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9 results for “Test Case Generation”
Data Set Used in Combinatorial Modeling and Test Case Generation for Industrial Control Software using ACTS
<p>This document contains the data set used for the study Combinatorial Modeling and Test Case Generation for Industrial Control Software using ACTS that is currently in submission.</p>
Learning How to Search: Generating Effective Test Cases Through Adaptive Fitness Function Selection
<p>Data Package for "Learning How to Search: Generating Effective Test Cases Through Adaptive Fitness Function Selection"</p> <p>This package contains data generated as part of our experiments on adaptive fitness function selection as part of unit test generation for Java systems.</p> <p>This paper is currently under submission. A draft of the paper is included in the data package.</p> <p>This package contains experimental data (in folder "experiment_data"), including goal attainment, fault detection, time per generation, and choices made by the reinforcement learning algorithm. In the folder "test_suites", the suites generated by each technique are included for each project. </p> <p>If you have questions, please contact Gregory Gay at greg@greggay.com.</p> <p>NOTE: A small number of items are currently missing from this data package and will be added shortly. Please make sure you have the latest version of this package.</p>
Enhanced Synthetic Texas 2,000 bus (ACTIVSg2000) test case w/synthesized dynamic parameters of wind generation and protective devices
<p>Enhanced Synthetic Texas 2,000 bus (ACTIVSg2000) test case w/synthesized dynamic parameters of wind generation and protective devices<br> Compatible with PowerWorld v21, adapted from ACTIVSg2000.pwb (<a href="https://electricgrids.engr.tamu.edu/electric-grid-test-cases/activsg2000/">https://electricgrids.engr.tamu.edu/electric-grid-test-cases/activsg2000/</a>)<br> <br> Used as a test case for the paper: `Electrical Grid Resilience Metric with Uncertainty.' Power Systems Computation Conference, under review. </p> <p>Wind Dynamic Parameters:<br> Machine models:<br> -REGC_A: Renewable Energy Generator/Converter.</p> <p> Machine governors:<br> -WTGT_A: Wind Turbine Generator Drive-train Model.</p> <p> Machine excitation system:<br> -REEC_A: Renewable Energy Electrical Control Model.</p> <p>Protective relays:<br> -DLSH: Rate of Frequency Load Shedding Model (used on all loads in network).<br> -LVSH: Undervoltage Load Shedding Model (used on all loads in network).<br> -TIOCR1: Time inverse overcurrent relay (used on all lines in network).<br> -FRQTPAT: Under frequency generator trip relay (used on all machines).<br> -LHVRT: Low/High Voltage Ride through Generator Protection (used on all machines).</p> <p> </p> <p>This research was completed by Idaho National Laboratory with funding<br> from the U.S. Department of Energy Wind Energy Technologies Office. Idaho National Laboratory is operated<br> by Battelle Energy Alliance under contract No. DE AC07-05ID14517.</p>
Supplementary data for "Enhancing Resource-based Test Case Generation For RESTful APIs with SQL Handling"
<p>Supplement to: <em>Enhancing Resource-based Test Case Generation For RESTful APIs with SQL Handling</em></p> <p>In this repository, we provide <em>tests</em> and their <em>coverage reports</em> (conducted by Intellij coverage reports) that are used in the Discussion section of the paper.</p>
Automated Test Case Generation - Master Thesis
<p>This is the dataset used and created within my master thesis.</p>
TGenAI: LLM-based Approach for Functional Test Case Generation for IoT System
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Systematic Mapping Appendix - Identifying approaches to generate test cases in model-based testing: a
<p>The appendix present the complete mapping of individual studies and its categories.</p>
Replication Package: "Simulation-based Test Case Generation for Unmanned Aerial Vehicles in the Neighborhood of Real Flights"
<p><strong>Structure:</strong></p> <p>For each of the experiments, conducted for our Research questions, we include the following:</p> <p>1. An spreadsheet file containing the aggregated experiment results</p> <ul> <li>first tab: aggregated data for all the 10 repetitions, and metrics reported in the paper</li> <li>raw logs for each of 10 repetitions in separate tabs</li> </ul> <p>2. Experiment summary for each of the 10 repetitions</p> <ul> <li>plots of the evaluated solutions at each iteration, and their fitness values</li> <li>the plot of the overall progress of the fitness values over iterations</li> <li>the raw log containing the details of computations for each iteration</li> </ul> <p>3. Experiment simulation logs (raw simulation outputs)</p> <ul> <li>'.ulg' flight logs of the solutions evaluated at each iteration ( 'n' parallel simulations at each iteration)</li> <li>only the repetition with the best final result is included. We exclude the other repetitions since the total space needed is too large (more than 200 GB).</li> </ul>
Reinforcement Learning-Based Test Case Generation
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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.