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Dataset Open Access

NJR-1 Dataset

Utture, Akshay; Kalhauge, Christian Gram; Liu, Shuyang; Palsberg, Jens


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  <identifier identifierType="DOI">10.5281/zenodo.4632231</identifier>
  <creators>
    <creator>
      <creatorName>Utture, Akshay</creatorName>
      <givenName>Akshay</givenName>
      <familyName>Utture</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-9623-3049</nameIdentifier>
      <affiliation>UCLA</affiliation>
    </creator>
    <creator>
      <creatorName>Kalhauge, Christian Gram</creatorName>
      <givenName>Christian Gram</givenName>
      <familyName>Kalhauge</familyName>
      <affiliation>UCLA</affiliation>
    </creator>
    <creator>
      <creatorName>Liu, Shuyang</creatorName>
      <givenName>Shuyang</givenName>
      <familyName>Liu</familyName>
      <affiliation>UCLA</affiliation>
    </creator>
    <creator>
      <creatorName>Palsberg, Jens</creatorName>
      <givenName>Jens</givenName>
      <familyName>Palsberg</familyName>
      <affiliation>UCLA</affiliation>
    </creator>
  </creators>
  <titles>
    <title>NJR-1 Dataset</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <subjects>
    <subject>Static Analysis, Java</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2020-06-16</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4632231</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsSupplementTo" resourceTypeGeneral="Text">10.1145/3236454.3236501</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3897691</relatedIdentifier>
  </relatedIdentifiers>
  <version>1.0.1</version>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;NJR is a Normalized Java Resource.&lt;/p&gt;

&lt;p&gt;The &lt;em&gt;NJR-1&lt;/em&gt; dataset consists of 293 Java bytecode programs, each of which runs successfully with the following 12 Java static analysis tools:&lt;/p&gt;

&lt;p&gt;1. &amp;nbsp;SpotBugs (https://spotbugs.github.io)&lt;br&gt;
2. &amp;nbsp;Wala (https://wala.github.io)&lt;br&gt;
3. &amp;nbsp;Doop (https://bitbucket.org/yanniss/doop)&lt;br&gt;
4. &amp;nbsp;Soot (https://github.com/soot-oss/soot)&lt;br&gt;
5. &amp;nbsp;Petablox (https://github.com/petablox/petablox)&lt;br&gt;
6. &amp;nbsp;Infer (https://fbinfer.com)&lt;br&gt;
7. &amp;nbsp;Error-Prone (http://errorprone.info)&lt;br&gt;
8. &amp;nbsp;Checker-Framework (https://checkerframework.org)&lt;br&gt;
9. &amp;nbsp;Opium (Opal-framework) (https://www.opal-project.de)&lt;br&gt;
10. Spoon (https://spoon.gforge.inria.fr)&lt;br&gt;
11. PMD (https://pmd.github.io)&lt;br&gt;
12. CheckStyle (https://checkstyle.org)&lt;/p&gt;

&lt;p&gt;Additionally, each program&amp;nbsp;executes at least 100 unique application methods at runtime.&amp;nbsp;These programs are repositories picked from the set of Java-8 projects on Github that compile and run successfully.&amp;nbsp;Each of these programs come with a jar file, the compiled bytecode files, compiled library files&amp;nbsp;and the Java source code. It also comes with a list of source files, declared methods, application-classes list, and main-class names.&amp;nbsp;The availability of the files in both jar-file form, as well as source code form (with the compiled library classes) is a major reason the dataset works&amp;nbsp;with&amp;nbsp;so many tools, without requiring any extra effort.&lt;/p&gt;

&lt;p&gt;There are 3 files available for download: &lt;em&gt;njr-1_dataset.zip, scripts.zip, benchmark_stats.csv.&lt;/em&gt;&lt;/p&gt;

&lt;p&gt;&lt;em&gt;njr-1_dataset.zip&lt;/em&gt; has the actual dataset programs. &lt;em&gt;scripts.zip&lt;/em&gt; contains&amp;nbsp;Python3 scripts&amp;nbsp;for each tool, to run it&amp;nbsp;on the entire dataset.&amp;nbsp;The &lt;em&gt;benchmark_stats.csv&lt;/em&gt; file lists, for each benchmark, the number of nodes and edges in its dynamic application call-graph, as well as the number of edges in its static application call-graph (as computed by Wala) when using the main function listed in the&amp;nbsp;&lt;em&gt;info/mainclassname&lt;/em&gt; file.&amp;nbsp;&lt;br&gt;
A summary of the same is listed here:&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;&lt;em&gt;Statistics &amp;nbsp;Dynamic-Nodes &amp;nbsp;Dynamic-Edges &amp;nbsp;Static-Edges&lt;/em&gt;&lt;/strong&gt;&lt;br&gt;
Mean &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; 205&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;469&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; 1404&lt;br&gt;
St.Dev &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; 199&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;464&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;2523&lt;br&gt;
Median &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;149&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;327&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;610&lt;/p&gt;

&lt;p&gt;To cite the dataset, please cite the following paper:&lt;br&gt;
Jens Palsberg and Cristina V. Lopes,&amp;nbsp;NJR: a&amp;nbsp;Normalized Java Resource.&amp;nbsp;&lt;br&gt;
In Proceedings of ACM SIGPLAN International Workshop&amp;nbsp;on State Of the Art in Program Analysis (SOAP), 2018.&lt;/p&gt;</description>
    <description descriptionType="Other">Funded by the following NSF grant (https://www.nsf.gov/awardsearch/showAward?AWD_ID=1823360&amp;amp;HistoricalAwards=false)</description>
  </descriptions>
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