Automatically generating features for learning program analysis heuristics for C-like languages

By Kwonsoo Chae, Hakjoo Oh, Kihong Heo, Hongseok Yang. 2017

28 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Software, Program Analysis & Verification

How researchers see this paper

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

In Artificial Intelligence

1. Miltiadis Allamanis
2. Charles Sutton
3. Earl T. Barr
4. Premkumar T. Devanbu
5. Eran Yahav
6. Uri Alon
7. Rishabh Singh
8. Rafael-Michael Karampatsis

In Information Systems

1. Charles Sutton
2. Miltiadis Allamanis
3. Earl T. Barr
4. Premkumar T. Devanbu
5. Michael Pradel
6. Rishabh Singh
7. Rafael-Michael Karampatsis
8. Eran Yahav

In Software

1. Charles Sutton
2. Miltiadis Allamanis
3. Earl T. Barr
4. Premkumar T. Devanbu
5. Michael Pradel
6. Rishabh Singh
7. Marc Brockschmidt
8. Sahil Bhatia

In Program Analysis & Verification

1. Miltiadis Allamanis
2. Charles Sutton
3. Earl T. Barr
4. Premkumar T. Devanbu
5. Eran Yahav
6. Uri Alon
7. Marc Brockschmidt
8. Omer Levy

Citations in the corpus

• A Survey of Machine Learning for Big Code and Naturalness (2017, methodology): “[35] reduce automatically (without machine learning) a program to a set of data-flow graphs, manually extract features from them.”