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.
Effort Prediction in Iterative Software Development Processes - Incremental Versus Global Prediction Models / Abrahamsson P; Moser R; Pedrycz W; Sillitti A; Succi G. - STAMPA. - (2007), pp. 344-353. (Intervento presentato al convegno 1St International Symposium On Empirical Software Engineering And Measuremtn (Esem 2007) tenutosi a Madrid, Spain nel September).
Effort Prediction in Iterative Software Development Processes - Incremental Versus Global Prediction Models
Succi G
2007
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.