.zenodo.json

{
  "title": "pymwp: MWP analysis in Python",
  "description": "pymwp is a tool for automatically performing static analysis on programs written in C. It analyzes resource usage and determines if a program's variables growth rates are no more than polynomially related to their inputs sizes.",
  "upload_type": "software",
  "access_right": "open",
  "license": "GPL-3.0-or-later",
  "creators": [
    {
      "affiliation": "School of Computer and Cyber Sciences, Augusta University",
      "name": "Aubert, Clément",
      "orcid": "0000-0001-6346-3043"
    },
    {
      "affiliation": "LIPN – UMR 7030 Université Sorbonne Paris Nord",
      "name": "Rubiano, Thomas"
    },
    {
      "affiliation": "School of Computer and Cyber Sciences, Augusta University",
      "name": "Rusch, Neea",
      "orcid": "0000-0002-7354-5330"
    },
    {
      "affiliation": "LIPN – UMR 7030 Université Sorbonne Paris Nord & CNRS",
      "name": "Seiller, Thomas",
      "orcid": "0000-0001-6313-0898"
    }
  ],
  "language": "eng",
  "keywords": [
    "program analysis", "mwp-analysis", "implicit computational complexity"
  ],
  "related_identifiers": [
    { "relation": "isDocumentedBy", "identifier": "https://statycc.github.io/pymwp/", "scheme": "url", "resource_type": "publication-softwaredocumentation"},
    { "relation": "isDescribedBy", "identifier":  "https://statycc.github.io/.github/pymwp/", "scheme": "url", "resource_type": "presentation" },
    { "relation": "isPublishedIn", "identifier":  "10.1007/978-3-031-45332-8_14", "scheme": "doi", "resource_type": "publication-conferencepaper" }
  ]
}