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Author(s): D.G. Edgar-Nevill
Abstract:
nd software metrics datasets
D.G.
Edgar-NeviH
Department of Computer Studies, Napier
University, Edinburgh, UK
ABSTRACT
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.
Widely used
software metrics systems such as COCOMO [1] and SLIM [2] have been based on
results analysed in this way.
When building such datasets credibility is usually given to large sets of data rather than
smaller.
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.
Guidelines are
given on the formation of...
Pages: 10
Size: 764 kb
Paper DOI: 10.2495/SQM940231
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