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102 results for “Software Testing”
Dataset for the paper: What Do Contribution Guidelines Say About Software Testing?
<p>Dataset for the paper: What Do Contribution Guidelines Say About Software Testing? This dataset contains the raw data for the guidelines of 200 Python and JavaScript open-source software projects.</p>
TCTracer: Establishing Test-to-Code Traceability Links Using Dynamic and Static Techniques - Evaluation Data - Empirical Software Engineering 2021
<p>This repository provides the data artefacts for the experiments conducted using our tool TCTracer for the journal paper "TCTracer: Establishing Test-to-Code Traceability links Using Dynamic and Static Techniques" as submitted to the Empirical Software Engineering journal in 2021.</p>
Results: Guided Metamorphic Testing for Software Engineering ML
<p>This package holds results from "Searching for Quality: Guided Metamorphic Testing for Software Engineering ML" as submitted to GECCO 2023. </p> <p>The results are directly gathered from running the (separately) provided replication package. </p> <p>Note: Due to a slight oversight, the postfixes "min" and "max" are switched, i.E. the F1-min as named in the file actually maximizes.<br> This is corrected later in the evaluation. </p>
SV-Benchmarks: Benchmark Set for Software Verification and Testing (SV-COMP 2023 and Test-Comp 2023)
<p>Full benchmark set of the</p> <ul> <li>12th Intl. Competition on Software Verification (SV-COMP 2023) and the</li> <li>5th Intl. Competition on Software Testing (Test-Comp 2023).</li> </ul> <p>Licenses are included with the source code.</p>
Results of the 5th Intl. Competition on Software Testing (Test-Comp 2023)
<p><strong>Test-Comp 2023</strong></p> <p><strong>Competition Results</strong></p> <p>This file describes the contents of an archive of the 5th Competition on Software Testing (Test-Comp 2023). <a href="https://test-comp.sosy-lab.org/2023/">https://test-comp.sosy-lab.org/2023/</a></p> <p>The competition was organized by Dirk Beyer, LMU Munich, Germany. More information is available in the following article: Dirk Beyer. <em>Software Testing: 5th Comparative Evaluation: Test-Comp 2023.</em> In Proceedings of the 26th International Conference on Fundamental Approaches to Software Engineering (FASE 2023, Paris, April 22 - 27), 2023. Springer.</p> <p>Copyright (C) Dirk Beyer <a href="https://www.sosy-lab.org/people/beyer/">https://www.sosy-lab.org/people/beyer/</a></p> <p>SPDX-License-Identifier: CC-BY-4.0 <a href="https://spdx.org/licenses/CC-BY-4.0.html">https://spdx.org/licenses/CC-BY-4.0.html</a></p> <p>To browse the competition results with a web browser, there are two options:</p> <ul> <li>start a local web server using php -S localhost:8000 in order to view the data in this archive, or</li> <li>browse <a href="https://test-comp.sosy-lab.org/2023/results/">https://test-comp.sosy-lab.org/2023/results/</a> in order to view the data on the Test-Comp web page.</li> </ul> <p><strong>Contents</strong></p> <ul> <li><code>index.html</code>: directs to the overview web page</li> <li><code>LICENSE-results.txt</code>: specifies the license</li> <li><code>README-results.txt</code>: this file</li> <li><code>results-validated/</code>: results of validation runs</li> <li><code>results-verified/</code>: results of test-generation runs and aggregated results</li> </ul> <p>The folder <code>results-validated/</code> contains the results from validation runs:</p> <ul> <li><code>*.results.txt</code>: TXT results from BenchExec</li> <li><code>*.xml.bz2</code>: XML results from BenchExec</li> <li><code>*.logfiles.zip</code>: output from tools</li> <li><code>*.json.gz</code>: mapping from files names to SHA 256 hashes for the file content</li> </ul> <p>The folder <code>results-verified/</code> contains the results from test-generation runs and aggregated results:</p> <ul> <li> <p><code>index.html</code>: overview web page with rankings and score table</p> </li> <li> <p><code>design.css</code>: HTML style definitions</p> </li> <li> <p><code>*.results.txt</code>: TXT results from BenchExec</p> </li> <li> <p><code>*.xml.bz2</code>: XML results from BenchExec</p> </li> <li> <p><code>*.fixed.xml.bz2</code>: XML results from BenchExec, status adjusted according to the validation results</p> </li> <li> <p><code>*.logfiles.zip</code>: output from tools</p> </li> <li> <p><code>*.json.gz</code>: mapping from files names to SHA 256 hashes for the file content</p> </li> <li> <p><code>*.xml.bz2.table.html</code>: HTML views on the detailed results data as generated by BenchExec’s table generator</p> </li> <li> <p><code><tester>*.table.html</code>: HTML views of the full benchmark set (all categories) for each tester</p> </li> <li> <p><code>META_*.table.html</code>: HTML views of the benchmark set for each meta category for each tester, and over all testers</p> </li> <li> <p><code><category>*.table.html</code>: HTML views of the benchmark set for each category over all testers</p> </li> <li> <p><code>*.xml</code>: XML table definitions for the above tables</p> </li> <li> <p><code>results-per-tool.php</code>: List of results for each tool for review process in pre-run phase</p> </li> <li> <p><code><tester>.list.html</code>: List of results for a tool in HTML format with links</p> </li> <li> <p><code>quantilePlot-*</code>: score-based quantile plots as visualization of the results</p> </li> <li> <p><code>quantilePlotShow.gp</code>: example Gnuplot script to generate a plot</p> </li> <li> <p><code>score*</code>: accumulated score results in various formats</p> </li> </ul> <p>The hashes of the file names (in the files <code>*.json.gz</code>) are useful for</p> <ul> <li>validating the exact contents of a file and</li> <li>accessing the files from the witness store.</li> </ul> <p><strong>Other Archives</strong></p> <p>Overview of archives from Test-Comp 2023 that are available at Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.7701126">https://doi.org/10.5281/zenodo.7701126</a> Test Suites from Test-Comp 2023 Test-Generation Tools. Store of coverage witnesses (containing the generated test suites)</li> <li><a href="https://doi.org/10.5281/zenodo.7701118">https://doi.org/10.5281/zenodo.7701118</a> Test-Suite Generators from Test-Comp 2023. Executable tools that were evaluated in the competition</li> <li><a href="https://doi.org/10.5281/zenodo.7701122">https://doi.org/10.5281/zenodo.7701122</a> Results of the 5th Intl. Competition on Software Testing (Test-Comp 2023). Results (XML result files, log files, file mappings, HTML tables)</li> <li><a href="https://doi.org/10.5281/zenodo.7627783">https://doi.org/10.5281/zenodo.7627783</a> SV-Benchmarks: Benchmark Set of SV-COMP 2023 and Test-Comp 2023. Verification tasks, version testcomp23</li> <li><a href="https://doi.org/10.5281/zenodo.7612021">https://doi.org/10.5281/zenodo.7612021</a> BenchExec, version 3.16. Benchmarking framework</li> <li><a href="https://doi.org/10.5281/zenodo.7635975">https://doi.org/10.5281/zenodo.7635975</a> CoVeriTeam, version 1.0. Remote execution and continuous integration of testers</li> </ul> <p>All benchmarks were executed for Test-Comp 2023 <a href="https://test-comp.sosy-lab.org/2023/">https://test-comp.sosy-lab.org/2023/</a> by Dirk Beyer, LMU Munich, based on the following components:</p> <ul> <li><a href="https://gitlab.com/sosy-lab/test-comp/archives-2023">https://gitlab.com/sosy-lab/test-comp/archives-2023</a> testcomp23 bd9d84151c52ba7ad549212a590e2b3a18c071bc</li> <li><a href="https://gitlab.com/sosy-lab/benchmarking/sv-benchmarks">https://gitlab.com/sosy-lab/benchmarking/sv-benchmarks</a> testcomp23 f87854c275a177e8dc3673fe6959cd89038652af</li> <li><a href="https://gitlab.com/sosy-lab/test-comp/bench-defs">https://gitlab.com/sosy-lab/test-comp/bench-defs</a> testcomp23 21a5ba27dc84c8e59fefe18369b5723550c96786</li> <li><a href="https://gitlab.com/sosy-lab/software/benchexec">https://gitlab.com/sosy-lab/software/benchexec</a> 3.16 b43e7384112770a41b571399135065daa7f387ab</li> <li><a href="https://gitlab.com/sosy-lab/benchmarking/competition-scripts">https://gitlab.com/sosy-lab/benchmarking/competition-scripts</a> testcomp23 e6f84b5a79626b4295108a0f96ea370edde1f023</li> <li><a href="https://gitlab.com/sosy-lab/test-comp/test-format">https://gitlab.com/sosy-lab/test-comp/test-format</a> testcomp23 e6b0eff82a5132a6e4e4b52f8fbfaa3553af3ebb</li> <li><a href="https://gitlab.com/sosy-lab/software/coveriteam">https://gitlab.com/sosy-lab/software/coveriteam</a> 1.0 78d9f9f9d5fefc4fdd934d1e0f43ddba4ec51711</li> </ul> <p><strong>Contact</strong></p> <p>Feel free to contact me in case of questions: <a href="https://www.sosy-lab.org/people/beyer/">https://www.sosy-lab.org/people/beyer/</a></p>
Um estudo sobre as práticas de testes funcionais de GUI na indústria brasileira de software
<p>Teste de software é uma importante atividade no ciclo de desenvolvimento de software, a qual busca garantir a qualidade dos software criados. Quando um software não supre as necessidades implícitas e explicitas de seus usuários, pode-se dizer que ele carece de qualidade. A falta de qualidade de um software pode gerar vários problemas para o projeto de desenvolvimento de software, como atritos entre fornecedor e clientes/usuários, perdas financeiras, problemas legais por descumprimento de contratos e até risco à vida dos seus usuários em contextos críticos.</p> <p>Nesse sentido, distintos níveis de testes foram desenvolvidos para garantir a qualidade em diferentes aspectos do software. Uma abordagem popular é o teste funcional de interface, que avalia o software através da execução de eventos na tela do software, como o preenchimento de um campo de texto ou o clique de um botão. Os testes funcionais de interface ou GUI (\textit{Graphical User Interface}), podem ser executados tanto de forma manual, com a interação direta do testador no software, quanto automatizada, com a execução do software através de um \textit{script} programado.</p> <p>Nos últimos anos, é possível encontrar na literatura diversas soluções e técnicas propostas para lidar com os testes de GUI. No entanto, as pesquisas não se aprofundam em analisar como os profissionais da indústria vem executando esse tipo de teste, deixando assim uma lacuna na área. Por isso, este estudo propõe investigar como os testadores estão realizando testes de interface em seus projetos. Assim, primeiramente foi realizado um questionário online com 222 profissionais de teste com distintas experiências, cargos e funções. O resultado indicou que ainda há muitos profissionais que realizam testes exclusivamente de forma manual. Além disso, a maioria dos profissionais concordam que as ferramentas utilizadas na automação de testes atendem as necessidades de negócio, embora tenham limitações técnicas. </p> <p>Em seguida, realizamos uma entrevista semiestruturada com 20 profissionais de testes para complementar os resultados obtidos com o questionário. Os resultados indicaram que testadores que realizam apenas testes de GUI manuais não criam testes de GUI automatizados devido ao contexto do projeto em que trabalham, suas preferências profissionais e também por questões educacionais, como dificuldade com programação. Além disso, foram observadas distintas limitações para testes de GUI manuais e automatizados que impactam negativamente as atividades desempenhadas pelos profissionais, como dificuldades relacionadas à cultura da empresa e problemas técnicos relacionados ao software sob teste. Os resultados combinados fornecem uma visão geral dos testes de GUI na indústria de software brasileira.</p>
Data Set: Promoting Open Science in Test-Driven Software Experiments
<p>Data set for reproduction purposes (tabular data is stored using Apache's Parqet format).</p>
Hypermedia-based software architecture enables test-driven development
<p><em>Objectives: </em></p> <p>Using agile software development practices, develop and evaluate a software architecture and implementation for reliable management of bioinformatic data that is stored in the cloud.</p> <p><em>Materials and Methods: </em></p> <p>CORE (Comprehensive Oncology Research Environment) Browser is a new open-source web application for cancer researchers to manage sequencing data organized in a flexible format in Amazon Simple Storage Service (S3) buckets. It has a microservices- and hypermedia-based architecture, which we integrated with Test-Driven Development (TDD), the iterative writing of computable specifications for how software should work prior to development. Optimal testing completeness is a tradeoff between code coverage and software development costs. We hypothesized this architecture would permit developing tests that can be executed repeatedly for all microservices, maximizing code coverage while minimizing effort.</p> <p><em>Results: </em></p> <p>After one-and-a-half years of development, the CORE Browser backend had 121 tests designed for repeated execution and 875 custom tests that were executed 3,031 times, providing 78% code coverage.</p> <p><em>Discussion: </em></p> <p>Hypermedia architecture's repeating pattern, links, permits CORE Browser to implement tests that can be executed repeatedly by every microservice to achieve high code coverage. Code coverage correlates with software reliability. Other benefits of this architecture include permitting access to bucket data from outside the application and separating management of bioinformatic data from analysis.</p> <p><em>Conclusion: </em></p> <p>Architectural choices are important enablers of modern software development practices, such as TDD. Updating software architecture may be a critical next step in agile transformation after an engineering team implements the structural changes on which most such transformations focus.</p> <p><em>Keywords: </em></p> <p>High-throughput nucleotide sequencing, software, data management, cloud computing.</p>
Testing Context-Aware Software Systems in the Automotive Domain: A Multi Vocal Literature Review Protocol and Dataset
<h2>Testing Context-Aware Software Systems in the Automotive Domain: A Multi Vocal Literature Review Protocol and Dataset</h2><p>A Multi-Vocal Literature Review (MVLR) is a form of a systematic review that includes grey literature in addition to peer-review literature (Garousi, Felderer, and Mäntylä 2019). The decision to justify an MVLR is drawn from the results of recent literature reviews, in particular the recent results from (Matalonga et al. 2022) where it is shown that there is little evidence in the white literature on the approaches to testing non-academic CASS Systems.</p><p>Previous academic works (including our Quasi-Systematic Literature Reviews and Rapid Reviews) operate under the following assumptions and observations:</p><ul><li>Assumption 1. CASS are widespread and being deployed for commercial or industrial use.</li><li>Observation 1. The software engineering and software testing communities have had time to adopt (or develop new) techniques to deal with the context and effects of testing software systems.</li><li>Observation 2. Academics have been able to work with software organizations to transfer or study the approaches used to test CASS, yet the published case studies we are aware of describe a partial picture of the overall adoption and approach of the problem.</li></ul><p>In spite of these assumptions and the availability of systematic literature review studies, there is little evidence of how software organizations are testing CASS.</p><h3>Research Goals</h3><h4><strong>Aim: </strong>To uncover evidence on how the automotive industry reports their working with the dynamic testing process regarding CASS.</h4><p>We use the term industry to broaden our scope to include stakeholders with an interest in the quality of CASS like NGOs, standard-setting organizations and regulation-setting organizations who can influence how software must be treated in different domains.</p><p>The following research questions convey the general interest of our enquiries. These are driven by our previous research and expectations on the sources.</p><ul><li><strong>RQ1</strong> Are there sources to support the understanding and indicate directions to deal with the problem of testing CASS?</li><li><strong>RQ2</strong> What are the challenges of using these dynamic testing process solutions?</li><li><strong>RQ3 </strong>How are the dynamic testing processes that deal with the context of CASS described in the sources?</li></ul><h3>Dataset </h3><p>This dataset contains the following artifacts:</p><ol><li><strong>Testing CASS MVLR Protocol.pdf</strong>: protocol containing the methodological details of performing the MVLR</li><li><strong>Sources Identification, Selection and Data Extraction.xlsx</strong>: spreadsheet used to record and control discovered and selected sources</li><li><strong>Extraction_Documents.zip</strong>: compressed file containing all data collection forms filled with data extracted from the</li><li><strong>MVLR_Analysis-Codebook.xlsx</strong>: listing of codes emerging from the collected data</li></ol><p> </p>
Testing of Computer Aided Detection Software for Riverain Medical Group
ClinicalTrials.gov study NCT00906789. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: AUTOEB: A software for systematically evaluating bipartitions in a phylogenetic tree employing an approximately unbiased test
Open the record for dataset details and reuse information.
Hypermedia-based software architecture enables test-driven development
Open the record for dataset details and reuse information.
Test of the haptic knob using a pilot software interface
<p>Additional material related to the paper "<em>A LOW-COST ENDLESS KNOB CONTROLLER WITH PROGRAMMABLE RESISTIVE FORCE FEEDBACK FOR MULTIMEDIA PRODUCTION</em>"</p> <p>This video contains an example of a hapitc knob device used for supporting basic audio editing operations in a pilot software environment developed in Processing. In particular, the five effects shown are amplitude transient detection, time window navigation, volume control, multiple choice selector and variable resistance.</p>
Implementing Traceability Repositories as Graph Databases for Software Quality Improvement: Datasets used to test our methodology that is presented in the paper 10.1109/QRS.2018.00040
<p>The first dataset is the Event Based Traceability for Managing Evolutionary Change (EBT), it is a public dataset provided by CoEST, the original artifacts and trace links are represented in XML and text format. From the EBT dataset, we selected the 41<em> requirements </em>and 25<em> test case </em>artifacts, in addition to the answer set of 51 trace links which relates the <em>requirements </em>with the<em> test case. </em>Artifacts and trace links are prepared in XML format<strong>. </strong>The data set contains XML for each artifact such as RQ.xml, EBTrelations.xml is the answer set file, TradModel.xml which describes the defined model and TradTraceabilityRule.xml that includes the rules applied for trace link types.</p> <p> </p> <p>The second dataset AgileOERP is collected from commercial management tool to customize an open source ERP applying agile methodology. It contains 350<em> user stories (US), </em>1323<em> tasks (TS) </em>and 198<em> developer test (DT) </em>artifacts, in addition to answer set of trace links that manually generated by developers which relates the <em>user story </em>artifact with<em> task (</em>1304) artifact, as such relates the <em>task </em>artifact with<em> developer test </em>artifact (65). Artifacts and trace links are prepared in XML format<strong>. </strong>The data set contains XML for each artifact such as US.xml, ERPrelations.xml is the answer set file, AgileModel.xml which describes the defined model and AgileTraceabilityRule,xml that includes all rules applied for trace links type</p> <p> </p> <p>The original dataset of the last dataset is the Aqualush irrigation system which is used as a case study in “C. Fox, Introduction to Software Engineering Design: Processes, Principles and Patterns with UML2. Addison-Wesley, 2006”. The trace links are generated and provided in “E. Ben Charrada, D. Caspar, C. Jeanneret, and M. Glinz, towards a benchmark for traceability, in Joint EVOL and IWPSE 2011, pp. 21-30”, in HTML format. For our work, we selected the <em>software requirements specification (</em>396 SRS), <em>user level requirements (</em>48 ULR), <em>use case (</em>74 UC), <em>detailed design (85 DD) </em>and <em>software architecture(15 SArch) </em>artifacts in addition to the answer set of trace links that relate the SRS with other artifacts(4038) and thus relates the DD artifact with other artifacts (1719) . Artifacts and trace links are prepared in XML<strong>. </strong>The data set contains XML for each artifact such as SRS.xml, AqualushRelations.xml is the answer set file, TradModel.xml which describes the defined model and TradTraceabilityRule.xml that includes the rules applied for trace link types.</p>
Complementary materials for: Looking For Novelty in Search-based Software Product Line Testing (TSE)
<p>In this repository, we provide complementary materials for the following paper: </p> <pre>Y. Xiang, H. Huang, M. Li, S. Li and X. Yang, "Looking For Novelty in Search-based Software Product Line Testing" in <em>IEEE Transactions on Software Engineering</em>, vol. , no. 01, pp. 1-1, 5555. doi: 10.1109/TSE.2021.3057853 url: https://doi.ieeecomputersociety.org/10.1109/TSE.2021.3057853</pre> <p>1. Correlation analysis results (Pearson'r and p-value) are tabulated in <a href="https://www.zenodo.org/api/files/f6451296-91dc-4c9c-89fc-28ebf315be10/CorrelationAnalysisResults.xlsx?versionId=2f4ec2ab-3e48-420d-9819-b5e60ea43c06">CorrelationAnalysisResults.xlsx</a>; </p> <p>2. MATLAB scripts and raw data, which were used to perform correlation analyses, are given in <a href="https://zenodo.org/api/files/f6451296-91dc-4c9c-89fc-28ebf315be10/RawDataForCorrelationAnalysis.rar?versionId=5a168e2e-df32-4773-b8f3-4bf49de8d01d">RawDataForCorrelationAnalysis.rar</a>. </p> <p>---------------------------------------------------------------------------------------------------------------------------------------</p> <p>We suggest reproducing the correlation analysis, and other experiments described in the paper, using the codes provided at Github: <a href="https://github.com/gzhuxiangyi/TSE_NS">https://github.com/gzhuxiangyi/TSE_NS </a></p> <p> </p>
Software Product Line Testing: A Systematic Literature Review Datasheets
<p>Software Product Line Testing: A Systematic Literature Review Dataset</p>
Data extraction form - A Systematic Literature Review on Prioritizing Software Test Cases using Markov Chains
<p>A data extraction form was created to gather all relevant data from the identified studies and manage the selection process in this systematic literature review. Some of the main information presented in this form was followed by a protocol, identifier (id) for each returned study, bibliographic reference, and answers to research questions. This catalog helps us in the data extraction and synthesis procedures and may be used by potentially interested, for example, for updating or replication. </p>
Results of the 4th Intl. Competition on Software Testing (Test-Comp 2022)
<p>Test-Comp 2022</p> <p>Competition Results</p> <p>This file describes the contents of an archive of the 4th Competition on Software Testing (Test-Comp 2022).<br> <a href="https://test-comp.sosy-lab.org/2022/">https://test-comp.sosy-lab.org/2022/</a></p> <p>The competition was run by Dirk Beyer, LMU Munich, Germany.<br> More information is available in the following article:<br> Dirk Beyer. <em>Advances in Automatic Software Testing: Test-Comp 2022.</em> In Proceedings of the 25th International Conference on Fundamental Approaches to Software Engineering (FASE 2022, Munich, April 2 - 7), 2021. Springer.</p> <p>Copyright (C) Dirk Beyer<br> <a href="https://www.sosy-lab.org/people/beyer/">https://www.sosy-lab.org/people/beyer/</a></p> <p>SPDX-License-Identifier: CC-BY-4.0<br> <a href="https://spdx.org/licenses/CC-BY-4.0.html">https://spdx.org/licenses/CC-BY-4.0.html</a></p> <p>To browse the competition results with a web browser, there are two options:</p> <ul> <li>start a local web server using php -S localhost:8000 in order to view the data in this archive, or</li> <li>browse <a href="https://test-comp.sosy-lab.org/2022/results/">https://test-comp.sosy-lab.org/2022/results/</a> in order to view the data on the Test-Comp web page.</li> </ul> <p>Contents</p> <ul> <li><code>index.html</code>: directs to the overview web page</li> <li><code>LICENSE.txt</code>: specifies the license</li> <li><code>README.txt</code>: this file</li> <li><code>results-validated/</code>: results of validation runs</li> <li><code>results-verified/</code>: results of test-generation runs and aggregated results</li> </ul> <p>The folder <code>results-validated/</code> contains the results from validation runs:</p> <ul> <li><code>*.xml.bz2</code>: XML results from BenchExec</li> <li><code>*.logfiles.zip</code>: output from tools</li> <li><code>*.json.gz</code>: mapping from files names to SHA 256 hashes for the file content</li> </ul> <p>The folder <code>results-verified/</code> contains the results from test-generation runs and aggregated results:</p> <ul> <li> <p><code>index.html</code>: overview web page with rankings and score table</p> </li> <li> <p><code>design.css</code>: HTML style definitions</p> </li> <li> <p><code>*.xml.bz2</code>: XML results from BenchExec</p> </li> <li> <p><code>*.merged.xml.bz2</code>: XML results from BenchExec, status adjusted according to the validation results</p> </li> <li> <p><code>*.logfiles.zip</code>: output from tools</p> </li> <li> <p><code>*.json.gz</code>: mapping from files names to SHA 256 hashes for the file content</p> </li> <li> <p><code>*.xml.bz2.table.html</code>: HTML views on the detailed results data as generated by BenchExec’s table generator</p> </li> <li> <p><code>*.All.table.html</code>: HTML views of the full benchmark set (all categories) for each tool</p> </li> <li> <p><code>META_*.table.html</code>: HTML views of the benchmark set for each meta category for each tool, and over all tools</p> </li> <li> <p><code><category>*.table.html</code>: HTML views of the benchmark set for each category over all tools</p> </li> <li> <p><code>iZeCa0gaey.html</code>: HTML views per tool</p> </li> <li> <p><code>quantilePlot-*</code>: score-based quantile plots as visualization of the results</p> </li> <li> <p><code>quantilePlotShow.gp</code>: example Gnuplot script to generate a plot</p> </li> <li> <p><code>score*</code>: accumulated score results in various formats</p> </li> </ul> <p>The hashes of the file names (in the files <code>*.json.gz</code>) are useful for</p> <ul> <li>validating the exact contents of a file and</li> <li>accessing the files from the witness store.</li> </ul> <p>Other Archives</p> <p>Overview over archives from Test-Comp 2022 that are available at Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.5831010">https://doi.org/10.5281/zenodo.5831010</a> Test Suites from Test-Comp 2022 Test-Generation Tools. Witness store (containing the generated test suites)</li> <li><a href="https://doi.org/10.5281/zenodo.5831012">https://doi.org/10.5281/zenodo.5831012</a> Results of the 4th Intl. Competition on Software Testing (Test-Comp 2022). Results (XML result files, log files, file mappings, HTML tables)</li> <li><a href="https://doi.org/10.5281/zenodo.5831003">https://doi.org/10.5281/zenodo.5831003</a> SV-Benchmarks: Benchmark Set of SV-COMP 2022 and Test-Comp 2022. Test tasks, version testcomp22</li> <li><a href="https://doi.org/10.5281/zenodo.5720267">https://doi.org/10.5281/zenodo.5720267</a> BenchExec, version 3.10. Benchmarking framework</li> </ul> <p>All benchmarks were executed for Test-Comp 2022 <a href="https://test-comp.sosy-lab.org/2022/">https://test-comp.sosy-lab.org/2022/</a> by Dirk Beyer, LMU Munich, based on the following components:</p> <ul> <li><a href="https://gitlab.com/sosy-lab/test-comp/archives-2022">https://gitlab.com/sosy-lab/test-comp/archives-2022</a> testcomp22 c211efbc</li> <li><a href="https://gitlab.com/sosy-lab/benchmarking/sv-benchmarks">https://gitlab.com/sosy-lab/benchmarking/sv-benchmarks</a> testcomp22 ad265d07</li> <li><a href="https://gitlab.com/sosy-lab/test-comp/bench-defs">https://gitlab.com/sosy-lab/test-comp/bench-defs</a> testcomp22 93f581b9</li> <li><a href="https://gitlab.com/sosy-lab/software/benchexec">https://gitlab.com/sosy-lab/software/benchexec</a> 3.10 4e8716bd</li> <li><a href="https://gitlab.com/sosy-lab/benchmarking/competition-scripts">https://gitlab.com/sosy-lab/benchmarking/competition-scripts</a> testcomp22 2022c698</li> <li><a href="https://gitlab.com/sosy-lab/test-comp/test-format">https://gitlab.com/sosy-lab/test-comp/test-format</a> testcomp22 2895be41</li> </ul> <p>Contact</p> <p>Feel free to contact me in case of questions: <a href="https://www.sosy-lab.org/people/beyer/">https://www.sosy-lab.org/people/beyer/</a></p>
Supplementary materials for "Testing Software's Changing Features with Environment-Driven Abstraction Identification"
<p><strong>Supplementary materials of the paper entitled:</strong></p> <p><strong>“Testing Software’s Changing Features with Environment-Driven Abstraction Identification”</strong></p>
Dataset para "Gamificação no ensino-aprendizagem de teste de software: um mapeamento sistemático da literatura"
<p>Documento contendo o detalhamento das etapas de seleção de estudos e extração de dados de um mapeamento sistemático da literatura (vide http://dx.doi.org/10.13140/RG.2.2.30215.00168) conduzido acerca de gamificação no contexto de ensino-aprendizagem de teste de software.</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.