Learning to Align the Source Code to the Compiled Object Code

By Dor Levy, Lior Wolf. 2017

17 citations recorded by the source corpus.

Subfields: Natural Language Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Natural Language Processing

1. Charles Sutton
2. Premkumar T. Devanbu
3. Miltiadis Allamanis
4. Earl T. Barr
5. Michael Pradel
6. Torsten Hoefler
7. Tal Ben-Nun
8. Alice Shoshana Jakobovits

Citations in the corpus

• A Survey of Machine Learning for Big Code and Naturalness (2017, background): “ural Language Distributed Commit Message Koc et al. [106] Bytecode False Positives Distributed Program Analysis Kremenek et al. [108] Partial PDG Ownership Factor (GM) Pointer Ownership Levy and Wolf [114] Statements Alignment Distributed Decompiling Li et al. [115] Memory Heap Separation Logic Dist”
• Neural Code Comprehension: A Learnable Representation of Code Semantics (2018, background): “Code Representation Previous research focuses on embedding high-level programming languages such as Java [20, 30], C [41], or OpenCL [18] in the form of tokens or statements, as well as lower (1)Code, datasets, trained embeddings, and results available at https://www.”