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Found 11 papers, 6 papers with code
Updated Headline Generation: Creating Updated Summaries for Evolving News Stories
We propose the task of updated headline generation, in which a system generates a headline for an updated article, considering both the previous article and headline.
Unsupervised Evaluation of Code LLMs with Round-Trip Correctness
To evaluate code large language models (LLMs), research has relied on a few small manually curated benchmarks, such as HumanEval and MBPP, which represent a narrow part of the real-world software domains.
Using Developer Discussions to Guide Fixing Bugs in Software
Automatically fixing software bugs is a challenging task.
CoditT5: Pretraining for Source Code and Natural Language Editing
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 to reason about edits.
Learning to Describe Solutions for Bug Reports Based on Developer Discussions
When a software bug is reported, developers engage in a discussion to collaboratively resolve it.
Learning to Generate Code Comments from Class Hierarchies
Descriptive code comments are essential for supporting code comprehension and maintenance.
Leveraging Class Hierarchy for Code Comprehension
Object-oriented programming languages enable a hierarchical class structure, which provides rich contextual information to guide code comprehension and synthesis.
Deep Just-In-Time Inconsistency Detection Between Comments and Source Code
For extrinsic evaluation, we show the usefulness of our approach by combining it with a comment update model to build a more comprehensive automatic comment maintenance system which can both detect and resolve inconsistent comments based on code changes.
Copy that! Editing Sequences by Copying Spans
Neural sequence-to-sequence models are finding increasing use in editing of documents, for example in correcting a text document or repairing source code.
Learning to Update Natural Language Comments Based on Code Changes
We formulate the novel task of automatically updating an existing natural language comment based on changes in the body of code it accompanies.
Associating Natural Language Comment and Source Code Entities
Comments are an integral part of software development; they are natural language descriptions associated with source code elements.
