Sigmoid Curve Model for software Test-Effort Estimation


The KIPS Transactions:PartD, Vol. 11, No. 4, pp. 885-892, Aug. 2004
10.3745/KIPSTD.2004.11.4.885,   PDF Download:

Abstract

Weibull distribution Iincluding Rayleigh and Exponential distribution is a typical model to estimate the effort distribution which is committed to the software testing phase. This model does not represent standpoint that many efforts are committed actually at the test beginning point. Moreover, it does not properly represent the various distribution form of actual test effort. To solve these problems, this paper proposes the Sigmoid model. The sigmoid function to be applicable in neural network transformed into the function which properly represents the test effort of software in the model. The model was verified to the six test effort data which were got from actual software projects which have various distribution form and verified the suitability. The Sigmoid model may be selected by the alternative of Weibull model to estimate software test effort because it is superior than the Weibull model.


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Cite this article
[IEEE Style]
S. U. Lee, "Sigmoid Curve Model for software Test-Effort Estimation," The KIPS Transactions:PartD, vol. 11, no. 4, pp. 885-892, 2004. DOI: 10.3745/KIPSTD.2004.11.4.885.

[ACM Style]
Sang Un Lee. 2004. Sigmoid Curve Model for software Test-Effort Estimation. The KIPS Transactions:PartD, 11, 4, (2004), 885-892. DOI: 10.3745/KIPSTD.2004.11.4.885.