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74 results for “Software tools”
Software Tools to Collect and Use Provenance in R
The software tools that scientists use to process and analyze data are typically optimized for performance and ease of use. Few if any such tools are designed to capture and record the details of what happens as the tool performs its task. This detailed information, and more generally the history of an item of data from its creation to its present state, is known as provenance. Provenance has the potential to make science more transparent, reliable, and reproducible. This project focused on collecting and using provenance for scripts written in the R statistical language, which is widely used by ecologists and environmental scientists for data analysis and visualization. Our tools include a provenance collector (rdtLite), which collects provenance as an R script executes (or during a console session), as well as other tools that use the collected provenance to document and visualize the execution or to support activites such as script debugging. The R packages included here are also available on CRAN. For more details, see the project website on GitHub (https://end-to-end-provenance.github.io).
Imalys: ESIS-Software-Tools – Tutorial Data
<p>Imalys is a <a href="https://codebase.helmholtz.cloud/esis/Imalys">software library</a> in the <a href="https://doi.org/10.3390/rs16071139">ESIS project</a>. The Imalys library includes a <a href="https://codebase.helmholtz.cloud/esis/Imalys/tutorial">tutorial</a> that shows how image and vector data can be analyzed and transformed into new products. The examples in the tutorial refer to the sample data in <strong>Imalys_tutorial_data.zip</strong>.</p> <p>The software repository with source code, binaries, documents and the tutorials is available on <a href="https://codebase.helmholtz.cloud/esis/Imalys">GitLab</a> and in an earlier version on <a href="https://github.com/c7sepe2/Imalys_ESIS-Software-Tools">GitHub</a>.</p> <p>In the <a href="https://doi.org/10.3390/rs16071139">ESIS project</a> we are trying to put environmental indicators on a well-defined and reproducible basis. The ESIS software library "Imalys" is supposed to generate the remote sensing products defined for ESIS. Landscape diversity, change and different landuse types can be analyzed in time and space. Landuse borders can be delineated and typical landscape structures can be characterized by a self adjusting process.</p> <p><strong>Acknowledgements:</strong></p> <p>We thank the Helmholtz Association and the Federal Ministry of Education and Research (BMBF) for supporting the DataHub Initiative of the Research Field Earth and Environment. The DataHub enables an overarching and comprehensive research data management, following FAIR principles, for all topics in the Program Changing Earth – Sustaining our Future.</p> <p>Parts of the work was funded by the Federal Ministry for Digital and Transport of Germany (BMDV, grant no. 45KI19D041, Artificial Intelligence and Mobility - AIAMO project).</p>
RRID Gold Set of annotations for software tools in the biomedical literature
<p>This data is a subset of a larger human curated, machine assisted gold standard data set of RRID citations within the text of the scientific literature. The full set is accessible via Hypothes.is at https://hypothes.is/users/scibot?q=group%3A__world__ and via individual RRID records such as RRID:SCR_016250 https://scicrunch.org/resolver/SCR_016250/mentions?q=&i=rrid:scr_016250 </p><p>The data is based on authors who added RRIDs into their manuscripts. The data was then extracted by SciBot (RRID:SCR_016250), into Hypothes.is (RRID:SCR_000430) and then manually checked by a curator to determine if the author and the database agreed. The list of annotators is available in Hypothes.is user group: SciBotCurationGroup.</p><p>There are 78,140 rows and each row contains an annotation (annotation id, URI), linked to a paper (paper identifiers: PMID, DOI, PMC) and linked to the RRID (scr_id, exact, text_quote_selector). </p><p>A second spreadsheet contains a list of 8,322 software tools from the SciCrunch Registry (available here https://scicrunch.org/resources/data/source/nlx_144509-1/search ), enhanced by additions by thousands of individual authors, and curated over 10 years (Ozyurt et al., 2016). </p><p>The third spreadsheet contains a data dictionary and links to related ontologies, and tagging sets. </p><p> </p><p> </p>
Software-based decision support tools used in the sanitation sector
<p>This dataset includes data used in a scoping review on how decision support tools used in the sanitation sector address resource recovery considerations. The dataset is an accompaniment to the publication "A review of how decision support tools address resource recovery in sanitation systems", which was submitted to the Journal of Cleaner Production.</p>
Dataset: Systematic Mapping Study on the Development and Application of Sentiment Analysis Tools in Software Engineering
<p>Update: We updated the data set in March 2022 by adding newly published papers and by providing more insights on how we analyzed them. Details can be found in the file " SEnti-SMS.xlsx".</p> <p>----------</p> <p>Update: The updated version (-v2) contains the results of one more snowballing iteration and extracted information on the accuracy of the used methods.</p> <p>----------</p> <p>In 2020, we conducted a systematic literature review to explore the development and application of sentiment analysis tools in software engineering.</p> <p>Information on the execution of the SLR, its scope, the search string, etc. are presented in the paper linked below.</p> <p> </p> <p> </p>
Student's logs and perceptions of an automated assessment tool in a software engineering MOOC specialization
<p>Our dataset contains students' perceptions and usage of an automated assessment tool (MOOCauto) for obtaining formative feedback in software engineering assignments that are part of a MOOC specialization at Universidad Politécnica de Madrid (Spain), delivered by the MiriadaX platform. The dataset has previously been used in a study to evaluate students' perceptions of the tool and to analyze their usage patterns using Growth Mixture Models <a href="https://www.computer.org/csdl/magazine/so/5555/01/10196480/1P9AhkBLYXK">(López-Pernas et al., 2023)</a>. The code of each of the assignments is available on Github: <a href="https://github.com/ging-moocs">https://github.com/ging-moocs</a>.</p> <p>Our dataset contains two files:</p> <h2>MOOCauto usage logs</h2> <p>The first file is called<strong> moocauto_logs.csv </strong>and it contains 9,108 anonymized logs of students' use of the automated assessment tool in the MOOC specialization assignments. The columns of the dataset are as follows:</p> <ul> <li><strong>MOOCid</strong>: Unique numeric identifier for the MOOC (1-4)</li> <li><strong>MOOC: </strong>Name of the MOOC: Frontend Development, Backend Development, Git & Github, Fullstack Development</li> <li><strong>AssignmentName</strong>: Name of the assignment.</li> <li><strong>AssignmentId</strong>: Unique identifier for each assignment (1-17)</li> <li><strong>user: </strong>Unique identifier of the student (it varies per assignment)</li> <li><strong>timestamp: </strong>Time in which the assessment was performed</li> <li><strong>score</strong>: Score obtained (0-10)</li> </ul> <h2>Students' perceptions of MOOCauto</h2> <p>The second file is called <strong>moocauto_questionnaire.csv</strong> and it contains 213 students' responses to the questionnaire conducted at the end of each MOOC in order to evaluate their opinion of the tool and perception on usefulness, ease of use, and other aspects related to the Technology Acceptance Model (TAM). The questions were as follows:</p> <ul> <li><strong>What is your general opinion of MOOCauto?</strong> (1 Horrible - 5 Excellent)</li> <li><strong>Indicate your level of agreement with the following statements </strong>(1 Strongly disagree - 5 Strongly agree) <ul> <li>MOOCauto has been easy to install</li> <li>MOOCauto has been easy to use</li> <li>The feedback provided by MOOCauto was easy to understand</li> <li>The feedback provided by MOOCauto was useful</li> <li>The feedback provided by MOOCauto helped me improve my assignments</li> <li>The documentation Of MOOCauto was useful</li> <li>MOOCauto has increased my motivation to work on the assignments</li> <li>I prefer the feedback from MOOCauto than from peer assessment</li> <li>I would like to have a bot like MOOCauto in other MOOCs</li> </ul> </li> <li><strong>How useful do you perceive the following features of MOOCauto?</strong> (1 Useless - 5 Very useful) <ul> <li>It works locally on my computer</li> <li>It allows to run the test suite as many times as I want</li> <li>It provides instantaneous feedback every time the test suite is executed</li> <li>It has documentation that explains its use and available options</li> </ul> </li> </ul>
The Software Sustainability Institute's Collaborations Workshop 2015 (CW15) attendees computational tools dataset
<p>Contains the question, raw data, and cleaned data for producing the most used software word cloud for those who attended the Software Sustainability Institute's Collaborations Workshop 2015 (CW15) held at the Oxford e-Research Institute, Oxford, UK from 25-27 March 2015</p>
AI Tool Use and Adoption in Software Development by Individuals and Organizations: A Grounded Theory Study
<div> <p>This data represents four artifacts from our research in studying what impacts AI adoption and use in SE. It includes our interview questions, the codebook with example quotes, survey questions, and table with the code to category generation.</p> <p>This page includes supplementary materials associated with our paper entitled "<span>AI Tool Use and Adoption in Software Development by </span><span>Individuals and Organizations: A Grounded Theory Study</span>".</p> </div>
Tool Artifact for "Mutation-based Lifted Repair of Software Product Lines"
<p>In this work, we describe the installation, usage, and evaluation results of the tool SPLAllRepair introduced by the paper<br>``Mutation-based Lifted Repair of Software Product Lines''. We provide step-by-step instructions on how to download, run, and compare the tool's outputs to outputs described in the paper. The tool implements a novel lifted repair algorithm for program families (Software Product Lines - SPLs) based on code mutations. The inputs of our algorithm are an erroneous SPL and a specification given in the form of assertions. We use variability encoding to transform the given SPL into a single program, called family simulator, which is translated into a set of SMT formulas whose conjunction is satisfiable iff the simulator (i.e. the input SPL) violates an assertion. We use a predefined set of mutations applied to feature and program expressions of the given SPL.<br>The algorithm repeatedly mutates the erroneous family simulator and checks if it becomes (bounded) correct. The outputs are all minimal repairs in the form of minimal number of (feature and program) expression replacements such that the repaired SPL is (bounded) correct with respect to a given set of assertions. We present the experimental results showing that our approach is able to successfully repair various interesting #ifdef-based C SPLs.</p>
Software Variability Tools: Industrial Survey and Systematic Mapping Study
<p>Software Variability Tools: Industrial Survey and Systematic Mapping Study</p>
Choosing the Right Test Generation Tool: A Guide for Software Practitioners
<p> 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.</p>
Supplemental Material for "Make Your Tools Sparkle with Trust: The PICSE Framework for Trust in Software Tools"
<p>This package contains the materials that were used for the paper "Make Your Tools Sparkle with Trust: The PICSE Framework for Trust in Software Tools".</p> <ul> <li><strong>Interview Script.docx</strong> contains the script that was used for the semi-structured interviews.</li> <li><strong>Codebook.xlsx </strong>contains the final codebook of the study.</li> </ul>
Software Variability Tools SMS and Survey: List of References and Tools
<p>Software Variability Tools SMS and Survey: List of References and Tools</p>
Data for Precursor intensity-based label-free quantification software tools for Galaxy Platform.
<p><strong>Precursor intensity-based label-free quantification software tools for proteomic and multi-omic analysis within the Galaxy Platform.</strong></p> <p> </p> <p><strong>ABRF:</strong> Data was generated through the collaborative work of the ABRF Proteomics Research Group (<a href="https://abrf.org/research-group/proteomics-research-group-prg">https://abrf.org/research-group/proteomics-research-group-prg</a>). See Reference for details: Van Riper, S. et al. ‘<a href="http://cbs.umn.edu/sites/cbs.umn.edu/files/public/downloads/2016_ABRF_PRG_Poster_for_ASMS_20160501.pdf">An ABRF-PRG study: Identification of low abundance proteins in a highly complex protein sample</a>’ at the 64th Annual Conference of American Society of Mass Spectrometry and Allied Topics" at San Antonio, TX."</p> <p><strong>UPS:</strong> <strong>MaxLFQ Cox J, Hein MY, Luber CA, Paron I, Nagaraj N, Mann M.<a href="https://www.ncbi.nlm.nih.gov/pubmed/24942700/"> Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ.</a> Mol Cell Proteomics. 2014 Sep;13(9):2513-26. doi: 10.1074/mcp.M113.031591. Epub 2014 Jun 17. PubMed PMID: 24942700; PubMed Central PMCID: PMC4159666;</strong></p> <p><strong>PRIDE #5412; ProteomeXchange repository PXD000279: </strong>ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2014/09/PXD000279</p>
Evaluating usefulness, ease of use and usability of an UML-based Software Product Line Tool
<p>Vídeo de apresentação do artigo "Evaluating usefulness, ease of use and usability of an UML-based Software Product Line Tool" para o 34° Simpósio Brasileiro de Engenharia de Software (SBES'20), 21-23 de Outubro de 2020, Natal, RN, Brasil. Autores: Leandro F. da Silva e Edson OliveiraJr.</p>
The Software Sustainability Institute's Collaborations Workshop 2015 (CW15) attendees computational tools word-cloud
<p>Word cloud representing the computational tools used by those attending the Software Sustainability Institute's Collaborations Workshop 2015 (CW15).</p> <p>For more information see www.software.ac.uk/cw15</p> <p>Please note there is an ERROR in the diagram for some reason wordle.net did not pickup 'R' in the dataset - http://dx.doi.org/10.5281/zenodo.19828 - i.e. the usage of R in research software in the people who attended CW15 is not represented in this diagram.</p>
Filling the Gap: A Tool to Automate Parameter Estimation for Software Performance Models
<p>The data part of this release support the results <br /> presented in the paper <br /> "Filling the Gap: A Tool to Automate Parameter Estimation<br /> for Software Performance Models", by W. Wang, J. F. Perez, and G. Casale, accepted <br /> to QUDOS workshop 2015. </p>
Choosing the Right Test Generation Tool: A Guide for Software Practitioners
<p>Context: Software testing tools are essential during the processes of developing and maintaining quality digital applications in a scenario where they become increasingly complex. Problem: The market offers hundreds of test generation tools with different approaches and functionalities, it is important that developers and designers have knowledge of which tools are best suited to their work in order to avoid unnecessary expenses and easily avoidable frustrations. Solution: to identify the main tools available on the market in order to highlight their advantages and disadvantages, thus presenting a reference guide that will help developers choose<br>the most appropriate tool for each test situation. </p><p>Method In this work: a multivocal literature review has been carried out to identify works related to test generation tools, also identifying the most cited tools in white and gray literature. Furthermore, a survey was developed and conducted with professionals working in different areas of software development, in order to ascertain their familiarity with the testing tools identified in the white and gray literature, as well as the advantages and challenges that have more weight when deciding which tool to adopt.</p><p>Summarization of Results: The results showed that most of the tools found in the white literature, such as Monkey and Dynodroid, are not very well known and used by the participants and that they were more familiar with tools more mentioned in the gray literature, such as Postman and Selenium. In addition, a list of characteristics most desired and avoided by participants when needing to choose a new tool for a project was obtained. Impact on the IS field: This work contributes to IS field by providing a reference guide where practitioners can identify the most recommended tools according to a specific scenario, and then use a comparative table in order to evaluate the most appropriate tool for the project among those recommended. The Guide can be used by any testing practitioner.</p>
SimRE: A Requirements Similarity Tool for Software Product Lines - Dataset
<p>The <strong>RequirementsPairs</strong> file consists of 34 pairs of software requirements related to GIS (Geographic Information Systems), each paired with a corresponding similarity degree. It was introduced in the paper <em>"SimRE: A Requirements Similarity Tool for Software Product Lines."</em></p> <p><strong>GISv1</strong> and <strong>GISv2</strong> refer to version 1 and version 2 of the GIS dataset, respectively. These datasets are composed of 173 requirements that represent the functionality of a web-based GIS product line.</p>
SoK: Taxonomy of Attacks on Open-Source Software Supply Chains - Visualization Tool Screenshots & Selected Papers
<p>This artifact complements the paper "SoK: Taxonomy of Attacks on Open-Source Software Supply Chains", submitted at IEEE S&P 2023.</p> <p>The papers selected during the Systematic Literature Review (SLR) are presented in the CSV file.</p> <p>This screenshots display the main features of the visualization tool that allows to explore the taxonomy of attacks on OSS supply chains, as well as the related safeguards and the selected references.</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.