7 citations · 30 across the 18 of their papers we have counts for
6 papers · 1 filter
Multilingual Code Co-Evolution Using Large Language Models
Jiyang Zhang, Pengyu Nie, Junyi Jessy Li +1
Many software projects implement APIs and algorithms in multiple programming languages. Maintaining such projects is tiresome, as developers have to ensure that any change (e.g., a…
Learning Deep Semantics for Test Completion
Pengyu Nie, Rahul Banerjee, Junyi Jessy Li +2
Writing tests is a time-consuming yet essential task during software development. We propose to leverage recent advances in deep learning for text and code generation to assist dev…
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…
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…
Executable Trigger-Action Comments
Pengyu Nie, Rishabh Rai, Junyi Jessy Li +3
Natural language elements, e.g., todo comments, are frequently used to communicate among the developers and to describe tasks that need to be performed (actions) when specific cond…