The ruby type checker

By Brianna M. Ren, John Toman, T. Stephen Strickland, Jeffrey S. Foster. 2013

34 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Hardware and Architecture, Information Systems, 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. Georgios Gousios
2. Satish Chandra
3. Michael Pradel
4. Jason Liu
5. Milod Kazerounian
6. Jeffrey S. Foster
7. Prem Devanbu
8. Kevin Jesse

In Hardware and Architecture

1. Satish Chandra
2. Georgios Gousios

In Information Systems

1. Georgios Gousios
2. Satish Chandra
3. Jason Liu
4. Michael Pradel
5. Jeffrey S. Foster
6. Milod Kazerounian
7. Charles Sutton
8. Prem Devanbu

In Program Analysis & Verification

1. Georgios Gousios
2. Satish Chandra
3. Jason Liu
4. Michael Pradel
5. Milod Kazerounian
6. Jeffrey S. Foster
7. Prem Devanbu
8. Kevin Jesse

Citations in the corpus

• TypeWriter: neural type prediction with search-based validation (2019, background): “Dynamic type inference [3, 30] tracks data flows between functions, e.”
• Design and evaluation of gradual typing for python (2014, unknown): “[22].”
• Learning to Predict User-Defined Types (2023, unknown): “Type Inference Dynamic type inference techniques [58], [59] and type checkers [60], [61], [62], [63] achieve soundness by enforcing type constraints.”