Title: Software stage-effort estimation based on association rule mining and fuzzy set theory,
Abstract: Relaying on early effort estimation to predict the required number of
resources is not often sufficient, and could lead to under or over estimation.
It is widely acknowledge that that software development process should be
refined regularly and that software prediction made at early stage of software
development is yet kind of guesses. Even good predictions are not sufficient
with inherent uncertainty and risks. The stage-effort estimation allows project
manager to re-allocate correct number of resources, re-schedule project and
control project progress to finish on time and within budget. In this paper we
propose an approach to utilize prior effort records to predict stage effort.
The proposed model combines concepts of Fuzzy set theory and association rule
mining. The results were good in terms of prediction accuracy and have
potential to deliver good stage-effort estimation.