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49 results for “continuous integration”
Minimizing the Side Effect of Cost-saving Build Selection in Continuous Integration
<p>Data set on Minimizing the Side Effect of Cost-saving Build Selection in Continuous Integration</p>
Figure 1 Continued from: Goulding TC, Khalil M, Tan SH, Dayrat B (2018) Integrative taxonomy of a new and highly-diverse genus of onchidiid slugs from the Coral Triangle (Gastropoda, Pulmonata, Onchidiidae). ZooKeys 763: 1-111. https://doi.org/10.3897/zookeys.763.21252
Figure 1 Continued
Temporary Epicardial Pace Wire With Integrated Sensor for Continuous Postoperative Monitoring of Myocardial Function
ClinicalTrials.gov study NCT04886934. IPD Sharing: NO. Countries: 1. Publications: 0.
Feasibility of an Integrated Medical Care Program for Patients With Continuing Health Complaints After Amalgam Removal
ClinicalTrials.gov study NCT02081664. IPD Sharing: NO. Countries: 1. Publications: 0.
When Should I Build? A Collection of Cost-efficient Approaches to Running Builds in Continuous Integration.
<p>Replication package.</p>
RIPK3 activation leads to cytokine synthesis that continues after loss of cell membrane integrity
GEO Series GSE134234. Mus musculus. 24 samples. Type: Expression profiling by high throughput sequencing.
Revisiting Machine Learning based Test Case Prioritization for Continuous Integration
<p>Aborted version</p>
The Impact of Continuous Integration into Test Code Evolution: An Empirical Study
<p>The set of datasets used during the study</p>
Revisiting Machine Learning based Test Case Prioritization for Continuous Integration
<p>This repository contains a replication package for a research paper submitted to the 45th International Conference on Software Engineering (https://conf.researchr.org/home/icse-2023). We provide our code, data, and result for the ease of replicating our experiments.</p> <p><strong>Code</strong></p> <ul> <li>In the <strong>collect_data</strong> subdirectory, scripts for constructing TCP datasets are provided. We do dependency analysis using Understand (https://www.scitools.com/), so please download the related tools in advance.</li> <li>In the<strong> rl</strong> subdirectory, we provide the python implementation for algorithms RL, COLEMAN, PPO2-PO, ACER-PA, PPO1-LI.</li> <li>In the <strong>supervised_learning</strong> subdirectory, we provide implementations for MART, RankNet, RankBoost, CA, L-MART, which mainly rely on Ranklib (https://sourceforge.net/p/lemur/wiki/RankLib/.). We also provide implementation for DeepOrder.</li> </ul> <p><strong>Data</strong></p> <ul> <li>The <strong>origin</strong> subdirectory contains the original datasets collected from github using our scripts, including 11 projects.</li> <li>The <strong>smote</strong> subdirectory contains the datasets pre-processed by SMOTE.</li> </ul> <p><strong>Result</strong></p> <ul> <li>Results for <strong>RQ1</strong>, <strong>RQ2</strong>, <strong>RQ3</strong>, and <strong>threats to validity</strong> are provided in the corresponding subdirectories. Scripts for plotting figures are also provided.</li> </ul> <p><strong>Reference</strong></p> <p>We adopt code from previous work</p> <p>Learning-to-Rank vs Ranking-to-Learn: Strategies for Regression Testing in Continuous Integration (https://dl.acm.org/doi/abs/10.1145/3377811.3380369) Github repository: https://github.com/icse20/RT-CI</p> <p>Reinforcement Learning for Test Case Prioritization (https://ieeexplore.ieee.org/abstract/document/9394799) Github repository: https://github.com/moji1/tp_rl</p> <p>DeepOrder: Deep Learning for Test Case Prioritization in Continuous Integration Testing (https://ieeexplore.ieee.org/abstract/document/9609187) Github repository: https://github.com/AizazSharif/DeepOrder-ICSME21</p> <p>A Multi-Armed Bandit Approach for Test Case Prioritization in Continuous Integration Environments (https://ieeexplore.ieee.org/abstract/document/9086053) Github repository: https://github.com/jacksonpradolima/coleman4hcs</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.