5 citations · 9 across the 6 of their papers we have counts for
9 papers
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…
A Framework for Multi-stage Bonus Allocation in meal delivery Platform
Zhuolin Wu, Li Wang, Fangsheng Huang +8
Online meal delivery is undergoing explosive growth, as this service is becoming increasingly popular. A meal delivery platform aims to provide excellent and stable services for cu…
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…
Learning to Format Coq Code Using Language Models
Pengyu Nie, Karl Palmskog, Junyi Jessy Li +1
Should the final right bracket in a record declaration be on a separate line? Should arguments to the rewrite tactic be separated by a single space? Coq code tends to be written in…