Title :
An investigation of prediction models for project management
Author :
Rodríguez, Daniel ; Harrison, Rachel ; Satpathy, Manoranjan ; Dolado, Javier
Author_Institution :
Dept. of Comput. Sci., Reading Univ., UK
Abstract :
It has been claimed that dynamic prediction models can be used to help project managers make more accurate estimates than static prediction models. However, such a claim needs to be validated so that project managers can use dynamic models with confidence. In this paper we discuss an experiment we conducted in an academic environment that compared a dynamic model using Bayesian belief networks (BBN) with a static model involving the COCOMO and Akiyama models. The results from this experiment in fact validate the above claim. However we suggest replication of this experiment in order to increase confidence to our results.
Keywords :
project management; software development management; Akiyama model; BBN; Bayesian belief networks; COCOMO model; prediction models; project management; software engineering; system dynamics; Application software; Bayesian methods; Computer science; Equations; Performance evaluation; Predictive models; Project management; Software engineering; Statistical analysis; Uncertainty;
Conference_Titel :
Computer Software and Applications Conference, 2002. COMPSAC 2002. Proceedings. 26th Annual International
Print_ISBN :
0-7695-1727-7
DOI :
10.1109/CMPSAC.2002.1045099