Software Open Access

POM-XOMO Software Engineering Models

Tim Menzies; George Mathew; Vivek Nair


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{
  "@context": "https://schema.org/", 
  "@id": "https://doi.org/10.5281/zenodo.1169623", 
  "@type": "SoftwareSourceCode", 
  "creator": [
    {
      "@type": "Person", 
      "affiliation": "North Carolina State University", 
      "name": "Tim Menzies"
    }, 
    {
      "@type": "Person", 
      "affiliation": "North Carolina State University", 
      "name": "George Mathew"
    }, 
    {
      "@type": "Person", 
      "affiliation": "North Carolina State University", 
      "name": "Vivek Nair"
    }
  ], 
  "datePublished": "2018-02-09", 
  "description": "<p>XOMO combines four software process models from Boehm&rsquo;s group at the University of Southern California.&nbsp;XOMO derives four objective scores: (1) project risk; (2) development effort; (3) predicted defects; (4) total months of development (Months = effort / #workers). Effort and defects are predicted from mathematical models derived from data collected from hundreds of commercial and Defense Department projects.</p>\n\n<p>&nbsp;</p>\n\n<p>POM3: According to Turner and Boehm, agile managers struggle to balance idle rates, completion rates, and overall cost. &bull; In the agile world, projects terminate after achieving a completion rate of (X &lt; 100)% of its required tasks. &bull; Team members become idle if forced to wait for a yet-tobe-finished task from other teams. &bull; To lower idle rate and increase completion rate, management can hire staff&ndash;but this increases overall cost.</p>", 
  "identifier": "https://doi.org/10.5281/zenodo.1169623", 
  "license": "https://creativecommons.org/licenses/by/4.0/", 
  "name": "POM-XOMO Software Engineering Models", 
  "url": "https://zenodo.org/record/1169623"
}

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