Publications | Di Wang

Zhichao Guan, Yiyuan Cao, Tailai Yu, Ziheng Wang, Di Wang, Zhenjiang Hu (2024). Semantics Lifting for Syntactic Sugar. In OOPSLA.

Long Pham, Di Wang, Feras A. Saad, Jan Hoffmann (2024). Programmable MCMC with Soundly Composed Guide Programs. In OOPSLA.

Ke Sun, Di Wang, Sheng Chen, Meng Wang, Dan Hao (2024). Formalizing, Mechanizing, and Verifying Class-based Refinement Types. In ECOOP.

Di Wang, Thomas Reps (2024). Newtonian Program Analysis of Probabilistic Programs. In OOPSLA.

Ruyi Ji, Yuwei Zhao, Yingfei Xiong, Di Wang, Lu Zhang, Zhenjiang Hu (2024). Decomposition-Based Synthesis for Applying Divide-and-Conquer-Like Algorithmic Paradigms. In TOPLAS.

Ankush Das, Di Wang, Jan Hoffmann (2023). Probabilistic Resource-Aware Session Types. In POPL.

Di Wang, Jan Hoffmann, Thomas Reps (2021). Sound Probabilistic Inference via Guide Types. In PLDI.

Di Wang, Jan Hoffmann, Thomas Reps (2021). Central Moment Analysis for Cost Accumulators in Probabilistic Programs. In PLDI.

Di Wang, David M. Kahn, Jan Hoffmann (2020). Raising Expectations: Automating Expected Cost Analysis with Types. In ICFP.

Tristan Knoth, Di Wang, Adam Reynolds, Jan Hoffmann, Nadia Polikarpova (2020). Liquid Resource Types. In ICFP.

Tristan Knoth, Di Wang, Nadia Polikarpova, Jan Hoffmann (2019). Resource-Guided Program Synthesis. In PLDI.

Di Wang, Jan Hoffmann, Thomas Reps (2019). A Denotational Semantics for Low-Level Probabilistic Programs with Nondeterminism. In MFPS.

Di Wang, Jan Hoffmann (2019). Type-Guided Worst-Case Input Generation. In POPL.

Di Wang, Jan Hoffmann, Thomas Reps (2018). PMAF: An Algebraic Framework for Static Analysis of Probabilistic Programs. In PLDI.

Peng Wang, Di Wang, Adam Chlipala (2017). TiML: A Functional Language for Practical Complexity Analysis with Invariants. In OOPSLA.

Hao Tang, Di Wang, Yingfei Xiong, Lingming Zhang, Xiaoyin Wang, Lu Zhang (2017). Conditional Dyck-CFL Reachability Analysis for Complete and Efficient Library Summarization. In ESOP.