Effort Prediction in Iterative Software Development Processes -- Incremental Versus Global Prediction Models

Authors:
Pekka Abrahamsson;Raimund Moser;Witold Pedrycz;Alberto Sillitti;Giancarlo Succi
Affiliations:
VTT Electronics Oulu, Finland;Free University of Bolzano-Bozen, Italy;University of Alberta, Canada;Free University of Bolzano-Bozen, Italy;Free University of Bolzano-Bozen, Italy
Venue:
ESEM '07 Proceedings of the First International Symposium on Empirical Software Engineering and Measurement
Year:
2007

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Abstract

Estimation of development effort without imposing overhead on the project and the development team is of paramount importance for any software company. This study proposes a new effort estimation methodology aimed at agile and iterative development environments not suitable for description by traditional prediction methods. We propose a detailed development methodology, discuss a number of architectures of such models (including a wealth of augmented regression models and neural networks) and include a thorough case study of Extreme Programming (XP) in two semi-industrial projects. The results of this research evidence that in the XP environment under study the proposed incremental model outperforms traditional estimation techniques most notably in early phases of development. Moreover, when dealing with new projects, the incremental model can be developed from scratch without resorting itself to historic data.