Traceability challenge 2013: Statistical analysis for traceability experiments: Software verification and validation research laboratory (SVVRL) of the University of Kentucky

  • Hays M
  • Hayes J
  • Stromberg A
 et al. 
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An important aspect of traceability experiments is the ability to compare techniques. In order to assure proper comparison, it is necessary to perform statistical analysis of the dependent variables collected from technique application. Currently, there is a lack of components in TraceLab to support such analysis. The Software Verification and Validation Research Laboratory (SVVRL) and the Statistics Department of the University of Kentucky have developed a collection of such components as well as a workflow for determining what type of analysis to apply (parametric, non-parametric). The components use industry-accepted R algorithms. The components have been validated using independent standard statistical algorithms applied to publicly available datasets. This work addresses the Purposed grand challenge (research project 4) and Cost-Effective Grand Challenge (research project 4) as well as the Valued Grand Challenge - research project 6. © 2013 IEEE.

Author-supplied keywords

  • Cost-Effective Grand challenge
  • Non-parametric tests
  • Parametric tests
  • Purposed grand challenge
  • Statistical analysis
  • TraceLab component
  • Traceability experiment
  • Valued Grand Challenge

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  • Mark Hays

  • Jane Huffman Hayes

  • Arnold J. Stromberg

  • Arne C. Bathke

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