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A Study of Non-linearity in the Statistical Convertibility of Function Points into COSMIC Function Points

Contributo in Atti di convegno
Data di Pubblicazione:
2010
Abstract:
Background. After the COSMIC Functional Size Measurement method was proposed, the issue of convertibility between traditional function points and COSMIC function points arose. Several studies have been performed, to evaluate whether a correlation between the two measures. Specifically, it has been suggested that the relation between the measures of FP and CFP may not be linear, i.e., it is a curve that increases its slope for bigger projects.
Objective. This paper aims at verifying this hypothesis using the available datasets that collect both FP and CFP size measures.
Method. Rigorous statistical analysis techniques are used. In particular regression analysis is used, and the conditions for its applicability are systematically applied.
Results. It appears that the analysis of the correlation between FP and CFP measures based on non linear regression models yields different results for the various available datasets: non-linear models can be the best representation of the correlation between FP and CFP, but can also be just equivalent to linear models, or even hardly applicable.
Conclusions. There is no evidence that the non-linear models represent well all the available datasets correlating FP and CFP measures. Both linear and non linear regressions should be applied to a given dataset in order to identify the best correlation of FP and CFP.
Tipologia CRIS:
Relazione (in Volume)
Keywords:
COSMIC Function points; Function point analysis; Functional Size Measurement; Functional size measure convertibility; Data analysis; Outliers; Statistical significance.
Elenco autori:
Lavazza, LUIGI ANTONIO; Morasca, Sandro
Autori di Ateneo:
Ingegneria del Software Empirica
LAVAZZA LUIGI ANTONIO
MORASCA SANDRO
Link alla scheda completa:
https://irinsubria.uninsubria.it/handle/11383/1717139
Titolo del libro:
Workshop on Advances in Functional Size Measurement and Effort Estimation (FSM '10)
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