From 92219096ae56af0c56da8fb5cf5f51aaffbcd1ab Mon Sep 17 00:00:00 2001 From: Sheena Panthaplackel Date: Fri, 3 Jul 2020 16:47:03 -0500 Subject: [PATCH] Adding ACL paper --- _publications/panthaplackel2020learning.markdown | 12 ++++++++++++ 1 file changed, 12 insertions(+) create mode 100644 _publications/panthaplackel2020learning.markdown diff --git a/_publications/panthaplackel2020learning.markdown b/_publications/panthaplackel2020learning.markdown new file mode 100644 index 00000000..9c60b7f1 --- /dev/null +++ b/_publications/panthaplackel2020learning.markdown @@ -0,0 +1,12 @@ +--- +layout: publication +title: "Learning to Update Natural Language Comments Based on Code Changes" +authors: S. Panthaplackel, P.Nie, M. Gligoric, J. J. Li, R. J. Mooney +conference: ACL +year: 2020 +bibkey: panthaplackel2020learning +additional_links: + - {name: "ArXiV", url: "https://arxiv.org/abs/2004.12169"} +tags: ["bimodal", "edit", "documentation"], +--- +We formulate the novel task of automatically updating an existing natural language comment based on changes in the body of code it accompanies. We propose an approach that learns to correlate changes across two distinct language representations, to generate a sequence of edits that are applied to the existing comment to reflect the source code modifications. We train and evaluate our model using a dataset that we collected from commit histories of open-source software projects, with each example consisting of a concurrent update to a method and its corresponding comment. We compare our approach against multiple baselines using both automatic metrics and human evaluation. Results reflect the challenge of this task and that our model outperforms baselines with respect to making edits.