23 citations · 56 across the 3 of their papers we have counts for
3 papers
cs.SE2019★ 17 cited
Learning Blended, Precise Semantic Program Embeddings
Ke Wang, Zhendong Su
Learning neural program embeddings is key to utilizing deep neural networks in program languages research --- precise and efficient program representations enable the application o…
cs.LG2019★ 23 cited
COSET: A Benchmark for Evaluating Neural Program Embeddings
Ke Wang, Mihai Christodorescu
Neural program embedding can be helpful in analyzing large software, a task that is challenging for traditional logic-based program analyses due to their limited scalability. A key…
cs.PL2019★ 16 cited
Learning Scalable and Precise Representation of Program Semantics
Ke Wang
Neural program embedding has shown potential in aiding the analysis of large-scale, complicated software. Newly proposed deep neural architectures pride themselves on learning prog…