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281 results for “source code”
Dataset and Code for "Mining Micro-Patterns of Issue Resolution Processes for Open Source Software Projects"
<p>Dataset and Code for "Mining Micro-Patterns of Issue Resolution Processes for Open Source Software Projects" with README included</p>
Local Voting Z: Source code and datasets.
<p>DataSet with results and code for paper submitted to Computer Networks</p>
Source codes for preprint Newmark algorithm for dynamic analysis with generalized Maxwell model
<p>Snapshot of a GitLab repository, containing Python source codes of results presented in the preprint by the same authors.</p>
parallelpro/numax: Source code for "Realistic Uncertainties for Fundamental Properties of Asteroseismic Red Giants and the Interplay Between Mixing Length, Metallicity and Numax" by Li, Yaguang et al. (2024)
<p>This repository contains the datasets and Python scripts used in the paper "Realistic Uncertainties for Fundamental Properties of Asteroseismic Red Giants and the Interplay Between Mixing Length, Metallicity, and Numax" by Yaguang Li et al. (2024). The stellar models used in this project are available on <a href="https://doi.org/10.5281/zenodo.12815718">Zenodo</a>.</p>
The source code for a new capillary and adsorption‒force model predicting hydraulic conductivity of soil during freeze‒thaw processes
<p>The source code is related to "A New Capillary and Adsorption‒Force Model Predicting Hydraulic Conductivity of Soil during Freeze‒thaw Processes" (Shufeng Qiao, Rui Ma, Yunquan Wang, Ziyong Sun, Helen Kristine French, Yanxin Wang)</p>
Reproduction package for the paper "The open-source sunbather code: Modeling escaping planetary atmospheres and their transit spectra"
<p>This is a reproduction package for the paper "The open-source sunbather code: modeling escaping planetary atmospheres and their transit spectra" by Dion Linssen, Jim Shih, Morgan MacLeod & Antonija Oklopčić (2024). It provides a front-to-end reproduction script to reproduce the results and Figures 1-5 of the paper. Figures 6&7 can be reproduced with the example notebook found in the sunbather installation.</p>
Inverting Cryptographic Hash Functions via Cube-and-Conquer - Results and Source code
<p>Sources, benchmarks, and results for the paper 'Inverting Cryptographic Hash Functions via Cube-and-Conquer' accepted to the Journal of Artificial Intelligence Research.</p> <p> </p>
Source code for CPBS Report 23UNM03 - Enhancing Collaboration through Web-based Visualization and Analysis of Traffic Crash Data
<p>Python source code for the crash mapping web application.</p>
Experimental data, source codes and scripts used in Kotsuki et al. (2024) submitted to GMD
<p>Experimental data, source codes and scripts used in Kotsuki et al. (2024) submitted to GMD</p>
Meteorological data of Ali_Tazhong_Minfeng and Potential Source Analysis Code_FEAST
<p>Meteorological data of Ali_Tazhong_Minfeng and Potential Source Analysis Code_FEAST</p>
Complementary Material for the Paper: "Relationships between Software Architecture and Source Code in Practice: An Exploratory Survey and Interview"
<p>This is the complementary material for the paper: "Relationships between Software Architecture and Source Code in Practice: An Exploratory Survey and Interview", which is currently under review. We provide a brief description of the files and folder.</p> <p><strong>1.</strong> <strong>Valid Responses of the Questionnaire.xlsx </strong>comprises the 87 valid survey responses that were collected by sending the questionnaire to 1000 participants.</p> <p><strong>2. Interview Transcript </strong>includes eight files (Interview Transcript_IP1.docx - Interview Transcript_IP8.docx) of the interview transcripts from eight practitioners.</p> <p><strong>3. Data Labeling & Encoding.mx18 </strong>is the results of data labeling and encoding that were analyzed by the MAXQDA tool. We extracted the answers of open questions from the questionnaire and interview instrument, labeled them with the number of respondents and interviewees (e.g., Respondent1, Respondent2, Interview Transcript_IP1), and encoded the extracted data using Grounded Theory. The file can be opened by MAXQDA 18 or higher versions, which are available at https://www.maxqda.com/ for download. You may also use the free 14-day trial version of MAXQDA 2018, which is available at https://www.maxqda.com/trial for download.</p>
Source code and GCM data for 'Direct radiative effects of airborne microplastics'
<p>Source code and GCM data for 'Direct radiative effects of airborne microplastics' by Revell et al., (2021)</p>
GPUSAT3 Benchmark Data and Source Code
<p>Benchmark data and source code for GPUSAT3.</p> <p>This dataset contains:</p> <p>* decompositions_mccext.zip: Tree decompositions by htd, flowcutter and tamaki for the GPUSAT3 extended benchmark set.</p> <p>* track12.zip: Benchmark instances for the GPUSAT3 extended benchmark.</p> <p>* mccuda-source.zip: GPUSAT3 source code at the time of submission.</p> <p>* experiments.zip: Benchmark results for GPUSAT3 and compared solvers.</p> <p>* </p>
Supplementary source code and evaluation results for submission 44 at SSS 2021
<p>Source code and data for submission 44, SSS 2021</p> <p>Content:</p> <p>+ directory src: source code</p> <p>+ directory lib: libaries used by source code</p> <p>+ directory graphs: input graphs (topology) for programs</p> <p>+ directory results-2021: analysis and simulation data</p> <p>+ run_analyze_cvf_script.sh: script for running analysis</p> <p>+ run_simulation_script.sh: script for running simulation</p>
Bridging Pre-trained Models and Downstream Tasks for Source Code Understanding
<p>Datasets for the paper "Bridging Pre-trained Models and Downstream Tasks for Source Code Understanding"</p>
Identifiers in source code extracted from 13,000,000 public GitHub repositories (October 2016)
<p>101 files, indexed LZO archives for Hadoop/Spark.<br> Each file is text lines with the format:</p> <p>(‘<GitHub repo name>', [(‘<name>', <count>),(‘<name>', <count>),(‘<name>', <count>)])</p> <p> </p>
Coiled tubing contact analysis data and source code
<p>基于数字孪生的连续油管接触分析数据及源代码研究</p>
Learning How to Mutate Source Code from Bug-Fixes
<p>Paper: Learning How to Mutate Source Code from Bug-Fixes</p> <p>Authors: Michele Tufano, Cody Watson, Gabriele Bavota, Massimiliano Di Penta, Martin White, and Denys Poshyvanyk</p> <p>Conference: ICSME 2019 - 35th IEEE International Conference on Software Maintenance and Evolution, October 2-4, 2019, Cleveland, OH, USA<br> </p>
Detection of the Fire Drill anti-pattern: 15 real-world projects with ground truth, issue-tracking data, source code density, models and code
<p>This package contains artifacts for <strong>15</strong> real-world software projects. The data is supposed to aid the detection of the presence of the Fire Drill anti-pattern. We include original data, ground truth, code (experimental setups and models), and notebooks. The data supports two distinct methods of detecting the AP: a) through issue-tracking data, and b) through the underlying source code. This version of the dataset corresponds to <strong>v8</strong> of the <a href="https://arxiv.org/abs/2104.15090v8">technical report</a> and the <a href="https://github.com/MrShoenel/anti-pattern-models/releases/tag/arxiv-v8">GitHub repository</a>. The package includes the following:</p> <p>Original data:</p> <ul> <li>For each project, its <strong>original</strong> artifacts (e.g., wikis, meeting minutes, mentor's notes, etc.)</li> <li>Evaluation of raters' notes by the assessor</li> </ul> <p>Fire Drill in issue-tracking data:</p> <ul> <li><strong>Ground truth</strong> for whether and how strong each project exhibits the Fire Drill AP, on a scale from [0,10]. This was determined by two individual raters, who also reached a consensus.</li> <li>Coefficients for indicators for the first method, per project.</li> <li>Detailed issue-tracing data for each project: what occurred and when.</li> <li>Time logs for each project.</li> </ul> <p>Fire Drill in source-code data:</p> <ul> <li><strong>Four</strong> technical reports that document the developed method of how to translate a description into a detectable pattern, and to use the pattern to detect the presence and to score it (similar to the rating). Also includes a report for how activities were assigned to individual commits.</li> <li>Source code density data (metrics) for each commit in each of the nine projects as a separate dataset.</li> <li>Code: a snapshot of the repository that holds all code, models, notebooks, and pre-computed results, for utmost reproducibility (the code is written in R).</li> </ul>
Magnetic braking with MESA evolutionary models in the single star and LMXB regimes (Gossage et al. 2023) - Inlists, source code, history files
<p>Associated MESA (r11701) inlists, source files (run_star_extras.f90 and run_binary_extras.f), and outputs (history files for single star models --but the same for binary star models is available upon request) used in producing models featured in <a href="https://ui.adsabs.harvard.edu/abs/2022arXiv221212037G/abstract">Gossage et al. 2023 - Magnetic braking with MESA evolutionary models in the single star and LMXB regimes</a>). README files are included, and please contact to alert me of any issues.</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.