5 citations · 8 across the 3 of their papers we have counts for
7 papers
Using Developer Discussions to Guide Fixing Bugs in Software
Sheena Panthaplackel, Milos Gligoric, Junyi Jessy Li +1
Automatically fixing software bugs is a challenging task. While recent work showed that natural language context is useful in guiding bug-fixing models, the approach required promp…
CoditT5: Pretraining for Source Code and Natural Language Editing
Jiyang Zhang, Sheena Panthaplackel, Pengyu Nie +2
Pretrained language models have been shown to be effective in many software-related generation tasks; however, they are not well-suited for editing tasks as they are not designed t…
Learning to Generate Code Comments from Class Hierarchies
Jiyang Zhang, Sheena Panthaplackel, Pengyu Nie +3
Descriptive code comments are essential for supporting code comprehension and maintenance. We propose the task of automatically generating comments for overriding methods. We formu…
Deep Just-In-Time Inconsistency Detection Between Comments and Source Code
Sheena Panthaplackel, Junyi Jessy Li, Milos Gligoric +1
Natural language comments convey key aspects of source code such as implementation, usage, and pre- and post-conditions. Failure to update comments accordingly when the correspondi…
Copy that! Editing Sequences by Copying Spans
Sheena Panthaplackel, Miltiadis Allamanis, Marc Brockschmidt
Neural sequence-to-sequence models are finding increasing use in editing of documents, for example in correcting a text document or repairing source code. In this paper, we argue t…
Learning to Update Natural Language Comments Based on Code Changes
Sheena Panthaplackel, Pengyu Nie, Milos Gligoric +2
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 t…