activity
20182025
most citedCoditT5: Pretraining for Source Code and Natural Language Editing

5 citations · 15 across the 14 of their papers we have counts for

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9 papers · 1 filter

cs.SE2025★ 1 cited

A Tool for Generating Exceptional Behavior Tests With Large Language Models

Linghan Zhong, Samuel Yuan, Jiyang Zhang +4

Exceptional behavior tests (EBTs) are crucial in software development for verifying that code correctly handles unwanted events and throws appropriate exceptions. However, prior re…

cs.SE2024★ 3 cited

exLong: Generating Exceptional Behavior Tests with Large Language Models

Jiyang Zhang, Yu Liu, Pengyu Nie +2

Many popular programming languages, including C#, Java, and Python, support exceptions. Exceptions are thrown during program execution if an unwanted event happens, e.g., a method…

cs.SE2023

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…

cs.SE2023

pytest-inline: An Inline Testing Tool for Python

Yu Liu, Zachary Thurston, Alan Han +3

We present pytest-inline, the first inline testing framework for Python. We recently proposed inline tests to make it easier to test individual program statements. But, there is no…

cs.SE2023★ 1 cited

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…

cs.SE2022★ 5 cited

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…

cs.SE2022

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…

cs.SE2021

Impact of Evaluation Methodologies on Code Summarization

Pengyu Nie, Jiyang Zhang, Junyi Jessy Li +2

There has been a growing interest in developing machine learning (ML) models for code summarization tasks, e.g., comment generation and method naming. Despite substantial increase…

cs.SE2018★ 1 cited

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…