Find research datasets worth reusing

opencc-by-4.0Mar 2022View details →

Minimal dataset to test multiplexed DNA imaging (Hi-M) software pipelines

This is a dataset of nuclei (DAPI), and 3 multiplexed DNA imaging cycles to test and validate processing software packages, such as pyHiM (https://github.com/marcnol/pyHiM). This dataset was acquired in a nc14 Drosophila embryo. File contents: scan_001_RT27_001_ROI_converted_decon_ch00.tif     barcode 27, fiducial     scan_001_RT27_001_ROI_converted_decon_ch01.tif     barcode 27 scan_001_RT29_001_ROI_converted_decon_ch00.tif     barcode 29, fiducial           scan_001_RT29_001_ROI_converted_decon_ch01.tif     barcode 29      scan_001_RT37_001_ROI_converted_decon_ch00.tif     barcode 37, fiducial              scan_001_RT37_001_ROI_converted_decon_ch01.tif     barcode 37        scan_006_DAPI_001_ROI_converted_decon_ch00.tif     DAPI      scan_006_DAPI_001_ROI_converted_decon_ch01.tif     DAPI, fiducial         scan_006_DAPI_001_ROI_converted_decon_ch02.tif     RNA   To test this dataset please refer to <a href="https://github.com/marcnol/pyHiM">pyHiM documentation page</a>.

opencc-by-4.0Jun 2022View details →

Cortical slice labelled with anti GFP and VAMP2 antibodies - sample image for software testing of "Contacting synapse" protocol

Image 1.tif is a Brain slice. This 16 bits confocal stack of pictures ((801x711 pixels x33 z slices - pixel size 78.17 nm) of a brain slice has been taken at 93x (LeicaHC PL APO CS2 93x/1.30 GLYC) in sequential mode with two channels : one dedicated to the GFP detection, and the other one to synpatic boutons labelled with VAMP2 protein. VAMP2 protein are expressed at glutamatergic presynaptic sites and is usually found apposed to Post Synaptic Density. This is a good sample to test "contacting synapse" software. Here GFP cells were electroporated with various plasmid. The aim of the software is to identify if expression of those plasmid within the GFP labelled cell, influence the density of synapse contacting this GFP cells. Here presynaptic contact are identified through the use of antibodies to VAMP2 proteins.

opencc-by-sa-4.0Mar 2018View details →

Survey of participant experience in workshop for testing IGP software setup: supplemental dataset for SimAUD 2018

This is a supplemental dataset for a SimAUD 2018 paper. For the context of the dataset, plots, and description text given here, please refer to the paper: <blockquote> Heinrich, M.K., Zahadat, P., Harding, J., et al. Using interactive evolution to design behaviors for non-deterministic self-organized construction. In Proc. of SimAUD (2018). In print. </blockquote> These survey results (see attached file dataset_survey-responses), are regarding the experience of participants in a workshop testing the Integrated Growth Projection software setup, including an implementation of the Vascular Morphogenesis Controller, and the Interactive Evolution software Biomorpher. The full-time one-week workshop was held as part of the normal coursework of the Master's degree program CITAstudio: Computation in Architecture, in the Institute of Architecture and Technology, at [KADK] The Royal Danish Academy, School of Architecture, Copenhagen, Denmark. It was part of the first semester of the 2017-2018 school year. Workshop participants were current Master's students in the CITAstudio program. The workshop teaching was led by Mary Katherine Heinrich and Phil Ayres, with guest teaching by Payam Zahadat and John Harding, overall program teaching supervision by Paul Nicholas, and teaching assistance by Sebastian Gatz. Survey method: The workshop participants gave survey responses anonymously. Survey responses were collected via Google Forms (https://www.google.com/forms/about/). At the start of the survey, participants gave permissions for use and publication, and verified that they participated in the workshop and had not previously taken the survey. The platform discourages duplicate responses by requiring an email sign-in (which is not visible to the surveyor). Although workshop participants gave permission for survey results to be published before taking the survey, the participants were unaware of the specific intended context and purpose of publishing, prior to taking the survey. Authors of the related paper who were workshop participants had no contact with the process of survey preparation, analysis of its results, or writing of related paper sections.  There were 26 workshop participants. Participants were architects or architectural designers.  Participants were asked about 1) their prior experience, 2) their understanding of topics before and after the workshop, 3) the helpfulness of specific software aspects for their understanding and their project work, and 4) their likelihood to use specific software aspects in the future. In addition to looking at the full surveyed group, we compare experience sub-groups. Participants select relevant tasks that they have previously completed, from a provided list. They are placed in the Less Experience sub-group if they select one or no tasks, and in the More Experience sub-group if they select two or more.  Survey results: Close to two-thirds of workshop participants submitted survey responses (16 of 26, or 61.5%), with at least two respondents per group. One respondent indicated workshop absence; their responses were removed. One respondent indicated that they did not understand two questions, so those two responses were removed. All responses were submitted within 18 days of workshop end. Attached file: Plot_1, caption: <blockquote> Plot 1: Participants' scoring of their understanding of the topics "self-organization" and "Interactive Evolution" respectively, comparing scores before and after the workshop. </blockquote> Attached file: Plot_2, caption: <blockquote> Plot 2: (Left) Participants' scoring of their likelihood to use certain aspects of the software setup again, if they were to design a non-deterministic self-organizing behavior, and (right) participants' indications of the helpfulness of those same software aspects. </blockquote> Responses regarding understanding (see attached file, Plot_1) give evidence that the Integrated Growth Projection software setup helped participants of both experience levels improve their understanding of related topics. Those with less prior experience improved their understanding more than others, and understanding of "Interactive Evolution" improved slightly more than understanding of "self-organization."  Responses regarding the usefulness of certain software aspects (see attached file, Plot_2) give evidence that: 1) Interactive Evolution helped participants to understand and design a non-deterministic self-organizing behavior (see Plot_2, a); 2) visualization of the environment and simultaneous viewing of multiple results helped them to understand and design such behaviors (see Plot_2, b and c); and 3) the Integrated Growth Projection's features of environment visualization and simultaneous results inside the artificial selection preview windows of the IE setup helped them to evolve behaviors to solve their chosen tasks (see Plot_2, d and e).  ____________________________________ The research work involved here is part of EU project flora robotica. <a href="http://www.florarobotica.eu/">http://www.florarobotica.eu/</a> Project flora robotica has received funding from the European Union's Horizon 2020 research and innovation program under the FET grant agreement, no. 640959.

opencc-by-4.0Apr 2023View details →

Testing and Demonstration Data for DataRig Software

This repository holds the testing and demonstration data for <a href="https://github.com/mscaudill/datarig">DataRig</a>, an opensource software program for downloading datasets from data repositories utilizing RESTful APIs. This repository contains 5 sample datasets.   annotations_001.txt This data set is a tab-separated text file containing 6 columns that start on line number 7. The column headers are;   'Number'   'Start Time'    'End Time'    'Time From Start'    'Channel'    'Annotation' There are 13 rows of data under each of these column headers representing the start and end times of annotated events from an eeg recording file in this repository called recording_001.edf. The events describe the behavior of a mouse in 5 sec increments with each behavior being one of 'exploring', 'grooming' or 'rest'.   recording_001.edf A European Data Format file consisting of 4 channels of EEG data lasting approximately 1 hour. The times in the annotations_001.txt file are referenced against this file.   sample_arr.npy A numpy array of shape (4, 250) with values sequentially running from 0 to 1000.   sample_excel.xls An excel file with a single column of 10 numbers from 0-9 sequentially.   sample_text.txt A text file with 4 rows containing 250 values per row. The values in the file run from 0 to 1000 sequentially.

opencc-by-4.0Mar 2020View details →

DATASET - AVALIAÇÃO EMPÍRICA DA GERAÇÃO AUTOMATIZADA DE TESTES DE SOFTWARE SOB A PERSPECTIVA DE TEST SMELLS

A constante busca pela qualidade sempre está em destaque na área de Engenharia de Software. Dentre as diversas disciplinas dedicadas a essa temática, o teste de software tem se estabelecido como uma das mais importantes, dado sua eficácia na identificação de defeitos, em momento prévio à liberação de sistemas de software para o mercado. O teste de software é atividade-chave para o desenvolvimento de software de qualidade. Entretanto, desenvolver testes é tão ou mais custoso do que desenvolver o código de produção. Uma alternativa para a redução dos custos associados ao teste de software se dá pelo uso intensivo de ferramentas de automação de testes. A proposta dessas ferramentas é reduzir o tempo de produção sem afetar a qualidade do código. Apesar dessa premissa, não é comum encontrar abordagens que incluam uma camada de verificação de qualidade dos testes gerados automaticamente, o que pode reduzir a confiabilidade da eficácia desses testes. Neste cenário, a proposta dessa dissertação é analisar empiricamente massas de dados de teste, sob a perspectiva de test smells, no sentido de avaliar a qualidade dos testes produzidos por ferramentas de geração automatizada de testes de software. Test smells são más escolhas no design dos testes e tem características sintomáticas e podem acarretar diminuição na qualidade dos sistemas. Considerando os test smells em código de teste, o estudo analisa os testes gerados por duas ferramentas amplamente aceitas pela comunidade de testes: Evosuite e Randoop. Um conjunto de vinte e um projetos de software de código aberto, disponíveis na plataforma Github foram considerados no estudo. A análise considerou a dispersão de test smells no código de teste desses projetos, bem como a existência de potenciais correlações entre test smells e as relações com as métricas estruturais. Como principais resultados, encontramos fortes correlações entre os test smells e as métricas de cobertura do código, diferenças significativas entre os dados encontrados nas suítes de testes geradas automaticamente e com os testes pré-existentes nos projetos avaliados.

opencc-by-4.0Apr 2020View details →

Measuring Software Testability Modulo Test Quality - Replication Package

This repository represents the replication package for the paper Measuring Software Testability Modulo Test Quality. It includes the dataset and the Jupyter Notebook we used for the analysis in our paper.

opencc-by-4.0Jan 2021View details →

Testing 3D modelling software. Modelling charging pads for WPT of electric vehicles for EM emissions simulation.

Even for the experienced 3D FEM modelers it may not be obvious which geometry discretization is the most appropriate and suitable for this type of problem. It may be a conservative approach to test the computation tool on a simplified geometry, on which the magnetic field distribution is known. As part of the “Metrology for inductive charging of electric vehicles” (MICEV) project (www.micev.eu), an axisymmetric geometry was used, with the results reported.

opencc-by-4.0Aug 2021View details →

Replication Package "Applying Test Case Prioritization to Software Microbenchmarks"

Replication package for the paper "Applying Test Case Prioritization to Software Microbenchmarks" accepted for publication in Empirical Software Engineering.

opencc-by-4.0May 2020View details →

Results of the 1st International Competition on Software Testing (Test-Comp 2019)

This file describes the contents of an archive of the 1st Competition on Software Testing (Test-Comp 2019) <a href="https://test-comp.sosy-lab.org/2019/">https://test-comp.sosy-lab.org/2019/</a> The competition was run by Dirk Beyer, LMU Munich, Germany. More information is available in the following article: Dirk Beyer. First International Competition on Software Testing: Test-Comp 2019. International Journal on Software Tools for Technology Transfer, 2020. Copyright (C) Dirk Beyer <a href="https://www.sosy-lab.org/people/beyer/">https://www.sosy-lab.org/people/beyer/</a> 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>   To browse the competition results with a web browser, there are two options: - start a local web server using   php -S localhost:8000   in order to view the data in this archive, or - browse <a href="https://test-comp.sosy-lab.org/2019/results/">https://test-comp.sosy-lab.org/2019/results/</a>   in order to view the data on the Test-Comp web page. Contents: index.html          directs to the overview web page LICENSE.txt         specifies the license README.txt          this file results-validated/  results of validation runs results-verified/   results of verification runs and aggregated results The folder results-validated/ contains the results from validation runs: - *.xml.bz2         XML results from BenchExec - *.logfiles.zip    output from tools - *.json.gz         mapping from files names to SHA 256 hashes for the file content The folder results-verified/ contains the results from test-generation runs and aggregated results: index.html               overview web page with rankings and score table design.css               HTML style definitions *.xml.bz2                XML results from BenchExec *.merged.xml.bz2         XML results from BenchExec, status adjusted according to the validation results *.logfiles.zip           output from tools *.json.gz                mapping from files names to SHA 256 hashes for the file content *.xml.bz2.table.html     HTML views on the detailed results data as generated by BenchExec's table generator *.All.table.html         HTML views of the full benchmark set (all categories) for each tool META_*.table.html        HTML views of the benchmark set for each meta category for each tool, and over all tools <category>*.table.html   HTML views of the benchmark set for each category over all tools iZeCa0gaey.html          HTML views per tool quantilePlot-*           score-based quantile plots as visualization of the results quantilePlotShow.gp      example Gnuplot script to generate a plot score*                   accumulated score results in various formats The hashes of the file names (in the files *.json.gz) are useful for - validating the exact contents of a file and - accessing the files from the witness store.   Overview over archives from Test-Comp 2019 that are available at Zenodo: <a href="https://doi.org/10.5281/zenodo.3856669">https://doi.org/10.5281/zenodo.3856669</a>   Witness store (containing the generated test suites) <a href="https://doi.org/10.5281/zenodo.3856661">https://doi.org/10.5281/zenodo.3856661</a>   Results (XML result files, log files, file mappings, HTML tables) <a href="https://doi.org/10.5281/zenodo.3856478">https://doi.org/10.5281/zenodo.3856478</a>   Test tasks, version testcomp19 <a href="https://doi.org/10.5281/zenodo.2561835">https://doi.org/10.5281/zenodo.2561835</a>   BenchExec, version 1.18 All benchmarks were executed for Test-Comp 2019, <a href="https://test-comp.sosy-lab.org/2019/">https://test-comp.sosy-lab.org/2019/</a> by Dirk Beyer, LMU Munich based on the components git@github.com:sosy-lab/sv-benchmarks.git  testcomp19-0-g6a770a9c1 git@gitlab.com:sosy-lab/test-comp/bench-defs.git  testcomp19-0-g1677027 git@github.com:sosy-lab/benchexec.git  1.18-0-gff72868 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>

opencc-by-4.0Jan 2021View details →

Results of the 3rd Intl. Competition on Software Testing (Test-Comp 2021)

Competition Results This file describes the contents of an archive of the 3rd Competition on Software Testing (Test-Comp 2021). <a href="https://test-comp.sosy-lab.org/2021/">https://test-comp.sosy-lab.org/2021/</a> The competition was run by Dirk Beyer, LMU Munich, Germany. More information is available in the following article: Dirk Beyer. Status Report on Software Testing: Test-Comp 2021. In Proceedings of the 24th International Conference on Fundamental Approaches to Software Engineering (FASE 2021, Luxembourg, March 27 - April 1), 2021. Springer. Copyright (C) Dirk Beyer <a href="https://www.sosy-lab.org/people/beyer/">https://www.sosy-lab.org/people/beyer/</a> 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> To browse the competition results with a web browser, there are two options: <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/2021/results/">https://test-comp.sosy-lab.org/2021/results/</a> in order to view the data on the Test-Comp web page.</li> </ul> Contents <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> The folder <code>results-validated/</code> contains the results from validation runs: <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> The folder <code>results-verified/</code> contains the results from test-generation runs and aggregated results: <ul> <li><code>index.html</code>: overview web page with rankings and score table</li> <li><code>design.css</code>: HTML style definitions</li> <li><code>*.xml.bz2</code>: XML results from BenchExec</li> <li><code>*.merged.xml.bz2</code>: XML results from BenchExec, status adjusted according to the validation results</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> <li><code>*.xml.bz2.table.html</code>: HTML views on the detailed results data as generated by BenchExec’s table generator</li> <li><code>*.All.table.html</code>: HTML views of the full benchmark set (all categories) for each tool</li> <li><code>META_*.table.html</code>: HTML views of the benchmark set for each meta category for each tool, and over all tools</li> <li><code><category>*.table.html</code>: HTML views of the benchmark set for each category over all tools</li> <li> <code>iZeCa0gaey.html</code>: HTML views per tool </li> <li><code>quantilePlot-*</code>: score-based quantile plots as visualization of the results</li> <li><code>quantilePlotShow.gp</code>: example Gnuplot script to generate a plot</li> <li> <code>score*</code>: accumulated score results in various formats </li> </ul> The hashes of the file names (in the files <code>*.json.gz</code>) are useful for <ul> <li>validating the exact contents of a file and</li> <li>accessing the files from the witness store.</li> </ul> Other Archives Overview over archives from Test-Comp 2021 that are available at Zenodo: <ul> <li><a href="https://doi.org/10.5281/zenodo.4459466">https://doi.org/10.5281/zenodo.4459466</a> Witness store (containing the generated test suites)</li> <li><a href="https://doi.org/10.5281/zenodo.4459470">https://doi.org/10.5281/zenodo.4459470</a> Results (XML result files, log files, file mappings, HTML tables)</li> <li><a href="https://doi.org/10.5281/zenodo.4459132">https://doi.org/10.5281/zenodo.4459132</a> Test tasks, version testcomp21</li> <li><a href="https://doi.org/10.5281/zenodo.4317433">https://doi.org/10.5281/zenodo.4317433</a> BenchExec, version 3.6</li> </ul> All benchmarks were executed for Test-Comp 2021 <a href="https://test-comp.sosy-lab.org/2021/">https://test-comp.sosy-lab.org/2021/</a> by Dirk Beyer, LMU Munich, based on the following components: <ul> <li><a href="https://gitlab.com/sosy-lab/test-comp/archives-2021">https://gitlab.com/sosy-lab/test-comp/archives-2021</a> testcomp21-0-gdacd4bf</li> <li><a href="https://gitlab.com/sosy-lab/software/sv-benchmarks">https://gitlab.com/sosy-lab/software/sv-benchmarks</a> testcomp21-0-gefea738258</li> <li><a href="https://gitlab.com/sosy-lab/software/benchexec">https://gitlab.com/sosy-lab/software/benchexec</a> 3.6-0-gb278ebbb</li> <li><a href="https://gitlab.com/sosy-lab/benchmarking/competition-scripts">https://gitlab.com/sosy-lab/benchmarking/competition-scripts</a> testcomp21-0-g8339740</li> <li><a href="https://gitlab.com/sosy-lab/test-comp/bench-defs">https://gitlab.com/sosy-lab/test-comp/bench-defs</a> testcomp21-0-g9d532c9</li> </ul> Contact 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>

opencc-by-4.0Dec 2020View details →

Data and material for the manuscript "Mutation testing and self/peer assessment: analyzing their effect on students in a software testing course"

This repository is composed of two different parts: <ul> <li><a href="https://zenodo.org/record/4464300/files/Assessment%20data%20and%20Mutation%20Scores.xlsx?download=1">Assessment data and Mutation Scores</a> file contains the student-generated data used in the experience.</li> <li><a href="https://zenodo.org/record/4464300/files/experience-material.zip?download=1">Experience-material</a> file contains the files to be able to reproduce the experience.</li> </ul>   The <a href="https://zenodo.org/record/4464300/files/experience-material.zip?download=1">Experience-material</a> file for the lab is used in two sessions: Session 1: Development and assessment of test suites In this session, the student has to develop a test suite for a program under test. At the end of the session, the test suite will be evaluated against a set of assessment criteria regarding the quality of the developed test suite. Files for this session: <ul> <li>VVS-Lab6-S1 pdf file , with the description of this session.</li> <li>Material-S1 zip file, with the files required to complete this session.</li> </ul> Session 2: Evaluation applying mutation testing with MuCPP In this session, the test cases designed in the first part of this lab will be evaluated based on the mutation adequacy criterion. This will be done by using the <a href="https://ucase.uca.es/mucpp/">MuCPP mutation tool</a>. Files for this session: <ul> <li>VVS-Lab6-S2 pdf file, with the description of this session.</li> <li>Material-S2 zip file, with the files required to complete this session.</li> </ul> The source code files family.[cpp|hpp] have been adapted from a listing in [1]. Note that, while considered to be fault free in this lab, these source files are used in other sessions where students are expected to detect some defects in them. [1] S. Wiener and L. J. Pinson, The C++ Workbook. USA: Addison-Wesley Longman Publishing Co., Inc., 1990.

opencc-by-4.0Jun 2021View details →

Supplemental Material: What we talk about when we talk about software test flakiness

This supplemental material details the definitions of the concepts that have been found by conducting the scoping review of both the white and grey literature introduced in Section 2 of the manuscript titled: "What we talk about when we talk about software test flakiness".

opencc-by-4.0Jan 2022View details →

Extra Testing Data for paper "OC_Finder: A deep learning-based software for osteoclast segmentation, classification, and counting"

<pre>Here we have 9 datasets we used to validate OC_Finder's performance on various imaging settings. The 9 datasets are inside the folder named "9 datasets for validation experiment". Each dataset is composed of image files and csv files for the coordination of osteoclasts and non-osteoclasts that were manually labelled by human examiner. csv files ending "_posi" has coordination of osteoclasts and "_nega" has coordination of non-osteoclasts. Images in dataset #4, #5, #6, #7, #8, and #9 were resized so the scale of the images matched to the OC_Finder's training dataset. Images in original size before resizing are also provided in "Original images before resizing". Detailed capture setting and resizing information of images in each dataset can be found in "capture setting.xlsx". The number of images in each dataset are as following: #1: 18 #2: 18 #3: 18 #4: 36 #5: 36 #6: 36 #7: 16 #8: 16 #9: 16</pre>

opencc-by-4.0Sep 2021View details →

Replication Data for "Mapping the Structure and Evolution of Software Testing Research Over the Past Three Decades"

In this research (publication included in the package), we have used author-assigned keywords as a quantitative data source for understanding the connections between keywords and research topics in software testing research, based on a large sample of studies from Scopus. We apply co-word analysis to map the topology of testing research as a network where author-assigned keywords are connected by edges indicating co-occurrence in publications. Keywords are clustered based on edge density and frequency of connection. We examine the most popular keywords, summarize clusters into high-level research topics, examine how topics connect, and examine how the field is changing. This package contains the map and network files used to perform our analyses, as well as the publication sample.

opencc-by-4.0Mar 2018View details →

Data Set Used in Combinatorial Modeling and Test Case Generation for Industrial Control Software using ACTS

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.

opencc-by-4.0Nov 2018View details →

Generated Software Testing Workload

This dataset represents a software testing workload generated from the distributions characterizing a real software testing workload. It consists of instance files, each of which is structured as follows: <pre><code>[number of test suites] [test suite uuid] [test suite priority (1>0)] [arrival time (s)] [number of test cases] [test case uuid] [test case type] [test case outcome (0 - pass)] [test case duration (s)] [test case uuid] [test case type] [test case outcome (0 - pass)] [test case duration (s)] (...) [test suite uuid] [test suite priority (1>0)] [arrival time (s)] [number of test cases] [test case uuid] [test case type] [test case outcome (0 - pass)] [test case duration (s)] [test case uuid] [test case type] [test case outcome (0 - pass)] [test case duration (s)] (...) (...)</code></pre>

opencc-by-4.0Sep 2024View details →

Supplemental material for: Software System Testing assisted by Large Language Models: An Exploratory Study

This is the supplemental material of the paper titled as “Software System Testing Assisted by Large Language Models: An Exploratory Study” presented at the 36th International Conference on Testing Software and Systems. It contains the raw execution data generated by both models, GPT-4o and GPT-4omini, during the exploratory study. The supplementary material includes the following files: <ul> <li>GPT-4ominiRQ1-2ExecutionData.zip: contains the JSON outputs from the OpenAI API for the GPT-4o mini model. Each output is labeled according to the research question number and the corresponding timestamp (for RQ1) or the requested test case (for RQ2), all provided in plain text format.</li> <li>GPT-4oRQ1-2ExecutionData.zip: contains the JSON outputs from the OpenAI API for the GPT-4o model. Like the previous file, each output is named in plain text format based on the research question number and timestamp (for RQ1) or the requested test case (for RQ2).</li> </ul> To cite this work:  C. Augusto, J. Morán, A. Bertolino, C. de la Riva and J. Tuya, “Software System Testing assisted by Large Language Models: An Exploratory Study”, in Testing Software and Systems (pp. 239–255). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-80889-0_17

opencc-by-4.0Jul 2021View details →

Data and Software associated with the paper "``A New Likelihood-based Test for Natural Selection''"

Data and Software associated with the paper  ``A New Likelihood-based Test for Natural Selection''

opencc-by-4.0Jun 2024View details →

Choosing the Right Test Generation Tool: A Guide for Software Practitioners

Context: As software systems become increasingly complex, testing automation plays a critical role in ensuring product quality and reliability. However, the wide variety of available test generation tools—with distinct purposes, features, and approaches—makes it difficult for practitioners to select the most appropriate option for their projects. Goal: This study aims to identify, analyze, and compare test generation tools reported in both academic and industrial contexts, providing a practical reference guide to support software professionals in tool selection decisions.  Method: We conducted a Multivocal Literature Review (MLR) complemented by a two-round survey with 87 software practitioners. The MLR identified tools and features reported in white and gray literature, while the survey assessed practitioners’ familiarity, usage, and perceptions of advantages and challenges associated with these tools. Results: The findings reveal a persistent gap between academic proposals and industrial adoption. While tools such as Postman, Selenium, and Cypress are among the most widely used tools in practice, academic tools like Monkey and Dynodroid remain rarely adopted. Practitioners value visibility, integration, and traceability as key features, whereas inconsistency and maintenance effort are seen as primary challenges. Conclusions: The study contributes a structured reference guide to assist professionals in selecting tools suitable for specific testing contexts. It also provides insights for researchers aiming to align future tool development with industry needs, fostering better usability, integration, and sustainability of automated testing solutions.