Component granularity optimization design based on business model stability evaluation

Coarse-grained reuse has been the primary tendency in software reuse field, and it has been proved that granularity has great effect on component reuse performance. However, previous studies have ignored rigorous and effective methods to support coarse-grained component identification and granularity optimization. A business model stability based component granularity optimization design method is presented to solve this problem. Firstly a feature-oriented component model and the corresponding component granularity metrics are briefly proposed, based on which, four different mapping strategies between business model space and component space are discussed for obtaining dynamic and optimal component granularities. According to some theoretic analysis on the correlation between business model stability and component granularity, i.e., the more stable a business model is, the larger the corresponding component's granularity could be, a stability-based component identification method (STCIM) is put forward in detail with the dynamic granularity mapping strategy, based on the metrics for business model stability with three independent factors, i.e., isomer number, stability entropy and isomer similarities. The significant advantages of STCIM on component reusability optimization are validated by a practical case and the qualitative comparisons between STCIM and other component identification methods in literatures.