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47 results for “software architecture”
Formal verification of software architectures with SysADL Studio
<p>This short video demonstrates how to formally verify a software architecture description expressed in the <a href="https://sysadl.imd.ufrn.br">SysADL architectural language</a> using its supporting tool, SysADL Studio.</p>
Continuous and proactive software architecture evaluation: An IoT case -- Dataset generated from iFogSim
<p>There will always be a trade-off between using the simulators and physical IoT devices in experimentation and data generation. This is due to the high cost of the actual deployment of IoT devices as compared to simulators. However, some companies, such as Amazon, IBM, and Intel, are motivating the need for having IoT simulation instrumenting what-if test scenarios, typically used during the architecture analysis and refinement stages to evaluate the response and sensitivity of the architecture to these tests. </p> <p>Additionally, many researchers are currently looking for an IoT dataset that provides QoS for IoT architectures. This work provides a dataset well-tested for the most important quality attributes when evaluating IoT architectures.</p> <p>In particular, this work used iFogSim to generate QoS of various IoT architectures in the form of Response Time, Energy consumption, and network usage. After that, MOA framework was used to generate the Forecast QoS values using different time series forecasting algorithms.</p>
Dataset for "Evaluation Methods and Replicability of Software Architecture Research Objects"
<p># Content<br> In this package, please find the following content:</p> <p>* Investigated Papers.bib<br> A BibTeX file with all papers investigated in the paper "Evaluation Methods and Replicability of Software Architecture Research Objects"<br> * Raw-Data-Table Content-Data.html and Raw-Data-Table Meta-Data.html<br> Tables with the raw data as extracted during the systematic literature review<br> * Colection of Data Visualizations.pdf<br> Multiple visualizations of the raw data for analysis. A copy of summary.pdf as described below.<br> * Data and Visualization<br> Contains:<br> - The data as CSV files,<br> - scripts for creating visualizations<br> - *.awk -- Awk scripts are used to create the corresponding of the *.csv files in data<br> - *.rb -- Ruby scripts to build the respective figures in figs as *.tex files<br> - make-all.sh -- A script to call all other scripts for creating diagrams and the summary<br> - make-paper-figures.sh -- A script to build "paper-figures.pdf" with all diagrams used in the accompanying paper<br> - A documentation of the contained scripts (Data and Visualization/README.md)<br> - summary.pdf -- A collection of diagrams (as built by make-all.sh)<br> - paper-figures.pdf -- A collection of all diagrams as used in the accompanying paper (as built by make-paper-figures.sh and make-all.sh)<br> * Wiki/<br> A copy of the wiki used during data extraction.<br> Constains:<br> - descriptions of all data items<br> - the process description<br> - the taxonomy used for data extraction</p> <p><br> # Reproduction<br> You can reproduce the visualizations with the following commands in a UNIX command line environment.</p> <p>> cd "Data and Visualization"<br> > ./make-paper-figures.sh<br> > ./make-all.sh</p> <p>The requirements are:<br> * A UNIX command line environment (e.g., bash) with awk installed<br> * Ruby (>2.5)<br> * latex (e.g., tex-live)</p> <p>The command "./make-paper-figures.sh" produces the file “paper-figures.pdf”, which contains all diagrams that are used in the paper.<br> The command "./make-all.sh" produces the file "summary.pdf", which contains diagrams used for data analysis, and the file "paper-figures.pdf". All figures describing the results in the paper are also in "summary.pdf".<br> These commands each take about 2 ("/make-paper-figures.sh") / 8 ("./make-all.sh") minutes to run on current standard laptop (Intel i5-8250U, 16 GB memory).<br> Calling the commands produces many log statements (information and warnings), which show the progress and can be ignored.</p>
A Classification of Software-Architectural Uncertainty regarding Confidentiality
<p>Dataset for the paper "A Classification of Software-Architectural Uncertainty regarding Confidentiality". For more information, please see the README.md.</p>
A Classification of Software-Architectural Uncertainty regarding Confidentiality
<p>Dataset for the paper "A Classification of Software-Architectural Uncertainty regarding Confidentiality". For more information, please see the README.md.</p>
Additional Material for Debiasing Architectural Decision-Making: Teaching Software Practitioners
<p>Additional material for the paper subsmission "Debiasing Architectural Decision-Making: Teaching Software Practitioners".<br><br>Coding_info.xlsx - Code description as well as code measurements for all coded values.<br>Experiment-plan.docx - Instructions used by authors which performed the experiment.<br>Debiasing-workshop-plan.docx - Instruction for the teacher conducting the workshop, specifying what should be done while showcasing particular presentation slides.<br>Debiasing-workshop-slides.pptx - Slides used during the debiasing workshop.<br>Questionaire_and_test.xlsx - Questionnaire used to gather information about the participants + Simple test used as the last step of the workshop.</p>
Electric Vehicle Fast-Charging Software: Architectural Considerations Towards Trustworthiness
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The Nature of Questions that Arise During Software Architecture Design
<p>This repository contains the companion data for the paper titled "The Nature of Questions that Arise During Software Architecture Design", by Neil B. Harrison (Utah Valley University) and Ademar Aguiar (INESC TEC, Faculdade de Engenharia da Universidade do Porto). 2024, published at ECSA 2024.</p> <p>It contains all the material required for replicating the study, including the survey responses and experiment data.</p>
Energy Consumption of IoT Monitoring Software Architectures in the Edge
<p>Data repository with the raw and synthesized data of the paper published in the ECSA 2024 "<strong>Energy Consumption of IoT Monitoring Software Architectures in the Edge</strong>"</p> <p>This repository presents the experimental results of an exploratory study that measures the energy consumption of four Edge software architecture configurations of an indoor environmental monitoring IoT system. This dataset provides the raw measurements, the data analysis and the results comparison of the four architectures.<br>This repository is composed of five folders. Their content is explainded following:<br>- AdditionalMetrics: It includes the raw data obtained from the 24 experiments that are not used for calculating the energy consumption but it was provided by the measurement tools.<br>- BasalEnergyConsumption: It includes the raw data of the experiments launched to measure the basal consumption of the Smart Gateway. In addition, the excel file with the calculation of the Basal Energy Consumption is also provided.<br>- DataSynthesis: The data analysis and synthesis from the results of energy consumption are included in this folder. <br>- EnergyMeasurementExperiments: It includes the raw energy consumption data obtained from the 24 experiments.<br>- Figures: It includes the figures generated from the data obtained.</p>
Dataset of the Paper "Architecture Decisions in Quantum Software Systems: An Empirical Study on Stack Exchange and GitHub"
<p>This dataset was collected from GitHub and Stack Exchange (including Stack Overflow, Quantum Computing Stack Exchange, and Computer Science Stack Exchange) to conduct an empirical study on architecture decisions in quantum software systems. We provide below a brief description of each file:</p><p><strong>1. Dataset (GitHub).xlsx</strong></p><p>contains selected quantum software projects from GitHub with project names, issue IDs, and issue URLs and the data extracted from the GitHub issues that are related to architecture decisions in quantum software development.</p><p><strong>2. Dataset (SO).xlsx</strong></p><p>contains the IDs and URLs of Stack Overflow (SO) labeled posts and the extracted data from the Stack Overflow posts that are related to architecture decisions in quantum software development.</p><p><strong>3. Dataset (QC).xlsx</strong></p><p>contains the IDs and URLs of Quantum Computing (QC) Stack Exchange labeled posts and the extracted data from the Quantum Computing Stack Exchange posts that are related to architecture decisions in quantum software development.</p><p><strong>4. Dataset (CS).xlsx</strong></p><p>contains the IDs and URLs of Computer Science (CS) Stack Exchange labeled posts and the extracted data from the Computer Science Stack Exchange posts that are related to architecture decisions in quantum software development.</p><p><strong>5. Extracted Data (GitHub+SO+QC+CS).xlsx</strong></p><p>provides the final results of data extracted from the related GitHub issues, SO posts, QC posts, and CS posts.</p>
Guidelines and Insights for Implementing Micro-Frontend Architecture in Software Development
<p><strong>Context: </strong>The complexity associated with incorporating new technologies into monolithic frontend projects has posed a challenge for software development teams. While the backend has advanced with microservices, the frontend has faced challenges related to code redundancy, consistency, scalability, and the lack of a modular approach. In response to these challenges, the micro-frontend architecture emerged, proposing a more modular and independent architecture.</p> <p><strong>Objective:</strong> To investigate the impacts and challenges associated with adopting the micro-frontend architecture and to provide practical guidelines for organizations to implement it.</p> <p><strong>Method:</strong> We conducted a Systematic Mapping Study (SMS) to identify the architectural patterns and visions used in micro-frontends. In addition, we conducted two surveys to validate strategies and guidelines for adopting the architecture.</p> <p><strong>Results:</strong> In the perception of the survey participants, the proposed guide can facilitate the process of adopting the micro-frontend architecture. As for the case study, we identified aspects related to practical implementation, covering performance and scalability, maintenance, collaboration, and parallel development. Participants also reported complexity associated with managing multiple smaller modules, as well as the lack of developer experience with micro-frontend architecture technologies. The case study also corroborated the findings of the surveys.</p> <p><strong>Conclusion:</strong> The findings highlighted the relevance of the Micro-frontend architecture in modernizing the frontend layer. However, it is important to note that the need for its adoption is strongly related to the complexity and size of the project and team. Thus, adopting the micro-frontend architecture with the support of a set of methodological and technological decisions has a greater chance of success in its implementation.</p> <p> </p> <p><br><em>Keywords: Micro-Frontend Architecture, Frontend Modernization, Systematic Mapping Study (SMS), Software Architecture, Web Development<br></em></p>
Architecturally Significant Requirements and Software Architecture for AI-Based Systems: A Case Study with Document Classification
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Complementary Material for the Paper: "Relationships between Software Architecture and Source Code in Practice: An Exploratory Survey and Interview"
<p>This is the complementary material for the paper: "Relationships between Software Architecture and Source Code in Practice: An Exploratory Survey and Interview", which is currently under review. We provide a brief description of the files and folder.</p> <p><strong>1.</strong> <strong>Valid Responses of the Questionnaire.xlsx </strong>comprises the 87 valid survey responses that were collected by sending the questionnaire to 1000 participants.</p> <p><strong>2. Interview Transcript </strong>includes eight files (Interview Transcript_IP1.docx - Interview Transcript_IP8.docx) of the interview transcripts from eight practitioners.</p> <p><strong>3. Data Labeling & Encoding.mx18 </strong>is the results of data labeling and encoding that were analyzed by the MAXQDA tool. We extracted the answers of open questions from the questionnaire and interview instrument, labeled them with the number of respondents and interviewees (e.g., Respondent1, Respondent2, Interview Transcript_IP1), and encoded the extracted data using Grounded Theory. The file can be opened by MAXQDA 18 or higher versions, which are available at https://www.maxqda.com/ for download. You may also use the free 14-day trial version of MAXQDA 2018, which is available at https://www.maxqda.com/trial for download.</p>
Dataset: Automatic Derivation of Vulnerability Models for Software Architectures
<p>Dataset for our publication "<em>Automatic Derivation of Vulnerability Models for Software Architectures</em>"</p>
Dataset for Thesis "Automated Consistency of Legal and Software Architecture System Specifications for Data Protection Analysis"
<p>Dataset for Thesis "Automated Consistency of Legal and Software Architecture System Specifications for Data Protection Analysis"</p>
Architectural Feature Re-Modularization for Software Product Line Evolution
<p>Extensive maintenance leads to the Software Product Line Architecture<br> (PLA) degradation over time. When there is the need of<br> evolving the Software Product Line (SPL) to include new features,<br> or move to a new platform, a degraded PLA requires considerable<br> effort to understand and modify, demanding expensive refactoring<br> activity. In the state of the art, search-based algorithms are used to<br> improve PLA at package level. However, recent studies have shown<br> that the most variability and implementation details of an SPL are<br> described in the level of classes. There is a gap between existing<br> approaches and existing practical needs. In this work, we extend<br> the current state of the art to deal with feature modularization in<br> the level of classes by introducing a new search operator and a set<br> of objective functions to deal with feature modularization in a finer<br> granularity of the architectural elements, namely at class level. We<br> evaluated the proposal in an exploratory study with a PLA widely<br> investigated and a real-world PLA. The results of quantitative and<br> qualitative analysis point out that our proposal provides solutions<br> to properly re-modularize features in a PLA, being preferred by<br> practitioners, in order to support the evolution of SPLs.</p>
Software Architecture Catalog for Fault-Tolerant Containerized Systems
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Software Architectures for New Generation Virtualization Infrastructures in Space
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Dataset: Attack Path Calculation for Software Architectures
<p>Non Anonymous Dataset for Attack Path Calculation for Software Architectures</p>
Exploring and Analyzing Software Architecture Refactoring in Practice
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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.