21 citations · 31 across the 7 of their papers we have counts for
13 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…
Inline Tests
Yu Liu, Pengyu Nie, Owolabi Legunsen +1
Unit tests are widely used to check source code quality, but they can be too coarse-grained or ill-suited for testing individual program statements. We introduce inline tests to ma…
Compiler Testing using Template Java Programs
Zhiqiang Zang, Nathan Wiatrek, Milos Gligoric +1
We present JAttack, a framework that enables template-based testing for compilers. Using JAttack, a developer writes a template program that describes a set of programs to be gener…
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…
Roosterize: Suggesting Lemma Names for Coq Verification Projects Using Deep Learning
Pengyu Nie, Karl Palmskog, Junyi Jessy Li +1
Naming conventions are an important concern in large verification projects using proof assistants, such as Coq. In particular, lemma names are used by proof engineers to effectivel…