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22 results for “program understanding”
Data from “A Mixed Method Approach to Understanding the Public Health Impact of a School-Based Citizen Science Program to Reduce Arsenic in Private Well Water”
Objectives We have approached the problem of low well water testing rates in Maine and New Hampshire communities by developing the All About Arsenic (AAA) project, which engages secondary school teachers and students as citizen scientists in collecting well water samples for analysis of arsenic and other toxic metals and supports their outreach efforts to their communities. Methods We assessed this project’s public health impact by analyzing student data relative to existing well water quality datasets in both states. In addition, we surveyed private well owners who contributed well water samples to the project to determine the actions taken to mitigate arsenic in well water. Data The data presented here are used in the analyses performed for the publication: "A Mixed Method Approach to Understanding the Public Health Impact of a School-Based Citizen Science Program to Reduce Arsenic in Private Well Water.” Additional data may be available at: The Anecdata Project Page: https://anecdata.org/projects/view/299 The project website: https://www.allaboutarsenic.org/
The dataset of the APSEC'20 paper titled "Understanding the Non-Repairability Factors of Automated Program Repair Techniques"
<p>The file <strong>ExecutionLogs.zip</strong> includes all execution logs that we take into consideration in the study. </p> <p>The file <strong>Exception_Statistics.xlsx</strong> includes the distribution of each type of exception in our study. </p> <p> </p> <p>All logs are located in directories that are named by fault localization strategy and the corresponding automated program repair tool. Specifically, in the directories of <strong>ExecutionLogs</strong> there are four sub-directories: <em>GZ-0.1</em>, <em>GZ-1.7</em>, <em>No_FL_Required</em>, and <em>Perfect_FL</em>.</p> <ul> <li><em>GZ-0.1</em> means fault localization strategy with GZoltar-v0.1 (from the <a href="https://dl.acm.org/doi/10.1145/3338906.3338911">FSE19</a> paper).</li> <li><em>GZ-1.7</em> means fault localization strategy with GZoltar-v1.7 (from the <a href="https://zenodo.org/record/3678960#.XwcRNIgzaUk">ICSE20</a> paper).</li> <li><em>Perfect_FL</em> means directly feeding ground-truth bug positions to APR tools (from the <a href="https://zenodo.org/record/3678960#.XwcRNIgzaUk">ICSE20</a> paper).</li> <li><em>No_FL_Required</em> means that the tool does not require fault localization process (from <a href="https://dl.acm.org/doi/10.1145/3338906.3338911">FSE19</a> paper).</li> </ul> <p>For example, the log of bug <em>Chart-1</em> generated by <em>Cardumen</em> with <em>Gzoltar-0.1</em> are stored in the directory <strong>GZ-0.1/Chart/1/Cardumen/</strong>. </p> <p> </p> <p>In the file <strong>Exception_Statistics.xlsx</strong>, we demonstrate the detailed distribution of each type of exception.</p> <p><strong>Format of the content</strong></p> <p>We use format like <em>Fault_localization_strategy-project_id-version_id-tool_name</em> to represent each log.</p> <p>Take <em>GZ0.1-Chart-1-Cardumen</em> as an example, this log is generated by <em>Cardumen</em> on bug <em>Chart-1</em> with fault localization strategy <em>GZoltar-v0.1</em>.</p> <p><strong>About compliance level</strong></p> <p>Take the log of <em>GZ0.1-Mockito-1-Cardumen</em> as an example. We can get the compliance level from the parameter <em>javacompliancelevel</em>. For example, 4 corresponds to java 1.4, 5 corresponds to java 1.5 and so on. Hence, we can know what compliance level authors used during the original experiment.</p> <pre><code class="language-java">time java -Xmx4048m -cp /home/tdurieux/RepairThemAll/script/../libs/jtestex7.jar:/home/tdurieux/RepairThemAll/script/../repair_tools/astor.jar fr.inria.main.evolution.AstorMain \ -mode cardumen \ -location . \ -id Chart-1 \ -failing org.jfree.chart.renderer.category.junit.AbstractCategoryItemRendererTests \ -jvm4testexecution /home/tdurieux/openjdk-1.7.0/bin/ \ -jvm4evosuitetestexecution /home/tdurieux/openjdk-1.7.0/bin/ \ -maxgen 1000000 \ -maxtime 120 \ -stopfirst true \ -seed 0 \ -scope local \ -population 1 \ -javacompliancelevel 4 \ ......</code></pre> <p><strong>About the server</strong></p> <p>In the end of each log, it illustrates the brief information about the cloud node. Hence, we can know which logs are from the same node.</p> <pre><code class="language-java">...... Node: suno-2.sophia.grid5000.fr Date: Fri Dec 28 21:21:00 EST 2018</code></pre> <p>We next give introduction to the omitted three types of exceptions in the paper.</p> <ul> <li><strong>NumberFormat exception</strong></li> </ul> <p>Below is an example of this type of exception. As we have mentioned in the paper, due to the impossibility of integrating GZoltar-v1.7 into APR tools, researchers choose to read the FL results from independent files. From the content of the log, Astor needs to get suspicious line numbers during initialization (executing <em>createEngine</em>) but triggers an exception. This exception only occurs for Closure-76 and we have confirmed with the authors of reference[9] that it is due to the wrong content of the input file. We thus categorized it into <strong>Improper operation of replication study</strong>.</p> <pre><code class="language-java">Exception in thread "main" java.lang.NumberFormatException: For input string: "" at java.lang.NumberFormatException.forInputString(NumberFormatException.java:65) at java.lang.Integer.parseInt(Integer.java:592) at java.lang.Integer.parseInt(Integer.java:615) at fr.inria.main.evolution.AstorMain.createEngine(AstorMain.java:172) at ......</code></pre> <ul> <li><strong>IO exception</strong></li> </ul> <p>During the experiment, the generated output files (i.e., the execution logs and the generated patches) can sometimes be more than 10 trillions of bites. Meanwhile, the system may generate and store abundant template files such as the variants of the buggy program. If there is not enough space left on the machine, the execution logs will not be outputted successfully and an IO exception will occur as shown below. This indicates that these exceptions may not occur if the template files can be cleaned in time. We thus classified this type into <strong>Improper operation of replication study</strong> in that researchers ignore the storage state of the machine.</p> <pre><code class="language-java">Exception in thread "main" java.lang.RuntimeException: java.io.IOException: No space left on device at fr.inria.astor.core.setup.ProjectRepairFacade.setupWorkingDirectories(ProjectRepairFacade.java:46) at fr.inria.main.evolution.AstorMain.initProject(AstorMain.java:61) at fr.inria.main.evolution.AstorMain.run(AstorMain.java:239)</code></pre> <ul> <li><strong>NoClassDefFound exception</strong></li> </ul> <p>An example of this type of exception is illustrated below. We failed to reproduce this exception in our own machine. We further tried the docker file provided in the project page of reference[8] but still did not succeed. We noted that the experiment in reference[8] was performed on cloud instances whose experimental environment may be unstable. Bugs that throw this exception are consecutive (i.e., the IDs of these bugs are consecutive which are from Math 39 to Math 52 in the Defects4J benchmark), which further confirms our hypothesis that the environment might be problematic during these executions. We thus categorized this type into <strong>Unstable environment</strong>.</p> <pre><code class="language-java">Exception in thread "main" java.lang.NoClassDefFoundError: com/gzoltar/core/spectra/Spectra at com.gzoltar.core.GZoltar.run(GZoltar.java:50) at us.msu.cse.repair.core.faultlocalizer.GZoltarFaultLocalizer.<init>(GZoltarFaultLocalizer.java:42) at us.msu.cse.repair.core.AbstractRepairProblem.invokeFaultLocalizer(AbstractRepairProblem.java:298) at us.msu.cse.repair.core.AbstractRepairProblem.invokeModules(AbstractRepairProblem.java:269) at us.msu.cse.repair.core.AbstractRepairProblem.<init>(AbstractRepairProblem.java:244) at us.msu.cse.repair.algorithms.kali.Kali.<init>(Kali.java:37) at ......</code></pre> <p> </p>
Understanding challenges of GPU programming by classifying and analyzing Stack Overflow posts
<p>This dataset includes a dataset of posts related to GPU programming and supplemental materials including the complete analyzed results of our paper "Understanding challenges of GPU programming by classifying and analyzing Stack Overflow posts".</p>
Understanding the Impact of School-Based Physical Activity Programs
ClinicalTrials.gov study NCT02810834. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Financial Navigation Program to Improve Understanding and Management of Financial Aspects of Cancer Care for Patients and Their Spouses
ClinicalTrials.gov study NCT04960787. IPD Sharing: Not stated. Countries: 2. Publications: 0.
Understanding Your Baby: A Parallel Group Study of a Universal Parenting Support Program
ClinicalTrials.gov study NCT03991416. IPD Sharing: NO. Countries: 1. Publications: 1.
Understanding the Need and Feasibility of Transitional Care Training Program Among Family Caregivers of Geriatric Stroke Survivors in Pakistan
ClinicalTrials.gov study NCT06341881. IPD Sharing: YES. Countries: 1. Publications: 12.
Program for Fully Understanding Eating and Lifestyle Change (FUEL)
ClinicalTrials.gov study NCT05562427. IPD Sharing: NO. Countries: 1. Publications: 1.
Replication Package for "Improving Programming Education Through SonarQube: A Multiple Empirical Study of How Students Understand Rule Violations, Perceive the Criticality of the Rule, and the Fixing Difficulty"
Open the record for dataset details and reuse information.
Scenario Tailored Opioid Messaging Program (STOMP) to Improve Risk Understanding in Young Adults
ClinicalTrials.gov study NCT03863353. IPD Sharing: NO. Countries: 1. Publications: 0.
Deplin® P.L.U.S. Program (Progress Through Learning Understanding & Support)
ClinicalTrials.gov study NCT01369030. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Achieving Health in Emerging Adults With Diabetes (AHEAD) Program: A Clinical Trial Designed to Understand if Participation in a Clinical Program Developed Specifically to Support Emerging Adults With
ClinicalTrials.gov study NCT07292558. IPD Sharing: YES. Countries: 1. Publications: 0.
Understanding the fate of the hungry caterpillar: Transcriptional and DNA methylation programs during metamorphosis of the butterfly Bicyclus anynana (RNA-Seq).
GEO Series GSE276477. Bicyclus anynana. 15 samples. Type: Expression profiling by high throughput sequencing.
Understanding the fate of the hungry caterpillar: Transcriptional and DNA methylation programs during metamorphosis of the butterfly Bicyclus anynana (methylation).
GEO Series GSE276476. Bicyclus anynana. 15 samples. Type: Methylation profiling by high throughput sequencing.
Replications Package for "Understanding the Dynamics of License Selection in OSS: A Data-Driven Exploration Across Different Programming Languages"
<p>Replications Package for "Understanding the Dynamics of License Selection in OSS: A Data-Driven Exploration Across Different Programming Languages"<br><br>Includes datasets and R code.</p>
Néevo®/NéevoDHA® P.L.U.S. Program (Progress Through Learning, Understand & Support)
ClinicalTrials.gov study NCT01358552. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Metanx® P.L.U.S. Program (Progress Through Learning, Understanding & Support)
ClinicalTrials.gov study NCT01368549. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Adherence and Understanding of a Therapeutic Education Program for Patients With Central Venous Access (EDUVVC)
ClinicalTrials.gov study NCT06478849. IPD Sharing: NO. Countries: 1. Publications: 0.
Mobile Phone Text Message Program to Understand Symptoms and Improve Outcomes in Minor Head Injury Patients
ClinicalTrials.gov study NCT01668342. IPD Sharing: Not stated. Countries: 1. Publications: 0.
NAC-003 P.L.U.S. Program (Progress Through Learning Understanding & Support)
ClinicalTrials.gov study NCT01370954. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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
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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.