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478 results for “artifact”
Computational Artifacts for Performance Feedback Autoscaling Experiments with Workloads of Workflows in Apache Airflow
<p>These computational artifacts are related to the software artifacts DOI:10.5281/zenodo.2635571</p> <p><strong>The content of the computational artifacts:</strong></p> <ul> <li><strong>experiments.pdf</strong> contains the list of all the conducted experiments with the Airflow system. Experiment IDs are not sequential since some experiments required rerunning, etc., we report only successful results. The file lists different experiment configurations, e.g., the number of processed workflows, the name of the used workload, the user budgets, and PFA settings.</li> <li><strong>db.tar.gz</strong> contains directories with Airflow database snapshots and autoscaler logs. The names of the directories correspond to those listed in `experiments.pdf`. Each experiment directory contains an autoscaler log and a full copy of a PostgreSQL database directory just after each experiment finished. The database name is `airflow`, the user name is `ailyushk`. Within each database, most of the paper-related data are stored in the `stat_log` table. The scripts for extracting data from these databases are available as software artifacts in `tools/analysis`.</li> <li><strong>gurobi.tar.gz</strong> contains the results obtained from the Gurobi solver when solving the MIP model.</li> <li><strong>pdf.tar.gz</strong> contains all the figures in pdf format, also those that were not included neither in the paper nor in the technical report. The scripts for creating this plots are delivered as software artifacts.</li> <li><strong>csv.tar.gz</strong> contains the analysis results extracted from Airflow database snapshots. These files are used to create the plots in the `pdf` directory. The scripts for doing this are delivered as software artifacts.</li> <li><strong>wl1.tar.gz</strong> is the first synthetic realistic workload (WL I) with three subsets of 200 workflows each (`1_0`, `1_1`, `1_2`). Each directory contains the file with interarrivals `interarrivals.txt`, and the file with workflow IDs `workload.txt` in the subset. The `dags` directory contains Python-based Airflow descriptors and CSV files that summarise the same descriptors in CSV format for simpler analysis. The scripts for extracting workload statistics from these CSV files are available in the software artifacts in `tools/analysis`. The `inputs` directory contains initial input files for each worfklow. The `dax` contains original DAX files obtained from the generator: <a href="https://github.com/pegasus-isi/WorkflowGenerator/tree/master/bharathi/src/simulation/generator">https://github.com/pegasus-isi/WorkflowGenerator/tree/master/bharathi/src/simulation/generator</a></li> <li><strong>wl2.tar.gz</strong> is the second synthetic realistic workload (WL II) with three subsets of 200 workflows each (`4_0`, `4_1`, `4_2`). Has similar structure as `wl1.tar.gz`, except that `dax` directory is omitted, as WL II uses the same DAX structures as WL I.</li> <li><strong>wl3.tar.gz</strong> is the small synthetic workload based on WL I for the experiment with the MIP solver, contains three subsets with 5 workflows in each, all in the `3_0` directory (thus, the structure differs from the WL I and WL II). The input data files are empty. The identifiers of workflows forming each subset are stored in the `workload_1.txt`, `workload_2.txt`, and `workload_3.txt` files.</li> </ul>
PACT2019 Artifacts for "Fast Parallel Equivalence Relations in a Datalog Compiler"
<p>This is the official artifact for the paper "Fast Parallel Equivalence Relations in a Datalog Compiler" due to be published in PACT 2019.</p> <p>We provide a pre-built Docker image on Dockerhub (~1GB), fetch with:</p> <pre><code class="language-bash">sudo docker pull pnappa/pact2019_eqrel</code></pre> <p> </p> <p><strong>Alternatively</strong>, you may rebuild the Docker image from scratch (or install natively on a Debian-based system) by downloading this zip file, and following the instructions below.</p> <p>After downloading the artifacts.zip file to your computer, unzip it to reveal the following hierarchy:</p> <pre><code>pact2019_eqrel_artifacts/ ├── bitcoin_same_user/ ├── Dockerfile ├── microbenchmarks/ ├── openjdk_javalang_steensgaard/ ├── README.md └── souffle_1.5.1-1_amd64.deb </code></pre> <p>There are several options of installing - we recommend using Docker, although we provide instructions also for native installation of Debian-systems in the README.md.</p> <p>One can build a new Docker instance (which will take over an hour - grab a coffee!) through the command (when inside the pact2019_eqrel_artifacts directory):</p> <pre><code class="language-bash">sudo docker build --tag=pnappa/pact2019_eqrel .</code></pre> <p> </p> <p> </p> <p>To run & enter the container, run:</p> <pre><code class="language-bash">sudo docker container run -it pnappa/pact2019_eqrel</code></pre> <p>Refer to README.md for additional instructions in how to perform the experiments, and observe the findings.</p>
CSS'24 #677 Artifact
<p>Artifact for #677 in CSS'24</p>
CrashRepair - Experiment Artifacts and Source Code
Open the record for dataset details and reuse information.
Detailed Artifacts of the Paper "A Case Study of the MEUSec Method to Enhance User Experience and Information Security of Digital Identity Wallets"
<p><strong>Detailed Artifacts of the Paper:</strong> <em><strong>A case study of the MEUSec method to enhance user experience and information security of digital identity wallets. 2025. Journal of Interactive Media (i-com). <a href="https://doi.org/10.1515/icom-2024-0057" target="_blank" rel="noopener">https://doi.org/10.1515/icom-2024-0057</a> </strong></em></p> <p>The artifacts were obtained by applying the MEUSec method to the Hidy wallet which was at an early stage of development.</p> <p> </p>
The Tale of Errors in Microservices (Artifact part 2)
<p>Part 2 of trace release. Please refer to part 1 <a href="https://doi.org/10.5281/zenodo.13947828">10.5281/zenodo.13947828</a> for details.</p>
(Artifact) Understanding Model Weaknesses: A Path to Strengthening DNN-Based Android Malware Detection
Open the record for dataset details and reuse information.
Artifact for the paper "Abstract Interpretation of LLVM with a Region-Based Memory Model"
<p>Contain all scripts necessary to reproduce the results (Table 1) in the paper.</p>
Artifact for paper "Lifelong Dynamic Optimization for Self-Adaptive Systems: Fact or Fiction?" published at IEEE SANER 2022
<p>The zip file contains all the source code and data for the experiments.</p>
Dataset and CNN code for DECam CNN Difference Imaging Artifact Paper
<p>Dataset and code to accompany the paper listed at: https://arxiv.org/abs/2106.11315v1</p>
Artifact for ICSE'23 paper: Triggers for Reactive Synthesis Specifications
<p>Artifact for ICSE'23 paper: Triggers for Reactive Synthesis Specifications</p>
Test artifact for fs-LDW
<p>Data to generate the given graphs in the publication as well as raw images of the shown images</p>
Artifact of 'Proof Automation for Linearizability in Separation Logic'
<p>This is the artifact for the OOPSLA '23 paper 'Proof Automation for Linearizability in Separation Logic'. It contains the Diaframe 2.0 source code, a VM containing a compiled version of this source code, and instructions for evaluation.</p> <p>Diaframe 2.0's current development can be found <a href="https://gitlab.mpi-sws.org/iris/diaframe">here</a>.</p>
Artifact of the paper: On the Effectiveness of Automated Program Repair: An Extensive Study
<p>The pre-trained Edits model.</p>
Artifact of paper: On the Effectiveness of Automated Program Repair: An Extensive Study
<p>This is the artifact repo for paper: <strong>On the Effectiveness of Automated Program Repair: An Extensive Study</strong>. This repo contains large files, e.g., patches and compilation logs for this study.</p>
TOPr artifact
<p>TOPr artifact</p>
GrayC-artifact
<p>GrayC ISSTA artifact</p>
Raw Data and Artifact
<p>Raw Data and Artifact</p>
Artifact of paper "Transforming Test Suites Into Croissants"
<p>This is the artifact of paper "Transforming Test Suites Into Croissants".</p>
Artifacts for ICSE 2024 Paper Submission #1674
<p><strong>This data set is for ICSE 2024 Paper Submission #1674</strong></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.