Author(s): D.G. Edgar-Nevill
nd software metrics datasets
Department of Computer Studies, Napier
University, Edinburgh, UK
Many software project assessment and prediction systems are based on the results of
analysis gathered from past projects.
It is intuitively sensible to gather such data and
look for trends upon which to form formulae using statistical techniques.
software metrics systems such as COCOMO  and SLIM  have been based on
results analysed in this way.
When building such datasets credibility is usually given to large sets of data rather than
Little regard seems to be given, however, when it is appropriate to add a new
projects results to a dataset.
Even less often is thought given to when a projects results
should be removed from a dataset.
This paper considers the problem by analysing the construction and use of historical
software project data repositories in a number of case study companies.
given on the formation of...
Size: 764 kb
Paper DOI: 10.2495/SQM940231
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This paper can be found in the following bookSoftware Quality Management II Vol 1 Managing Quality Systems Buy