On the generalizability of Neural Program Models with respect to semantic-preserving program transformations

Author:

Rabin Md Rafiqul IslamORCID,Bui Nghi D.Q.,Wang KeORCID,Yu Yijun,Jiang LingxiaoORCID,Alipour Mohammad AminORCID

Funder

Singapore Management University

Publisher

Elsevier BV

Subject

Computer Science Applications,Information Systems,Software

Reference64 articles.

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3. M. Allamanis, M. Brockschmidt, M. Khademi, Learning to Represent Programs with Graphs, in: International Conference on Learning Representations, 2018.

4. E. Dinella, H. Dai, Z. Li, M. Naik, L. Song, K. Wang, Hoppity: Learning Graph Transformations to Detect and Fix Bugs in Programs, in: International Conference on Learning Representations, 2019.

5. COSET: A benchmark for evaluating neural program embeddings;Wang,2019

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