used to work on scientific computing and program analysis.
Publication
Polymorphic Reachability Types: Tracking Freshness, Aliasing, and Separation in Higher-Order Generic Programs
Guannan Wei, Oliver Bračevac, Songlin Jia, Yuyan Bao, and Tiark Rompf
in the 51st ACM SIGPLAN Symposium on Principles of Programming Languages (POPL), 2024
Graph IRs for Impure Higher-Order Languages: Making Aggressive Optimizations Affordable with Precise Effect Dependencies
Oliver Bračevac, Guannan Wei, Songlin Jia, Supun Abeysinghe, Yuxuan Jiang, Yuyan Bao, and Tiark Rompf
in ACM SIGPLAN International Conference on Object-Oriented Programming Systems, Languages, and Applications (OOPSLA), 2023
Compiling Parallel Symbolic Execution with Continuations
Guannan Wei, Songlin Jia, Ruiqi Gao, Haotian Deng, Shangyin Tan, Oliver Bračevac, and Tiark Rompf
in IEEE/ACM 45th International Conference on Software Engineering (ICSE), 2023
Annotating, Tracking, and Protecting Cryptographic Secrets with CryptoMPK
Xuancheng Jin, Xuangan Xiao, Songlin Jia, Wang Gao, Dawu Gu, Hang Zhang, Siqi Ma, Zhiyun Qian, and Juanru Li
in IEEE Symposium on Security and Privacy (SP), 2022
Accelerating SM2 Digital Signature Algorithm Using Modern Processor Features
Long Mai, Yuan Yan, Songlin Jia, Shuran Wang, Jianqiang Wang, Juanru Li, Siqi Ma, and Dawu Gu
in International Conference on Information and Communications Security, 2019
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