Dataset Open Access

Characterizing Energy Consumption of Third-Party API Libraries using API Utilization Profiles (ESEM'2020 Dataset)

Andreas Schuler; Gabriele Kotsis


JSON-LD (schema.org) Export

{
  "description": "<p><strong>Motivation</strong></p>\n\n<p>This repository contains the data-set used as a basis for our ESEM&#39;2020 paper&nbsp;<em>Characterizing Energy Consumption of Third-Party API Libraries using API Utilization Profiles</em>&nbsp;The dataset is comprised of 2 test scenarios: The first one is based on the paper from Rocha et al. (2019), the second one is based on the commonly known Google Gson library.</p>\n\n<p><strong>Description of the dataset</strong></p>\n\n<p>The dataset is stored in a file&nbsp;*.csv&nbsp;and contains the following data:</p>\n\n<ul>\n\t<li>id&nbsp;- an individual identifier</li>\n\t<li>name&nbsp;- the name of the library examined</li>\n\t<li>className&nbsp;- the class name as an abbreviation</li>\n\t<li>method&nbsp;- the name of the executed method</li>\n\t<li>duration&nbsp;- duration of method execution</li>\n\t<li>energyConsumption&nbsp;- computed energy consumption</li>\n\t<li>watts&nbsp;- recorded wattage</li>\n\t<li>uApi&nbsp;- the computed uAPI profile value</li>\n</ul>\n\n<p>Besides the data, this repository also contains the result images from the ESEM&#39;2020 paper in&nbsp;pdf-file format.</p>\n\n<p><em><strong>Android I/O Experiment</strong></em></p>\n\n<p>For the Android I/O Experiment we examined the correlation between API utilization and energy consumption. For the dataset, we took inspiration from Rocha et al. (2019). The dataset uses abbreviations for the examined classes which are further described in the <em>readme.md</em> file</p>\n\n<ul>\n\t<li>Filename:&nbsp;io_test_052020.csv</li>\n</ul>\n\n<p><em><strong>Google Gson Experiment</strong></em></p>\n\n<p>The Google Gson dataset contains recordings for Google Gson version 2.8.5. Again, the dataset was used as a foundation for examining the correlation between the computed API profiles and energy consumption.</p>\n\n<ul>\n\t<li>Filename:&nbsp;gson_test_052020.csv</li>\n</ul>\n\n<p><strong>License</strong></p>\n\n<p>Creative Commons CC-BY</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "University of Applied Sciences Upper Austria", 
      "@type": "Person", 
      "name": "Andreas Schuler"
    }, 
    {
      "affiliation": "Department of Telecooperation, Johannes Kepler University Linz", 
      "@type": "Person", 
      "name": "Gabriele Kotsis"
    }
  ], 
  "url": "https://zenodo.org/record/3952021", 
  "datePublished": "2020-07-27", 
  "@type": "Dataset", 
  "keywords": [
    "energy consumption", 
    "software energy profiling", 
    "dynamic program analysis"
  ], 
  "@context": "https://schema.org/", 
  "distribution": [
    {
      "contentUrl": "https://zenodo.org/api/files/2cf7e92b-d917-465d-be94-4d6a651d06f7/attribution.pdf", 
      "encodingFormat": "pdf", 
      "@type": "DataDownload"
    }, 
    {
      "contentUrl": "https://zenodo.org/api/files/2cf7e92b-d917-465d-be94-4d6a651d06f7/cg_computation.pdf", 
      "encodingFormat": "pdf", 
      "@type": "DataDownload"
    }, 
    {
      "contentUrl": "https://zenodo.org/api/files/2cf7e92b-d917-465d-be94-4d6a651d06f7/compare_1.pdf", 
      "encodingFormat": "pdf", 
      "@type": "DataDownload"
    }, 
    {
      "contentUrl": "https://zenodo.org/api/files/2cf7e92b-d917-465d-be94-4d6a651d06f7/compare_2.pdf", 
      "encodingFormat": "pdf", 
      "@type": "DataDownload"
    }, 
    {
      "contentUrl": "https://zenodo.org/api/files/2cf7e92b-d917-465d-be94-4d6a651d06f7/correlation_2.pdf", 
      "encodingFormat": "pdf", 
      "@type": "DataDownload"
    }, 
    {
      "contentUrl": "https://zenodo.org/api/files/2cf7e92b-d917-465d-be94-4d6a651d06f7/experiment_def.pdf", 
      "encodingFormat": "pdf", 
      "@type": "DataDownload"
    }, 
    {
      "contentUrl": "https://zenodo.org/api/files/2cf7e92b-d917-465d-be94-4d6a651d06f7/gson_dataset_20072020.csv", 
      "encodingFormat": "csv", 
      "@type": "DataDownload"
    }, 
    {
      "contentUrl": "https://zenodo.org/api/files/2cf7e92b-d917-465d-be94-4d6a651d06f7/io_dataset_052020.csv", 
      "encodingFormat": "csv", 
      "@type": "DataDownload"
    }, 
    {
      "contentUrl": "https://zenodo.org/api/files/2cf7e92b-d917-465d-be94-4d6a651d06f7/readme.md", 
      "encodingFormat": "md", 
      "@type": "DataDownload"
    }, 
    {
      "contentUrl": "https://zenodo.org/api/files/2cf7e92b-d917-465d-be94-4d6a651d06f7/regression.pdf", 
      "encodingFormat": "pdf", 
      "@type": "DataDownload"
    }, 
    {
      "contentUrl": "https://zenodo.org/api/files/2cf7e92b-d917-465d-be94-4d6a651d06f7/residuals.pdf", 
      "encodingFormat": "pdf", 
      "@type": "DataDownload"
    }
  ], 
  "identifier": "https://doi.org/10.5281/zenodo.3952021", 
  "@id": "https://doi.org/10.5281/zenodo.3952021", 
  "workFeatured": {
    "url": "https://eseiw2020.di.uniba.it/esem_conf/", 
    "alternateName": "ESEM", 
    "location": "Bari, Italy", 
    "@type": "Event", 
    "name": "ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)"
  }, 
  "name": "Characterizing Energy Consumption of Third-Party API Libraries using API Utilization Profiles (ESEM'2020 Dataset)"
}
88
180
views
downloads
All versions This version
Views 8888
Downloads 180180
Data volume 17.5 MB17.5 MB
Unique views 6969
Unique downloads 160160

Share

Cite as