Other Open Access

Additional proofs and code for "Data-flow analyses as effects and graded monads"

Andrej Ivaskovic; Alan Mycroft; Dominic Orchard


DataCite XML Export

<?xml version='1.0' encoding='utf-8'?>
<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd">
  <identifier identifierType="DOI">10.5281/zenodo.3784967</identifier>
  <creators>
    <creator>
      <creatorName>Andrej Ivaskovic</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-1347-4884</nameIdentifier>
      <affiliation>University of Cambridge</affiliation>
    </creator>
    <creator>
      <creatorName>Alan Mycroft</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-7013-8572</nameIdentifier>
      <affiliation>University of Cambridge</affiliation>
    </creator>
    <creator>
      <creatorName>Dominic Orchard</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-7058-7842</nameIdentifier>
      <affiliation>University of Kent</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Additional proofs and code for "Data-flow analyses as effects and graded monads"</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <subjects>
    <subject>data-flow analysis</subject>
    <subject>effect systems</subject>
    <subject>graded monads</subject>
    <subject>correctness</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2020-05-04</date>
  </dates>
  <resourceType resourceTypeGeneral="Other"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3784967</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsSupplementTo" resourceTypeGeneral="Text">10.4230/LIPIcs.FSCD.2020.15</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3784966</relatedIdentifier>
  </relatedIdentifiers>
  <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;This deposit provides code and additional proofs associated to the paper &amp;quot;Data-flow analyses as effects and graded monads&amp;quot; appearing at FSCD 2020 (5th International Conference On Formal Structures for Computation and Deduction).&lt;/p&gt;

&lt;ul&gt;
	&lt;li&gt;
	&lt;ul&gt;
	&lt;/ul&gt;
	&lt;strong&gt;extra-proofs.pdf&amp;nbsp;&lt;/strong&gt;provides additional proofs not included in the appendix of the published paper for space reasons.&lt;/li&gt;
	&lt;li&gt;&lt;strong&gt;GradedMonad.agda&amp;nbsp;&lt;/strong&gt;provides further mechanised proofs, referred to&amp;nbsp;from extra-proofs.pdf&lt;/li&gt;
	&lt;li&gt;&lt;strong&gt;dataflow-effects-as-grades-fscd2020.zip&amp;nbsp;&lt;/strong&gt;provides the source code corresponding to Section 4.4 and Appendix B
	&lt;ul&gt;
		&lt;li&gt;The code is hosted on GitHub as well:&amp;nbsp;&lt;a href="https://github.com/dorchard/dataflow-effects-as-grades"&gt;https://github.com/dorchard/dataflow-effects-as-grades&lt;/a&gt;&lt;/li&gt;
		&lt;li&gt;This .zip corresponds to this release&amp;nbsp;&lt;a href="https://github.com/dorchard/dataflow-effects-as-grades/releases/tag/fscd2020"&gt;https://github.com/dorchard/dataflow-effects-as-grades/releases/tag/fscd2020&lt;/a&gt;&lt;/li&gt;
		&lt;li&gt;Unzip and see README.md for details on how to build and interact with this code&lt;/li&gt;
	&lt;/ul&gt;
	&lt;/li&gt;
&lt;/ul&gt;</description>
  </descriptions>
</resource>
136
35
views
downloads
All versions This version
Views 136136
Downloads 3535
Data volume 9.9 MB9.9 MB
Unique views 119119
Unique downloads 2121

Share

Cite as