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478 results for “artifact”
Artifacts of the Article: "Guidelines for Using Financial Incentives in Software-Engineering Experimentation"
Open the record for dataset details and reuse information.
Artifact for Misconceptions in Finite-Trace and Infinite-Trace Linear Temporal Logic
<p>Welcome!</p> <p>This artifact contains the survey instruments, final catalog, and labeled responses from our FM 2024 paper:</p> <p><em>Misconceptions in Finite-Trace and Infinite-Trace Linear Temporal Logic</em></p> <ul> <li>The artifact is primarily a dataset. There is no required software to run.</li> <li>The instruments and catalog are PDF files.</li> <li>The labeled responses are in spreadsheets, which we provide as open document files (`.ods`) with HTML as a backup.</li> </ul>
Raw trace data for GVARP artifact
<p>Raw trace containing ANT-MOC tracing data with 128 GPUs.</p> <div> <div>One should install the gvarp artifact before analyzing this raw trace: <a href="../records/10975567">GVARP-artifact (zenodo.org)</a></div> <div> </div> <div>To analysis the performance variance in this raw trace, one can use the following commands:</div> <div> <pre><code>GVARP_HOME=/path/to/gvarp-artifact VERSION=500_stream_2024_02_15_03_08_20 variance_analysis -i measurement_${VERSION} -o variance_${VERSION} -f python3 ${GVARP_HOME}/scripts/analysis/variance/heatmap.py --input variance_${VERSION} --output heatmap_${VERSION}</code></pre> <p>The analysis results should be presented as a figure (e.g., comm.png) located in the folder heatmap_${VERSION}.</p> </div> </div>
Comparing developer-provided to user-provided tests for fault localization and automated program repair: Artifacts
<p>Artifacts for the paper <em>Comparing developer-provided to user-provided tests for fault localization and automated program repair.</em></p> <p>Note that the artifacts are maintained in the following repositories:</p> <ul> <li>https://github.com/rjust/defects4j</li> <li>https://bitbucket.org/rjust/tests-tested-data</li> <li>https://bitbucket.org/rjust/fault-localization-data</li> </ul>
Linking Sketches and Diagrams to Source Code Artifacts — Supplementary Material
<p>Sketches and diagrams play an important role in the daily work of software developers. If they are archived, they are often detached from the source code they document, because there is no adequate tool support to assist developers in capturing, archiving, and retrieving sketches related to certain source code artifacts. We implemented <em>SketchLink</em> to increasing the value of sketches and diagrams created during software development by supporting developers in these tasks. Our prototype implementation provides a web application that employs the camera of smartphones and tablets to capture analog sketches, but can also be used on desktop computers to upload, for instance, computer-generated diagrams. We also implemented a plugin that embeds the links in Javadoc comments and visualizes them in situ in the source code editor as graphical icons for the IntelliJ Java IDE. Besides being a useful software documentation tool, SketchLink also enables developers to navigate through their source code using the linked sketches and diagrams.</p> <p>This dataset contains:</p> <ul> <li>The source code of the <em>SketchLink</em> server, web application, and IntelliJ plugin.</li> <li>A demo video.</li> <li>Recordings of the user study sessions (audio removed due to confidentiality).</li> <li>The questionnaire and task list used for the plugin study sessions.</li> </ul>
Tomographic data for testing, demonstrating, and developing methods of removing ring artifacts
<p>These tomographic data were used for demonstrating our methods of eliminating ring artifacts published in Optics Express, <em>Nghia T. Vo, Robert C. Atwood, and Michael Drakopoulos, "Superior techniques for eliminating ring artifacts in X-ray micro-tomography," <strong>26</strong>, 28396-28412 (2018)</em><em>. </em>In sinogram, the artifacts appear as straight lines or stripe artifacts. The data have many types of stripe artifacts: full stripes, partial stripes, unresponsive stripes, fluctuating stripes, and blurry stripes. They are very useful for testing and developing methods of removing ring artifacts.</p> <p>Documentation: <a href="https://sarepy.readthedocs.io/">https://sarepy.readthedocs.io/</a></p> <p>Python implementations of these methods:</p> <p><a href="https://github.com/nghia-vo/sarepy">https://github.com/nghia-vo/sarepy</a></p> <p>In Tomopy:</p> <p><a href="https://tomopy.readthedocs.io/en/latest/api/tomopy.prep.stripe.html">https://tomopy.readthedocs.io/en/latest/api/tomopy.prep.stripe.html</a></p> <p>In Savu:</p> <p><a href="http://github.com/DiamondLightSource/Savu/tree/master/savu/plugins/ring_removal">https://github.com/DiamondLightSource/Savu/tree/master/savu/plugins/ring_removal</a></p> <p>In Algotom:</p> <p><a href="https://github.com/algotom/algotom/blob/master/algotom/prep/removal.py">https://github.com/algotom/algotom/blob/master/algotom/prep/removal.py</a> </p>
Artifact: VISON: An Ontology-Based Approach for Software Visualization Tool Discoverability
<p>VISON an ontology that captures the semantics of software visualizations through concepts and relationships. The artifact has been submitted to VISSOFT'19 to support the results reported on our full paper "VISON: An Ontology-Based Approach for Software Visualization Tool Discoverability".</p>
Artifacts: An Approach for Reviewing Security Related Apects in Agile Requirements Specifications of Web Applications
<p>Abstract—Defects in requirements specifications can have severe consequences during the software development lifecycle. Some of them result in overall project failure due to incorrect or missing quality characteristics. Security is one of those uality characteristics that need to be considered in early phases. There are several concerns that make security difficult to deal with; for instance, (1) when stakeholders discuss general requirements in (review) meetings, they are often not aware that they should also discuss security-related topics, and in the rather rare cases they are aware (2), they typically do not have sufficient security expertise. This picture is even more challenging in agile development contexts, where lightweight documentation are typically involved. To address these issues, we designed an approach that considers user stories and security specifications as input and relates those user stories to security properties via Natural Language Processing (NLP) techniques. Based on the related security properties, our approach then identifies high-level security requirements from the Open Web Application Security Project (OWASP) to be verified afterwards. In a last step, the verification of the generated security requirements is then conducted via a focused reading technique. We finally validate our approach via a controlled experiment comparing the effectiveness and efficiency of novice inspectors (we used two different groups of students) verifying security aspects in agile requirements using our generated reading techniques against using the complete list of OWASP high level security requirements and a the same list of defect types embedded in our technique. The (statistically significant) results indicate that using the reading technique has a positive impact (with large effect size) on the performance of inspectors in terms of effectiveness and efficiency. </p> <p>This repository also contains:</p> <p>Artifacts used and results of the experimental study of the paper entitled "An Approach for Reviewing Security Related Apects in Agile Requirements Specifications of Web Applications".</p>
Data and Analysis Artifacts for Service-Based Evolvability Patterns (Experiment and Metrics)
<p>Two functionally equivalent service-based web-shop systems (one version with selected service-based patterns, one without) were analyzed with a controlled experiment as well as with structural maintainability metrics. This repo contains all analysis artifacts.</p>
Comparing the Use of Research Resource Identifiers and Natural Language Processing for Citation of Databases, Software and Other Digital Artifacts
<p><strong>The Research Resource Identifier was introduced in biomedicine in 2014 to more precisely identify the reagents and tools used in published biomedical research and to track use of tools across the breadth of the biomedical literature. The current RRID specification covers key biological and digital resources. Authors are instructed to include an RRID after the first mention of any resource used. RRIDs are designed to be easy to find using a full text search search engine. </strong></p> <p><strong>The published data sets were used in our comparative study where comparing the output of our RRID curation workflow with the outputs of automated text mining systems that have been used to identify mentions of resources in the text of publications. All files in tab-separated format (tsv). </strong></p> <p><strong>Scibot.tsv: Records of the RRID curation workflow using SciBot. </strong></p> <p>Each record shows that a resource RRID was identified in paper PMID with curator tags (Tag1, Tag2, both optional)</p> <p><strong> </strong>PMID: Pubmed ID</p> <p> RRID: Research Resource Identifier</p> <p> Tag1: Curator tags (optional)</p> <p> Tag2: Additional curator tags (optional)</p> <p><strong>rdwsorted.tsv: Records of the output from RDW, a text mining software. </strong></p> <p>RDW identifies mentions of research resources in papers. Each record shows that a resource RRID was identified in paper PMID.</p> <p><strong> </strong>PMID: Pubmed ID</p> <p> RRID: Research Resource Identifier</p> <p><strong>rridbyrdw05282019.tsv: Records of the output of the RRID-by-RDW in RDW. </strong></p> <p>RRID-by-RDW is a component in RDW that identifies mentions of research resources in papers by matching patterns of RRID specifications. Each record shows that a resource RRID was identified in paper PMID.</p> <p><strong> </strong>PMID: Pubmed ID</p> <p> RRID: Research Resource Identifier</p> <p> Context: Snippet where the RRID was found</p> <p><strong>resource_metadata20190418.tsv: Metadata of RRIDs</strong></p> <p>This file contains metadata of resources and their RRIDs. See file header for column definitions.</p> <p><strong>RRIDCUR-definitions.tsv: Definitions of curator tags used in Scibot.tsv.</strong></p> <p><strong> </strong>tag: Tag name</p> <p> definition: Definition of the tag</p>
Figure 1. A in First report of Rhantus validus Sharp (Coleoptera: Dytiscidae) as necrophage and generator of postmortem artifacts in a human corpse found in an artificial freshwater pond from the Región de La Araucanía, Chile
Figure 1. A floating corpse of 47 year-old man found in Peñehue, Región de La AraucanÍa, Chile.
The Effects of Computational Resources on Flaky Tests (Artifact)
<p>This artifact contains resources for reproducing and extending the work "The Effects of Computational Resources on Flaky Tests"</p><p>Contents:</p><ul><li> Analysis and Processed Test Results.tgz: An archive that contains information about the projects analyzed, summarized test results per-throttling configuration per-run, and a Jupyter notebook that detects RAFT (generating all tables and figures in the article). A README in this archive provides further guidance on its contents</li><li>js-results.tar, java-results.tar, python-results.tar: The raw results produced by the test runner when executing each JavaScript, Java and Python project 300 times in each of the throttling configurations.</li></ul><p>See also:</p><p>We have published docker containers that include each project that we studied, along with all of the dependenices for running the tests. These containers can be used to reproduce our results, or to extend our work by running additional tests. The containers are available at <a href="https://hub.docker.com/r/jonbell/raft/tags">https://hub.docker.com/r/jonbell/raft/tags</a></p>
Artifact for "Verifying the Option Type with Rely-Guarantee Reasoning"
<p>This repository contains the dataset and scripts to reproduce Table 1 and Table 2 in the paper "Verifying the Option Type with Rely-Guarantee Reasoning".</p> <h2>Requirements</h2> <p>Please see <code>REQUIREMENTS.md</code> for the same information, but listed separately from this README file.</p> <p>Our scripts are designed for a Unix environment (Linux, macOS, WSL, etc.). They will not work under a Windows command shell.</p> <p>Our scripts require the following tools:</p> <ul> <li> <p><a href="https://www.python.org/downloads/">Python 3</a>, version 3.9.6 or later.</p> </li> <li> <p>GNU <code>grep</code>. For macOS, install it as <code>ggrep</code> via the command <code>brew install grep</code>.</p> <ul> <li>If not already installed, <code>brew</code> can be installed via the instructions<a href="https://docs.brew.sh/Installation">here</a></li> </ul> </li> </ul> <h2>Subject programs</h2> <p>File <code>dataset.txt</code> lists the subject programs.</p> <p>The subject programs are stored under the following directories:</p> <ul> <li><code>optional-paper-base-repos</code>: all the subject programs with their build files modified to run the Optional Checker.</li> <li><code>optional-paper-annotated-repos</code>: all the subject programs, with<code>@SuppressWarnings</code> for each true positive and false positive issued by the Optional Checker (scripts count these). It also contains the Optional Checker type qualifiers that we wrote.</li> <li><code>optional-paper-intellij-repos</code>: all the subject programs with <code>@SuppressWarnings</code> for each IntelliJ warning (so they can be programmatically counted).</li> <li><code>optional-paper-errorprone-repos</code>: all the subject programs with <code>@SuppressWarnings</code> for each Error Prone warning.</li> <li><code>optional-paper-spotbugs-repos</code>: all the subject programs with <code>@SuppressWarnings</code> for each SpotBugs warning.</li> </ul> <h2>Scripts</h2> <p>Looking to reproduce <em>all</em> the data in our tables? See <a href="reproduce-data"><code>reproduce-data</code></a>.</p> <p>This repository contains the following scripts:</p> <ul> <li><a href="reproduce-data"><code>reproduce-data</code></a>: this script reproduces all the data for our tables.</li> <li><a href="compute-precision-recall-annotations"><code>compute-precision-recall-annotations</code></a>: this script generates Table 1: it computes the values for precision, recall, and the number of human-written, machine-checked annotations used by each tool.</li> <li><a href="count-style-violations"><code>count-style-violations</code></a>: this script generates Table 2: it reports the number of style violations detected by each tool.</li> <li><a href="mygrep.py"><code>mygrep.py</code></a>: this is a Python utility used by other scripts as a thin wrapper around <code>grep</code>. You need not use it directly.</li> </ul> <p>All these scripts may be executed from the root of this directory. For example, to generate Table 1:</p> <pre><code>% ./compute-precision-recall-annotations </code></pre> <h2>Resulting Data</h2> <p>Each script produces the <em>rows</em> of the dataset, excluding the column titles. Below is a brief description of each output <code>.tex</code> file:</p> <ul> <li><code>eval-statistics.tex</code>: generated by the <code>compute-precision-recall-annotations</code> script, maps to Table 1 in our paper. The columns of the data are, in order from left-to-right: <ul> <li>Tool name</li> <li>Number of true positives detected by the tool</li> <li>Number of false positives detected by the tool</li> <li>Precision</li> <li>Recall</li> <li>Total number of machine-verified annotations written as a specification across all subject programs.</li> </ul> </li> <li><code>style-violations.tex</code>: generated by the <code>count-style-violations</code>script, maps to Table 2 in our paper. The columns are the data are, in order from left-to-right: <ul> <li>Tool name</li> <li>Number of violations of style rule 1</li> <li>Number of violations of style rule 3</li> <li>Number of violations of style rule 4</li> <li>Number of violations of style rule 5</li> <li>Number of violations of style rule 6.a</li> <li>Number of violations of style rule 6.b</li> <li>Number of violations of style rule 6.c</li> <li>Number of violations of style rule 7</li> </ul> </li> </ul> <h2>Implementation</h2> <p>The implementation of the Optional Checker appears in the <code>implementation</code> directory. This folder contains the following subdirectories:</p> <ul> <li><code>optional</code>: the source code for the Optional Checker's verification logic for the Optional type system. <ul> <li><code>optional/qualifiers</code>: the definitions for each type qualifier from the Optional type system that may be used with the Optional Checker.</li> </ul> </li> <li><code>nonempty</code>: the source code for the Optional Checker's verification logic for the Non-Empty type system. <ul> <li><code>nonempty/qualifiers</code>: the definitions for each type qualifier from the Non-Empty type system that may be used with the Optional Checker.</li> </ul> </li> </ul>
Artifact of the paper: Scheduling with lightweight predictions in power-constrained HPC platforms
<p>Please refer to the <a href="https://zenodo.org/records/13961003/files/artifact-overview.pdf?download=1&preview=1">artifact-overview.pdf</a> file in this dataset for instructions to reproduce the experiments we have conducted for this article, or for more context about the article.</p>
Artifacts for "Living on a Diet: A Brief Study of the Daily Allowances of Spanish Public Workers"
<div> <div>Academic researchers from Spain are entitled to financial compensation to cover accommodation and meals when attending conferences.</div> <div>The amount of this compensation, known as <em>per diem</em> or daily allowance, varies with the destination country and is defined in an official table set by the government in 2002.</div> <div>This study examines the adequacy of these allowances by comparing them to current accommodation and meal costs, defining a score to find countries where researchers can attend conferences without incurring financial loss.</div> <div>Our results show that only 55 countries offer neutral or positive results, highlighting the need to update the official table to suit current cost of living conditions.</div> </div>
ACSAC_ML_SCA_EVA Artifacts
<p>The artifacts for ACSAC 2024 paper <em><span><span>R+R: Demystifying ML-Assisted Side-Channel Analysis Framework: A Case of Image Reconstruction</span></span></em></p>
Artifacts for the FDL21 Paper: In-Vivo Stack Overflow Detection and Stack Size Estimation for Low-End Multithreaded Operating Systems using Virtual Prototypes
<p>Artifacts for the evaluation of the paper <em>In-Vivo Stack Overflow Detection and Stack Size Estimation for Low-End Multithreaded Operating Systems using Virtual Prototypes</em> which will be published as part of <a href="http://www.fdl-conference.org">FDL21</a>. The artifacts provided here use pre-compiled binaries and pre-generated stack usage databases. Based on these provided files, the stack size estimation and performance evaluation performed in the paper can be replicated. Various README.md files, which provide more information on individual artifacts, are also included.</p> <p>The software used in conjunction with these artifacts is also freely available on GitHub:</p> <ul> <li>https://github.com/agra-uni-bremen/fdl21-stackuse-vp</li> <li>https://github.com/agra-uni-bremen/stack-usage-db</li> </ul>
Set of photos (123) of surface artifacts and cranium bones in the Iroungou burial cave, Mouila area, Gabon
<p>Photographs (annotated) of all 182 artifacts (iron currency knives, hoes, iron and copper bracelets, rings, kindu, gong) and 51 cranium bones visible on the ground during the initial visit of the Iroungou burial cave, Mouila area, Gabon, on september 23, 2018.</p>
SLR Artifacts - CONTINUOUS INTEGRATION QUALITY IMPACTS
<p>SLR Artifacts - CONTINUOUS INTEGRATION QUALITY IMPACTS</p> <ul> <li>ODS file SLR - Studies.ods containing the selected papers in each research step.</li> <li>ODS file SLR - Claims.ods containing the extracted claims in the papers, the coding process, and themes.</li> <li>SQL file to restore a relational database with the relations: studies (included ones), claims, codes, themes, and authors.</li> <li>CI SLR - Quality Assessment.pdf - containing the quality assessment checklist.</li> <li>scripts_search.zip - containing the scripts used to perform the search of papers.</li> </ul> <p> </p> <p> </p>
STonKGs INDRA Artifacts
<p>Embeddings of the INDRA database and random walks generated by the best Node2Vec models</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.