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21 results for “quality attribute”
Water quality and watershed attributes of 41 Pampean streams in Argentina, 12 years later (2003-2015).
This database consists of water chemistry (pH, conductivity, dissolved oxygen, nutrients, and carbonates) and catchment attributes for 41 streams of Buenos Aires province, Argentina. Water quality was measured in 2003/4 and 12 years later (2015/16). Sampling were made in May (autumn), November (spring), and February (summer) at baseflow condition. Some physico-chemical parameters were measured in situ. Parameters determined at laboratory were nutrients and salts. And catchment attributes were determined (physiographic parameters, land use, soil type and geology).
Appendices of the work "On the perceived relevance of critical internal quality attributes when evolving software features"
<p>Several refactorings performed while evolving software features aim to improve internal quality attributes like cohesion and complexity. Studies show that non-assisted refactorings might worsen, not improve, internal attributes. Current knowledge is scarce on how developers perceive the relevance of critical internal attributes while evolving features. Internal attributes are critical if their measurement assumes anomalous values. This qualitative study investigates the developer's perception on the relevance of critical internal attributes when evolving features. We target six class-level critical attributes: low cohesion, high complexity, high coupling, large hierarchy depth, large hierarchy breadth, and large size. We performed two industry case studies based on online focus group sessions. Developers discussed how much (and why) critical attributes are relevant for adding or enhancing features. We assessed the relevance of critical attributes individually and relatively, reasons behind the relevance of each critical attribute, and interrelations of critical attributes. Low cohesion and high complexity were perceived as very relevant because they often make evolving features hard while tracking failures and adding features. The other critical attributes were perceived as less relevant when reusing code or adopting design patterns. An example of perceived interrelation is high complexity leading to high coupling.</p>
Appendices of the work "On the perceived relevance of critical internal quality attributes when evolving software features"
<p>Several refactorings performed while evolving software features aim to improve internal quality attributes like cohesion and complexity. Studies show that non-assisted refactorings might worsen, not improve, internal attributes. Current knowledge is scarce on how developers perceive the relevance of critical internal attributes while evolving features. Internal attributes are critical if their measurement assumes anomalous values. This qualitative study investigates the developer's perception on the relevance of critical internal attributes when evolving features. We target six class-level critical attributes: low cohesion, high complexity, high coupling, large hierarchy depth, large hierarchy breadth, and large size. We performed two industry case studies based on online focus group sessions. Developers discussed how much (and why) critical attributes are relevant for adding or enhancing features. We assessed the relevance of critical attributes individually and relatively, reasons behind the relevance of each critical attribute, and interrelations of critical attributes. Low cohesion and high complexity were perceived as very relevant because they often make evolving features hard while tracking failures and adding features. The other critical attributes were perceived as less relevant when reusing code or adopting design patterns. An example of perceived interrelation is high complexity leading to high coupling.</p>
Appendices of the work "On the perceived relevance of critical internal quality attributes when evolving software features"
<p><strong>Context:</strong> Several refactorings performed while evolving software features aim to improve internal quality attributes like cohesion and complexity. Studies shows that non-assisted refactorings might worsen, not improve, internal attributes. Current knowledge is scarce on how developers perceive the relevance of critical internal attributes while evolving features. Internal attributes are critical if their measurement assumes anomalous values. <strong>Objective:</strong> This qualitative study aims at revealing the developer's perception on the relevance of critical internal attributes when evolving features. We target six class-level critical attributes: low cohesion, high complexity, high coupling, large hierarchy depth, large hierarchy breadth, and large size. <strong>Method:</strong> We performed two industry case studies based on online focus group sessions. We asked developers to discuss how much (and why) critical attributes are relevant for adding or enhancing features. We assessed the relevance of critical attributes individually and relatively, reasons behind the relevance of each critical attribute, and interrelations of critical attributes. <strong>Results:</strong> Low cohesion and high complexity were perceived as very relevant because they often make evolving features hard while tracking failures and adding features. The other critical attributes were perceived as less relevant when reusing code or adopting design patterns, for instance. Examples of interrelations include large size leads to low cohesion and high complexity leads to high coupling. <strong>Conclusions:</strong> Our findings could be combined with previous results on how refactorings affect quality attributes to assist developers in applying refactorings that may have a practically relevant impact on critical attributes.</p>
Predicting particle quality attributes of organic crystalline materials using Particle Informatics
<p>Dataset related to the publication: "Predicting particle quality attributes of organic crystalline materials using Particle Informatics" published in Powder Technology (<a title="Go to table of contents for this volume/issue" href="https://www.sciencedirect.com/journal/powder-technology/vol/443/suppl/C"><span>Volume 443</span></a>, 1 July 2024, 119927Volume 443, 1 July 2024, 119927). In this work, a novel quercetin solvate of dimethylformamide (QDMF) was studied. The crystal structure was solved using single crystal X-ray diffraction and analysed using synthon analysis and other particle informatics tools (<em>e.g.</em>, solvate analyser). The thermal behaviour and thermodynamic stability of QDMF were studied experimentally using Raman spectroscopy, ATR-FTIR spectroscopy, differential scanning calorimetry, and thermogravimetric analysis. A clear relationship between the two-step desolvation behaviour of QDMF and the type, strength, and directionality of the main bulk synthons characterizing the QDMF structure was observed. Additionally, the attachment energy model was used to predict the QDMF morphology, together with facet-specific topology and chemical nature of each of the dominant {001}, {110}, and {200} facets. The {200} facet was found to be significantly rougher than the other two; whereas, the {110} was characterized by a higher percentage of exposed DMF molecules compared to the other two facets. Specific scanning electron microscopy and contact angle measurements were used to experimentally detect differences among the three facets and validate the modelling results.</p>
Defining Categorical Reasoning of Numerical Feature Models with Feature-Wise and Variant-Wise Quality Attributes
<p><strong>To watch it in Youtube:</strong></p> <p><a href="https://youtu.be/Uq2qtb4_K2U">https://youtu.be/Uq2qtb4_K2U</a></p> <p><strong>This is a pre-print, please access and cite the published version:</strong></p> <p><a href="https://doi.org/10.1145/3503229.3547057">https://doi.org/10.1145/3503229.3547057</a></p> <p>Automatic analysis of variability is an important stage of <em>Software Product Line</em> (SPL) engineering. Incorporating quality information into this stage poses a significant challenge. However, quality-aware automated analysis tools are rare, mainly because in existing solutions variability and quality information are not unified under the same model.</p> <p>In this paper, we make use of the <em>Quality Variability Model</em> (QVM), based on <em>Category Theory</em> (CT), to redefine reasoning operations. We start defining and composing the six most common operations in SPL, but now as quality-based queries, which tend to be unavailable in other approaches. Consequently, QVM supports interactions between variant-wise and feature-wise quality attributes. As a proof of concept, we present, implement and execute the operations as lambda reasoning for CQL IDE -- the state-of-the-art CT tool.</p>
Quality Attributes Assessment in Self-Adaptive Systems: An Empirical Evaluation
<p>Self-adaptive Systems (SAS) can monitor themselves and their context. They can detect changes and react to unexpected conditions with minimal human supervision during their execution. One of the challenges behind developing SAS is dealing with the decision-making process while analyzing the tradeoff points among the multiple quality attributes (QA). In Software Engineering, a widely accepted method of evaluating QA goals in software projects is the Architecture Tradeoff Analysis Method (ATAM). However, despite its importance and wide acceptance, there are few reports of empirical studies on analyzing QA tradeoffs in SAS. In this sense, the present investigation proposes an adapted version of ATAM called ATAM-4SAS to deal with the particularities of SAS. To achieve the research goal, we employed the UPPAAL SMC (statistical verification model) to analyze a set of QA. To evaluate the feasibility of the proposed method, we performed an empirical study on the execution of the ATAM-4SAS in a SAS developed according to the MAPE-K model. This model encompasses the Monitoring, Analysis, Planning, and Execution phases. Such steps share a knowledge base (K), which is fundamental in supporting decision-making. We complemented the empirical evaluation by conducting a focus group, which sought to assess the perceived ease of use and the perceived usefulness of the ATAM-4SAS to support the strategic choice of QA in a SAS. As a result, we observed that most participants agreed that ATAM-4SAS provides adequate support for the strategic choice of QA in SAS.</p>
Air quality source attribution and scenario analysis in the UNECE region
<p>The dataset contains the metrics of PM2.5 and ozone exposure in the UNECE region attributed to 13 activity sectors in three different ECLIPSE v6b emission scenarios (CLE BASE, MFR-BASE and SDS-MFR) used by the authors in the publication "Air quality and related health impact in the UNECE region: source attribution and scenario analysis" submitted to the Journal Atmospheric Chemistry and Physics (https://doi.org/10.5194/acp-2022-776).</p>
Analyzing App Store Comments and Quality Attributes for Defining an Inspection Checklist for Mobile Educational Games
<p>To evaluate educational games, several techniques have been proposed considering different quality attributes. However, there are still several educational games for the mobile context that have low scores in the app stores. These stores allow users to make comments to evaluate the applications, as this data can be useful for the development team that aims to meet users' expectations. The analysis of comments made by users can help identify which attributes impact the use of mobile educational games. In this paper, an inspection checklist is proposed to evaluate mobile educational games. To complement the attributes identified in the analysis of comments, attributes from existing techniques for evaluating mobile educational games were also considered. The final evaluation form contains a total of 82 attributes distributed in evaluation categories, such as: user interface, mobility, pedagogy, gameplay, among others. To evaluate the proposed technique, an evaluation was carried out with the checklist in two mobile educational games available in the Google Play Store, different from those used to define the technique. The initial results indicate that the proposed checklist allows the identification of problems pointed out by users in the comments left in the app store.</p> <p> </p> <p><a href="https://zenodo.org/api/files/8ca1af4d-6f7c-440f-a272-9366de2ad3ef/SBES%202020%20-%20Ideias%20Inovadoras%20e%20Resultados%20Emergentes%20-%20Analisando%20atributos%20de%20qualidade%20e%20coment%C3%A1rios%20de%20lojas%20de%20aplicativos%20para%20a%20defini%C3%A7%C3%A3o%20de%20uma%20t%C3%A9cnica%20de%20inspe%C3%A7%C3%A3o%20de%20jogos%20educacionais%20m%C3%B3veis.mp4">SBES 2020 - Ideias Inovadoras e Resultados Emergentes</a></p>
A compendium and evaluation of taxonomy quality attributes
<p>This dataset contains the following data and source code and results.</p> <ul> <li>The definition of taxonomy quality attributes from Szopinski et al. and Usman et al. (szopinski_usman_analysis.xls)</li> <li>The results of the data extraction validation (data_extraction_validation.xls)</li> <li>The implementations of the robustness and conciseness measures (source_code.zip). Unpack also the model files in doc2vec_model.zip.</li> <li>The results of the taxonomy analysis (results_qualitative_attributes.xls and conciseness_robustness_results.zip)</li> <li>Detailed results of intruder nodes, calculated for the robustness measure (intruder_node_details.zip)</li> </ul>
Impact of four inorganic impurities – iron, copper, nickel and zinc - on the quality attributes of a Fc-fusion protein upon incubation at different temperatures.
<p>Data regarding the impact of four inorganic impurities – iron, copper, nickel and zinc - on the quality attributes of a Fc-fusion protein upon incubation at different temperatures. </p>
The rehydration attributes and quality characteristics of 'Quick-cooking' dehydrated beans: Implications of glass transition on storage stability
<p>The data set was used to generate the figures.</p>
Supplemental Material: Effects of Environmental Sustainability Enhancing Architectural Patterns and Tactics on different Quality Attributes
<p>These are the additional resources to the thesis with the same title.</p> <p>Context: Environmental sustainability is increasingly vital amid global challenges,<br>as IT presents both solutions and threats to the environment. Integrating environ-<br>mental sustainability into software engineering practices is essential, necessitating a<br>comprehensive understanding of environmental sustainability design decisions and<br>how they impact sustainability and other quality attributes within software architec-<br>tures.<br>Objectives: This research aims to address two primary objectives: firstly, to elicit environ-<br>mental sustainability scenarios and patterns and tactics from domain experts, and secondly,<br>to assess the tradeoffs of these design decisions in the context of a case study. Through qual-<br>itative insights garnered from a workshop and quantitative analysis via experiments, this<br>study seeks to offer nuanced insights into these tradeoffs.<br>Methodology: Utilizing a case study approach in collaboration with an industrial partner,<br>this work employs a combination of qualitative and quantitative analysis methods.<br>Qualitative insights are gathered through an Architecture Tradeoff Analysis Method<br>(ATAM) workshop with industrial partners, aimed at eliciting environmental sustainability<br>scenarios, design decisions, and their tradeoffs. Afterward, quantitative experiments<br>are conducted based on the workshop results using the Goal-Question-Metric (GQM)<br>approach, to measure the impact of environmental sustainability design decisions on<br>specific quality attributes in a mock implementation based on the industrial partner’s<br>system.<br>Results: We were able to capture eight environmental sustainability scenarios and<br>patterns and tactics and tradeoffs for five of them during the workshop. In the ex-<br>periments we implemented two tactics, expecting them to negatively impact the per-<br>formance. The experimentation provided empirical data, revealing nuanced insights,<br>sometimes contradicting initial hypotheses, highlighting the importance of empirical<br>validation.<br>Conclusion: This study underscores the complexity of balancing environmental sustain-<br>ability with other quality attributes in software design. It emphasizes the complementary<br>role of qualitative and quantitative analysis in understanding tradeoffs and making informed<br>decisions. By integrating insights from both approaches, this research contributes to ad-<br>vancing discussions on sustainability in software engineering, benefiting both researchers<br>and practitioners. Continued collaboration between academia and industry is crucial for<br>furthering sustainable software engineering practices.</p> <p> </p>
The Impact of Drying and Rehydration on the Structural Properties and Quality Attributes of Pre-Cooked Dried Beans
<p>The data used for the figures of the journal article is uploaded here.</p>
Validating and Confirming Crucial Service Quality Attributes to Airline Customers' Recommendations: A Feature Selection Approach
Open the record for dataset details and reuse information.
Dataset Characterizing Architectural Evaluations and Identifying Quality Attributes addressed in Systems-of-Systems: A Systematic Mapping Study
<p>Dataset</p>
Appendix Characterizing Architectural Evaluations and Identifying Quality Attributes addressed in Systems-of-Systems: A Systematic Mapping Study
<p>Data analysis.</p>
Data Repository for "Integrating Water Quality Data with a Bayesian Network Model to Improve Spatial and Temporal Phosphorus Attribution: Application to the Maumee River Basin"
<p>Data for "Integrating Water Quality Data with a Bayesian Network Model to Improve Spatial and Temporal Phosphorus Attribution: Application to the Maumee River Basin". This repository contains all the processed data used in the simulation (in "processed" folder), part of the raw data (in "raw" folder), and the SWAT simulation results (in "SWAT" folder). The code for processing the raw data, which are either provided here or publicly available online, is provided in the <a href="https://doi.org/10.5281/zenodo.8132662">code repository</a>. The links to the publicly available raw data are also provided in the code repository.</p>
A Study to Evaluate The Impact on Skin Quality Attributes by Juvederm® Volite Injection on Healthy Volunteers
ClinicalTrials.gov study NCT04206293. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Development of a Multi-attribute Health Index: to Measure the Quality of Labour Analgesia: The QLA Index
ClinicalTrials.gov study NCT01177046. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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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.
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DANDI Archive for NWB datasets
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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.