Abstract:

Under some small history data condition, a grey relational analysis method for software effort estimation is proposed. Firstly, the relationship grade between features and effort is analyzed according to the grey relational analysis theory. At the same time, the optimal feature set is chose by regression technique. On the basis of which, the grey relationship grades between new software and history dataset are computed, and some high relationship grade software data are used for estimating the effort of new software. Finally, four history datasets are used for analyzing the performance of the estimation method. The results of experiment show that the proposed method could precisely estimate software effort, and the method is superior to the linear regression, back propagation network, and analogy method. After some low relationship grade features are deleted from the optimal feature set, the mean magnitude of relative errors is further reduced.