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677 results for “Replication package”
Replication package for: Dust and Death: Evidence from the West African Harmattan
<p>Data and code to replicate all the results in the article Adhvaryu, Achyuta; Bharadwaj, Prashant; Fenske, James; Nyshadham, Anant ; and Stanley, Richard "Dust and Death: Evidence from the West African Harmattan," Economic Journal.</p>
Replication package of: 'Perceived Fairness and Consequences of Affirmative Action Policies'
<p>Replication package for: Schildberg-Hörisch, H., Schwarz, M., Trieu, C., and Willrodt, J. (2023). “Perceived Fairness and Consequences of Affirmative Action Policies”, Economic Journal, conditionally accepted.</p>
Replication package for: Real Exchange Rates and the Earnings of Immigrants
<p>The package contains the code necessary to reproduce the tables and figures in Dustmann, Ku, and Surovtseva (forthcoming): "Real Exchange Rates and the Earnings of Immigrants". The Economic Journal. </p>
Replication Package of Submission #1725 for ICSE 2024
<p>Here is the replication package for the paper "Unraveling Software Decoupling: Contexts, Practices, and Patterns" of Submission 1725.</p>
Replication Package for "The Double-edged Sword of Banning Generative AI on Online Question-and-Answer Communities: Evidence from Stack Exchange"
<p>This is a replication package for "The Double-edged Sword of Banning Generative AI on Online Question-and-Answer Communities: Evidence from Stack Exchange".</p>
Replication package for "WIA-SZZ: Work Item Aware SZZ"
<p>This dataset includes scripts and data files used to generate all analysis and results from the paper. A <strong>README.md</strong> file is included for details on using the scripts.</p> <p>For replication purposes, a copy of the cloned repositories from Rosa et al. (dowloaded as of to Dec. 2022) is provided through 7 Zenodo links:</p> <p>1. <a href="https://zenodo.org/record/8285106">https://zenodo.org/record/8285106</a> (doi: 10.5281/zenodo.8285106)</p> <p>2. <a href="https://zenodo.org/record/8285119">https://zenodo.org/record/8285119</a> (doi: 10.5281/zenodo.8285119)</p> <p>3. <a href="https://zenodo.org/record/8285121">https://zenodo.org/record/8285121</a> (doi: 10.5281/zenodo.8285121)</p> <p>4. <a href="https://zenodo.org/record/8285125">https://zenodo.org/record/8285125</a> (doi: 10.5281/zenodo.8285125)</p> <p>5. <a href="https://zenodo.org/record/8285127">https://zenodo.org/record/8285127</a> (doi: 10.5281/zenodo.8285127)</p> <p>6. <a href="https://zenodo.org/record/8285138">https://zenodo.org/record/8285138</a> (doi: 10.5281/zenodo.8285138)</p> <p>7. <a href="https://zenodo.org/record/8285140">https://zenodo.org/record/8285140</a> (doi: 10.5281/zenodo.8285140)</p>
Replication Package - From Research to Practice: A Survey of XAI Process Frameworks
<p>Replication package for the ICSE NIER Submission "From Research to Practice: A Survey of XAI Process Frameworks." Provides details about the methods and data used in our analysis. For more information, please take a look at the README.</p>
Replication package for: "Information Aggregation Under Ambiguity: Theory and Experimental Evidence"
<p>The package contains the data and code to replicate all figures and tables in Galanis, Ioannou, and Kotronis (forthcoming), "Information Aggregation Under Ambiguity: Theory and Experimental Evidence", Review of Economic Studies.</p>
Data and code to replicate: Diet analysis using generalized linear models derived from foraging processes using R package mvtweedie
Open the record for dataset details and reuse information.
Replicate analysis from: tinyVAST: R package with an expressive interface to specify lagged and simultaneous effects in multivariate spatio-temporal models
Open the record for dataset details and reuse information.
Does Unit-Tested Code Crash? A Case Study of Eclipse: Replication Package
<p><strong>Does Unit-Tested Code Crash? A Case Study of Eclipse: Replication Package</strong></p> <p>This is a replication package associated with the paper titled “Does Unit-Tested Code Crash? A Case Study of Eclipse”. Below is a description of the package’s contents.</p> <p><strong>Data</strong></p> <p>Data files associated with the paper are provided in the <code>data</code> directory.</p> <p><strong>Text file <code>tested-crashed.txt</code></strong></p> <p>Data specifying whether methods were tested and whether they crashed (according to the criteria adopted in the study). Extracted from <code>matches.xlsx</code>. The data are used as input for Fisher’s test (RQ1).</p> <p><strong>Spreadsheet <code>matches.xlsx</code></strong></p> <p>Test coverage data and calculations associated with failed methods, class coverage, and matching method coverage results are provided in an Excel spreadsheet. Below is the description of the spreadsheet’s contents.</p> <p>Worksheet <em>Test Coverage</em></p> <p>Contains the data regarding the JaCoCo test code coverage analysis.</p> <ul> <li>Class: The name of the class in which a method appears in JVM internal form notation</li> <li>Method: The method’s name</li> <li>Parameters: The method’s arguments in JVM parameter descriptor format; required to handle Java’s {} polymporphism</li> <li>Class Has Unit Test: Whether the corresponding class has associated unit test code</li> <li>Class Unit-Test Line Density: The ratio of lines in class’s test code over those in the class’s implementation code</li> <li>Covered Instructions / Branches / Lines: As reported by JaCoCo</li> <li>Total Instructions / Branches / Lines: As reported by JaCoCo</li> <li>Covered Instructions / Branches / Lines ratio: The ratio between the two preceding values; 1 for methods without any branches</li> <li>Top-1 / Top-6 / Top-10 : In how many stack traces the method appears within; the top-10 / top-6 / the very first stack frame(s)</li> <li>Tested: TRUE if the method is considered tested by having a test code coverage above the median (0.966) and an associated test class</li> <li>Crashed: TRUE if the method has crashed as evidenced by its appearance on the topmost stack frame</li> <li>Stack trace file names: in which the method appeared</li> </ul> <p>Worksheet <em>Test Existence</em></p> <p>Contains the data of the analysis regarding the existence of test code.</p> <ul> <li>Class: Class containing implementation code</li> <li>TestClassNames: Classes that contain tests for the above</li> <li>Number of relevant tests</li> <li>Lines in class test code</li> <li>Lines of class</li> <li>Class Unit-Test Line Density: The ratio between the two above</li> </ul> <p>Worksheet <em>Metrics</em></p> <p>Contains the derivation of metrics reported in the paper. In the cases of tables these are formatted in LaTeX for direct incorporation into the text.</p> <p><strong>Spreadsheet <code>jacoco.xlsx</code></strong></p> <p>Complete test coverage data obtained from JaCoCo are provided in an Excel spreadsheet. Below is the description of the spreadsheet’s contents.</p> <p>Worksheet <em>Data</em></p> <p>Contains the following method code coverage fields as reported by JaCoCo, as well as the calculated percentages.</p> <ul> <li>Class</li> <li>Method</li> <li>Parameters</li> <li>Covered Instructions</li> <li>Total Instructions</li> <li>% Covered Instructions</li> <li>Covered Branches</li> <li>Total Branches</li> <li>% Covered Branches</li> <li>Covered Lines</li> <li>Total Lines</li> <li>% Covered Lines</li> </ul> <p>Worksheet <em>Metrics</em></p> <p>Contains the derivation of numbers reported in the preliminary quantitative analysis and Figure 2.</p> <p>Compressed tar archive <code>eclipse-src.tar.gz</code></p> <p>Contains the Eclipse source code used for running the Eclipse tests with JaCoCo code coverage analysis. It was obtained from the Eclipse source code repositories as follows.</p> <ul> <li>Clone the Eclipse aggreagator repository into a directory named z by running: <code>git clone -b master --recursive git://git.eclipse.org/gitroot/platform/eclipse.platform.releng.aggregator.git z</code></li> <li>In the <code>z</code> directory, checking out the used release by running <code>cd z && git submodule foreach git checkout M20160212-1500</code></li> <li>Checking out the release for the main repository by running: <code>git checkout M20160212-1500</code></li> <li>Applying the patch <code>eclipse-src.diff</code></li> </ul> <p><strong>Patch file <code>eclipse-src.diff</code></strong></p> <p>See above.</p> <p><strong>Zip file <code>incidents.zip</code></strong></p> <p>Contains the 126,026 incidents (crash report stack traces and meta-data) associated with <em>EclipseProduct</em> <code>org.eclipse.epp.package.java.product</code> and <em>BuildID</em> <code>4.5.2.M20160212-1500</code>. This is a subset from the two million incidents available as the <a href="http://software-data.org/datasets/aeri-stacktraces/downloads/incidents_full.tar.bz2">AERI stack traces data set</a>.</p> <p>The subset of incidents was extracted from the full AERI data set with the following command.</p> <pre><code class="language-bash">for f in *; do grep -q org.eclipse.epp.package.java.product $f && grep -q 4.5.2.M20160212-1500 $f && mv $f selected-files/ done</code></pre> <p><br> <strong>Compressed file <code>jacoco.xml.gz</code></strong></p> <p>Contains the results of the JaCoCo code coverage analysis over the Eclipse testing.</p> <p><strong>Code</strong></p> <p>The following scripts are provided in the <code>src</code> directory</p> <ul> <li><code>extract.py</code>: script for extracting crash (incidents) and coverage (JaCoCo) data</li> <li><code>unit-tested-classes.py</code>: script for finding the classes with associated unit test code</li> <li><code>merge.py</code>: script for matching crash (incidents) with coverage (JaCoCo) data</li> <li><code>fisher.r</code>: R script for running Fisher’s test</li> </ul>
Replication Package of a Paper
<p>Replication Package of Order in Chaos: Prioritizing Mobile App Reviews using Consensus Algorithms paper</p>
Replication Package for "Did You Remember To Test Your Tokens?"
<p>Supplementary data to "Did You Remember To Test Your Tokens?", accepted for publication at MSR 2020. We include several artifacts that were generated during the analysis of JUnit tests for token authentication, as well as the original dataset.</p>
Replication package for "Mutation testing of smart contracts at scale"
<p>Replication package for TAP2020 paper "Mutation testing of smart contracts at scale"</p> <p>Abstract: It is crucial that smart contracts are tested thoroughly due to their immutable nature. Even small bugs in smart contracts can lead to huge monetary losses. However, testing is not enough; it is also important to ensure the quality and completeness of the tests. There are already several approaches that tackle this challenge with mutation testing, but their effectiveness is questionable since they only considered small contract samples. Hence, we evaluate the quality of smart contract mutation testing at scale. We choose the most promising of the existing (smart contract specific) mutation operators, analyse their effectiveness in terms of killability and highlight severe vulnerabilities that can be injected with the mutations. Moreover, we improve the existing mutation methods by introducing a novel killing condition that is able to detect a deviation in the gas consumption, i.e., in the monetary value that is required to perform transactions.</p>
Replication Package: A Study on the Accuracy of OCR Engines for Source Code Transcription from Programming Screencasts
<p>The replication package of the paper "A Study on the Accuracy of OCR Engines for Source Code Transcription from Programming Screencasts" including the dataset, results and tools</p>
Replication Package: UI Screens Identification and Extraction from Mobile Programming Screencasts
<p>The replication package of the paper "UI Screens Identification and Extraction from Mobile Programming Screencasts" including the dataset, results, and code.</p>
Replication package for class comment analysis
<p>This project contains the necessary material to replicate the project. It also contains supplementary data to give better insights into the results.</p>
z-sh/fse20: Replication package for paper#133 - Gender Bias in Code Review
<p>The replication package for paper#133 - Gender Bias in Code Review written by Huang et. al.</p>
Test record for REStud replication packages
<p>Test record for REStud replication packages</p>
Replication package for the paper accepted at Springer's EMSE Journal: Publish or Perish - But do not Forget your Software Artifacts
<p>This is the replication package for the paper "Publish or Perish - But do not Forget your Software Artifacts", accepted at Springer's EMSE Journal in June 2020.</p> <p>It contains:</p> <ul> <li>A ReadMe file with instructions on how to use the replication scripts</li> <li>The complete, labeled dataset of 792 ICSE papers as CSV</li> <li>All the python scripts that we used for data-acquisition and -preparation</li> <li>The jupyter notebook that we used for the evaluation. This also contains some additional analyses which are not included in the paper.</li> <li>An html export of the notebook for quick reference</li> <li>A folder containing all of the diagrams in pdf form</li> </ul>
ScienceDex guides
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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.