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111 results for “Integration Testing”
CATCH-EyoU: Exploiting European data and testing the integrated theory of youth active EU citizenship: EACEA subset analysis
<p>This dataset was created within the research project Constructing AcTive CitizensHip with European Youth: Policies, Practices, Challenges and Solutions (CATCH-EyoU) funded by European Union, Horizon 2020 Programme, Grant Agreement No 649538. Work Package 4 of this project (Exploiting European data and testing the integrated theory of youth active EU citizenship) is focused on the re-analysis of existing European data. This dataset contains a subset of data originally collected within the project “<em>EACEA 2010/03: Youth Participation in Democratic Life</em>”, coordinated by the London School of Economic and Political Science. Specifically, an online questionnaire survey in seven European countries was conducted among young people age 15-30 in 2011. This dataset contains a subset of 22 variables that were employed for the reanalysis within the CATCH-EyoU project.</p>
CATCH-EyoU: Exploiting European data and testing the integrated theory of youth active EU citizenship: PIDOP subset reanalysis
<p>This is a subset of the full PIDOP dataset. The derived subset contains cross-sectional survey results from the PIDOP questionnaire survey that were collected in 9 European countries (incl. Turkey) during a period of 16-26 year old in 2011. The data set includes 9060 individual cases. The questionnaire used in the survey is published in Barrett, M. & Zani, B. (Eds.) (2015). <em>Political and civic engagement: Multidisciplinary perspectives.</em> Hove: Routledge (p.519-534).</p>
Enhanced Westermo dataset - Transformed and Modified for Test case Selection and Priorotization in the context of Continuous Integration and Reinforcement Learning.
<p><strong>Overview</strong></p> <p>This repository contains a modified version of the existing, recently published dataset, Westermo. The initial dataset was gathered at Westermo Network Technologies AB, located in Västerås, Sweden. It encompasses over <strong>1 Million verdicts</strong> obtained from testing embedded systems, collected over a span of more than <strong>500 consecutive days</strong> of nightly testing. The dataset has been transformed and tailored specifically to cater to the research community, particularly for addressing challenges such as regression test selection, identification of flaky tests, and visualization of test results. The original dataset can be accessed through the reference provided in <strong>[1]</strong>.</p> <p>The Westermo dataset offers valuable historical information regarding the execution of test cases and their corresponding results. It serves as a valuable resource for evaluating and comparing different Test case Selection and Prioritization (TSP) techniques, enabling researchers to identify test cases that are more likely to fail during subsequent executions. Test cases in the dataset are characterized by attributes such as execution duration, previous last execution time, and the results of their recent executions.</p> <p>This dataset offers valuable historical information regarding the execution of test cases and their corresponding results. It serves as a valuable resource for evaluating and comparing different test case prioritization and selection techniques, enabling researchers to identify test cases that are more likely to fail during subsequent executions. Test cases in the dataset are characterized by attributes such as execution duration, previous last execution time, and the results of their recent executions.</p> <table align="left"> <caption><strong>Table 1: Dataset Overview</strong></caption> <tbody> <tr> <td>Test Cases</td> <td>1855</td> </tr> <tr> <td>CI Cycles</td> <td>15,197</td> </tr> <tr> <td>Verdict</td> <td>1,036,818</td> </tr> <tr> <td>Failed</td> <td>5.03%</td> </tr> </tbody> </table> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p>However, the diversity and multitude of the features in the dataset can be irrelevant to some TSP approaches. This led us to perform a dataset conversion, where we customized Westermo to have the same features from Paint Control and IOF/ROL, two widely used datasets in Reinforcement Learning based TSP approaches.</p> <p>This conversion required the combination of multiple variables and generating the target ones. When it comes to generating the “LastResults” and “Cycle” values, further analysis was required and the data handling needed an in-depth understanding of how the nightly testing was conducted. This led us to investigate what a CI cycle is in their context, and we followed their definition of a session, stating that “a session is when we run a suite of tests on one test system with a certain software version and testware version”. When splitting the data according to the 9 different systems used, we were able to generate 9 different sub-sets that fit the CI context.</p> <p> </p> <p><strong>File Format</strong></p> <p>The compressed .zip file contains 9 files, each one corresponding to each of the 9 systems. The datasets are available in CSV format, with the semicolon (;) serving as the delimiter. The columns included are represented in the table below along with their descriptions.</p> <table> <caption><strong>Table 2: Parameters of the dataset</strong></caption> <thead> <tr> <th scope="col">Column Name</th> <th scope="col">Content</th> </tr> </thead> <tbody> <tr> <td>Id</td> <td>Unique numeric identifier of the test execution </td> </tr> <tr> <td>Name</td> <td>Unique numeric identifier of the test case</td> </tr> <tr> <td>Duration</td> <td>Approximated runtime of the test case</td> </tr> <tr> <td>CalcPrio</td> <td>Priority of the test case, calculated by the prioritization algorithm (output column, initially 0)</td> </tr> <tr> <td>LastRun</td> <td>Previous last execution of the test case as date-time-string (Format: <em>YYYY-MM-DD HH:ii </em>)</td> </tr> <tr> <td>LastResults</td> <td>List of previous test results (Failed: 1, Passed: 0), ordered by ascending age. Lists are delimited by [ ].</td> </tr> <tr> <td>Verdict</td> <td> <p>Test verdict of this test execution (Failed: 1, Passed: 0)</p> </td> </tr> <tr> <td>Cycle</td> <td>The number of the CI cycle this test execution belongs to.</td> </tr> </tbody> </table> <p> </p> <p>The implications of this conversion are important as it can help the previous works to re-assess their approaches and have more data for training and testing, as well as opening a broader data spectrum for future researchers in this field to find ready-to-use, rich datasets, on which they could evaluate their approaches and contribute to the TSP community. This also addresses the limitations in the field discussed in the systematic literature review <strong>[2]</strong>, stating that future research on TSP techniques should focus on collecting data from more recent subjects in a CI context with varying failure rates and larger execution times, as reproducible studies with appropriate datasets are needed to develop a usable body of knowledge regarding TSP over time. We believe that this conversion of the Westermo dataset is our contribution to alleviating the gap for the RL-based approaches.</p> <p>The original dataset can be found <a href="https://sites.mdu.se/aidoart/results/open-source/test-results-dataset-westermo">here.</a></p>
An Empirical Study of Activity, Popularity, Size, Testing, and Stability in Continuous Integration
<p>A good understanding of the practices followed by software development projects can positively impact their success --- particularly for attracting talent and on-boarding new members. In this paper, we perform a cluster analysis to classify software projects that follow continuous integration in terms of their activity, popularity, size, testing, and stability. Based on this analysis, we identify and discuss four different groups of repositories that have distinct characteristics that separates them from the other groups. With this new understanding, we encourage open source projects to acknowledge and advertise their preferences according to these defining characteristics, so that they can recruit developers who share similar values.</p>
SherpaTT Integration Test Bremen
<p>Data recorded from SherpaTT. The logs have been recorded during a short integration test of SherpaTT and HCRU.</p>
Dataset for Understanding and Improving Regression Test Selection in Continuous Integration
<p>This is the dataset for the paper "Understanding and Improving Regression Test Selection in Continuous Integration". The dataset consists of the logs collected from running RTS tools on Travis CI along with a CSV summary of those results.</p>
Investigating Multi and Many-Objective Metaheuristics to Support Software Integration Testing
<p> In spite of the fact that Search-Based Software Testing (SBST) is a very appealing field today, there are few studies that deal with software integration testing and, even so, most of these works are not truly related to the generation of test cases to this testing level. In this paper, we present a method, InMeHy, which aims at investigating the use of metaheuristics to derive integration test cases based on C++ source code. A graph is created based on the code which represents the integration of several classes of the application. Multi and Many-Objective metaheuristics (Evolutionary Algorithms) were considered to generate integration test cases and were assessed via three quality indicators. Results show that the traditional Indicator-Based Evolutionary Algorithm (IBEA) turned out to be the best out of four algorithms evaluated, including newer Many-Objective strategies such as Nondominated Sorting Genetic Algorithm-III (NSGA-III).</p>
Learning by Viewing: Generating Test Inputs for Games by Integrating Human Gameplay Traces in Neuroevolution
<p>Replication package for the paper "Learning by Viewing: Generating Test Inputs for Games by Integrating Human Gameplay Traces in Neuroevolution" </p><p> </p><p>Although automated test generation is common in many programming domains, games still challenge test generators due to their heavy randomisation and hard-to-reach program states. Neuroevolution combined with search-based software testing principles has been shown to be a promising approach for testing games, but the co-evolutionary search for optimal network topologies and weights involves unreasonably long search durations. Humans, on the other hand, tend to be quick in picking up basic gameplay. In this paper, we therefore aim to improve the evolutionary search for game input generators by integrating knowledge about human gameplay behaviour. To this end, we propose a novel way of systematically recording human gameplay traces, and integrating these traces into the evolutionary search for networks using traditional gradient descent as a mutation operator. Experiments conducted on eight diverse Scratch games demonstrate that the proposed approach reduces the required search time from five hours down to only 30 minutes on average.</p>
Optimizing Continuous Integration by Dynamic Test Selection
<p>Continuous integration (CI) is widely used in modern software engineering. However, it is an expensive practice. Some proposed approaches only focus on either intra- or inter-build cost reduction. In this paper, we propose an adaptive technique for dynamic test selection DTS, which combines intra- and inter-build cost reduction techniques. DTS uses build features to construct machine learning models to predict the probability of a specific build failure and transform the probability into the necessary test proportion, with respect to a selected test case prioritization technique. Based on the output of prediction model, it thus selects a prioritized test suite and a variable proportion of test cases with respect to a build. We constructed a large-scale dataset with approximately 115,000 builds, and conducted a controlled experiment using the dataset. The experiment shows that DTS outperforms existing techniques significantly. It detects 19.9% to 32.5% more failed test cases, compared with state-of-the-art techniques evaluated in the experiment. At the same time, DTS performs better than all three existing peer techniques on approximately 47% of projects. Moreover, the experiment also shows that our failure prediction model has an improvement of 0.15 in Area Under Curve (AUC), compared to prior machine learning models.</p>
An integrated framework for analysing, simulating and testing UML models
<h1>Project Overview</h1> <p>This is the artefact associated with the paper "An integrated framework for analysing, simulating and testing UML models", submitted to the 27th Brazilian Symposium on Formal Methods (SBMF 2024).</p> <h2>Directory Structure</h2> <ul> <li><strong>CSP_Validation</strong>: Contains the validation of our mapping rules from UML diagrams to CNL requirements.</li> <li><strong>NAT2TEST_Projects</strong>: Contains the NAT2TEST projects for two case studies: the classical Dijkstra's dining philosophers problem, and a distributed ring-buffer model.</li> <li><strong>UML2CNL</strong>: Contains the implementation of our mapping rules from UML diagrams to CNL requirements.</li> </ul>
Testing an Integrated Bio-Behavioral Primary HIV Prevention Intervention Among High-Risk People Who Use Drugs
ClinicalTrials.gov study NCT03282890. IPD Sharing: NO. Countries: 1. Publications: 11.
Grandi Byen: Test of an Integrated Parenting and Nutrition Intervention
ClinicalTrials.gov study NCT04785352. IPD Sharing: YES. Countries: 1. Publications: 1.
Testing the Integrated mHealth App Intervention "SiS-H"
ClinicalTrials.gov study NCT05886621. IPD Sharing: Not stated. Countries: 1. Publications: 9.
15-gene expression profile and PRAME as an integrated prognostic test for uveal melanoma: First report of Collaborative Ocular Oncology Group Study No. 2 (COOG2.1)
Open the record for dataset details and reuse information.
Data from: Testing models of reciprocal relations between social influence and integration in STEM across the college years
<p class="CxSpFirst">The present study tests predictions from the Tripartite Integration Model of Social Influences (TIMSI) concerning processes linking social interactions to social integration into science, technology, engineering, and mathematics (STEM) communities and careers. Students from historically overrepresented groups in STEM were followed from their senior year of high school through their senior year in college. Based on TIMSI, we hypothesized that interactions with social influence agents (operationalized as mentor network diversity, faculty mentor support, and research experiences) would promote both short- and long-term integration into STEM via social influence processes (operationalized as science self-efficacy, identity, and internalized community values). Moreover, we examined the previously untested hypothesis of reciprocal influences from early levels of social integration in STEM to future engagement with social influence agents. Results of a series of longitudinal structural equation model-based mediation analyses indicate that, in the short term, higher levels of faculty mentorship support and research engagement, and to a lesser degree more diverse mentor networks in college promote deeper integration into the STEM community through the development of science identity and science community values. Moreover, results indicate that, in the long term, earlier high levels of integration in STEM indirectly influences research engagement through the development of higher science identity. These results extend our understanding of the TIMSI framework and advance our understanding of the reciprocal nature of social influences that draw students into STEM careers.</p>
Integrating QSAR models predicting acute contact toxicity and mode of action profiling in honey bees (A. mellifera): Data curation using open source databases, performance testing and validation
<p>This excel file (DOI: <a href="https://doi.org/10.5281/zenodo.3755675">https://doi.org/10.5281/zenodo.3755675</a>) provides the collection of raw data used for developing the first integrative Quantitative Structure-Activity Relationship (QSAR) model using EFSA's OpenFoodTox, US-EPA ECOTOX and Pesticide Properties DataBase i) to predict acute contact toxicity (LD<sub>50</sub>) and ii) to profile the Mode of Action (MoA) of pesticides active substances in honey bees (<em>Apis mellifera</em>)<em>. </em>Chemical identifiers (e.g. SMILES, CAS n., InChI) and acute contact toxicity data (LD<sub>50</sub>) on honey bees were used to develop and validate i) a two-category QSAR model (toxic/non-toxic; n=411) (sensitivity =0.93), specificity =0.85), balanced accuracy =0.90), Matthews correlation coefficient MCC=0.78), and ii) a regression-based model (n=113) (R2=0.74; MAE=0.52). Similarly, current study proposes the first MoA profiling for 113 pesticides active substances and the first harmonised MoA classification scheme for acute contact toxicity in honey bees, including LD<sub>50s</sub> data points from three different databases such as EFSA's OpenFoodTox, US-EPA ECOTOX and Pesticide Properties DataBase. Such classification allows to further define MoAs and the target site of Plant Protection Products (PPPs) active substances, thus enabling regulators and scientists to refine chemical grouping and toxicity extrapolations for single chemicals and component-based mixture risk assessment of multiple chemicals.</p> <p>The full data collection and analysis of QSAR models, toxicity data (LD<sub>50</sub>) and Mode of Action (Moa) data are described in Carnesecchi et al., 2020 (DOI: doi.org/10.1016/j.scitotenv.2020.139243).</p> <p>This work was supported by the European Food Safety Authority (EFSA) [contract number: OC/EFSA/SCER/2018/01 and NP/EFSA/AFSCO/2016/02 (Edoardo Carnesecchi)].</p>
Replication package for "An Industrial Study on the Challenges and Effects of Diversity-based Testing in Continuous Integration"
<p>This is the replication package for the analysis done in the paper "An Industrial Study on the Challenges and Effects of Diversity-based Testing in Continuous Integration".</p> <p>The package includes: (i) CSV files with data on test case and corresponding feature coverage, as well as test execution data; (ii) CSV files including failure coverage for the executed techniques; (iii) R scripts to re-run our visual and statistical analysis when comparing techniques results; and (iv) An R Markdown file (rendered into HTML) detailing the steps of our analysis with the coresponding code.</p>
Data from: Tests of species-specific models reveal the importance of drought in postglacial range shifts of a Mediterranean-climate tree: insights from integrative distributional, demographic and coalescent modelling and ABC model selection
Past climate change has caused shifts in species distributions and undoubtedly impacted patterns of genetic variation, but the biological processes mediating responses to climate change, and their genetic signatures, are often poorly understood. We test six species-specific biologically informed hypotheses about such processes in canyon live oak (Quercus chrysolepis) from the California Floristic Province. These hypotheses encompass the potential roles of climatic niche, niche multidimensionality, physiological trade-offs in functional traits, and local-scale factors (microsites and local adaptation within ecoregions) in structuring genetic variation. Specifically, we use ecological niche models (ENMs) to construct temporally dynamic landscapes where the processes invoked by each hypothesis are reflected by differences in local habitat suitabilities. These landscapes are used to simulate expected patterns of genetic variation under each model and evaluate the fit of empirical data from 13 microsatellite loci genotyped in 226 individuals from across the species range. Using approximate Bayesian computation (ABC), we obtain very strong support for two statistically indistinguishable models: a trade-off model in which growth rate and drought tolerance drive habitat suitability and genetic structure, and a model based on the climatic niche estimated from a generic ENM, in which the variables found to make the most important contribution to the ENM have strong conceptual links to drought stress. The two most probable models for explaining the patterns of genetic variation thus share a common component, highlighting the potential importance of seasonal drought in driving historical range shifts in a temperate tree from a Mediterranean climate where summer drought is common.
Supplementary Data for "Exploring the Integration of Large Language Models in Industrial Test Maintenance Processes"
<p>This package contains supplementary data not directly included in the paper, including per-commit results for each prototype and the prompts used in the proof-of-concept implementations.</p>
Figure 1 in Figure 5 in On the Integrity of Online Testing for Introductory Statistics Courses: A Latent Variable Approach
Figure 1 The kinship amcnS individuals cf three matrilineal units within trccp WW-1. The ciocles oepoesent cemales and squaoes oepoesent males. Matoilineal units: HL, honglian unit; CM, changmao unit; BD, bandian unit.
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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.