PLDI 2018 (series) / MAPL 2018 (series) / MAPL 2018 /
Retrieval on source code: a neural code search
Mon 18 Jun 2018 11:30 - 12:00 at Columbus Ballroom A - Code Search
Searching over large code corpora can be a powerful productivity tool for both beginner and experienced developers because it helps them quickly find examples of code related to their intent. Code search becomes even more attractive if developers could express their intent in natural language, similar to the interaction that Stack Overflow supports.
In this paper, we investigate the use of natural language processing and information retrieval techniques to carry out natural language search directly over source code, i.e. without having a curated Q&A forum such as Stack Overflow at hand. Our preliminary experiments using a benchmark derived from Stack Overflow and GitHub repositories shows promising results.
Mon 18 JunDisplayed time zone: Eastern Time (US & Canada) change
Mon 18 Jun
Displayed time zone: Eastern Time (US & Canada) change
11:00 - 12:00 | |||
11:00 30mTalk | Obfuscation Resilient Search through Executable Classification MAPL Fang-Hsiang Su Columbia University, New York, Jonathan Bell George Mason University, Gail Kaiser Columbia University, New York, Baishakhi Ray Columbia University, New York | ||
11:30 30mTalk | Retrieval on source code: a neural code search MAPL Saksham Sachdev Facebook, Hongyu Li Rice University, Sifei Luan Facebook, Seohyun Kim Facebook, Koushik Sen University of California, Berkeley, Satish Chandra Facebook |