Add He et al. 2021

Miltos Allamanis · Miltos Allamanis · commit 1d54e3b20bea · 2021-05-21T16:03:58.000+01:00
diff --git a/_publications/he2021learning.markdown b/_publications/he2021learning.markdown
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+---
+layout: publication
+title: "Learning to Find Naming Issues with Big Code and Small Supervision"
+authors: Jingxuan He, Cheng-Chun Lee, Veselin Raychev, Martin Vechev
+conference: PLDI
+year: 2021
+bibkey: he2021learning
+tags: ["repair"]
+---
+We introduce a new approach for finding and fixing naming
+issues in source code. The method is based on a careful
+combination of unsupervised and supervised procedures: (i)
+unsupervised mining of patterns from Big Code that express
+common naming idioms. Program fragments violating such
+idioms indicates likely naming issues, and (ii) supervised
+learning of a classifier on a small labeled dataset which filters
+potential false positives from the violations.
+
+We implemented our method in a system called
+Namer and evaluated it on a large number of Python and Java programs.
+We demonstrate that Namer is effective in finding naming mistakes
+in real world repositories with high precision (∼70%).
+Perhaps surprisingly, we also show that existing deep learning methods
+are not practically effective and achieve low precision in finding naming issues (up to ∼16%).
