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26
datasets available to search
ShareScore release 0.7.1
Dataset results
26 results for “Code Comment”
Dataset of "Inferring Fine-grained Traceability Links between Javadoc Comments and JUnit Test Code"
<p>Dataset of Inferring Fine-grained Traceability Links between Javadoc Comments and JUnit Test Code</p>
Challenges in analysis of code review comments. Various BERTopic parameters and impact on coherence.
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Advancing Automated Code Review Comment Generation Using Large Language Models
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Dataset of "Primers or Reminders? The Effects of Existing Review Comments on Code Review"
<p>Dataset of "Primers or Reminders? The Effects of Existing Review Comments on Code Review".</p> <p>See README.md for more information. </p>
Code and Comments Dataset
<p>The code and comment data are a compilation of code blocks and their related comments. Doxygen successfully ran on 106,304 different GitHub projects. A total of 16,115,540 code-comment pairs were obtained by running Doxygen on C, C++, Java, and Python projects. The source code in these pairs can be of various granularities: classes, methods, functions, and variables. These data provide an association between source code and a description of that code. The data directory contains one directory for each project downloaded from GitHub. These project directories are named with the GraphQL ID from GitHub's GraphQL API. In each of these GraphQL-ID labeled directories, there is a license.txt, a url.txt, and a derivatives directory. The license.txt contains the license for the original project, the url.txt contains a link to the original project on GitHub, and the derivatives directory contains the output of running Doxygen on the project. The Doxygen output is a json file, structured as a dictionary with a "contents" field, where the value of that field is a list of lists containing 3 elements each. The following is a mock example of that structure: {"contents": [[path1, snippet1, comment1], [path2, snippet2, comment2], ...]}. The "path" is a filepath relative to the original project from which the code and comment were obtained. The "snippet" is the actual body of the source code. The "comment" is the corresponding comment. For convenience, there is also an initialize.py python script that iterates through all of the json files in the data directory and stores them in an SQLite database called "all_data.db".</p>
Replication Package of ''Automated Bug Fixing: Do Code Comments Matter?"
<p>This repository contains the replication package of "Automated Bug Fixing: Do Code Comments Matter?".</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.