A Survey of Dynamic Software Metrics <s> Dynamic Metrics for Object Clustering <s> In client/server and distributed applications, the quality of object clustering plays a key role in determining the overall performance of the system. Therefore, a set of objects with higher coupling should be grouped into a single cluster so that each cluster can have a higher cohesion. As a result, the overall message traffic among objects can be greatly minimized. In addition, it should also be considered in CORBA-based applications that clusters themselves can evolve due to the dynamic object migration feature of CORBA. Hence, dynamic metrics as well as as static metrics should be developed and used in order to measure the dynamic message traffic and to tune up the system performance effectively. Various object-oriented design metrics proposed mainly deal with static coupling and cohesion, and they only consider the basic class relationships such as association, inheritance, and composition. Therefore, these metrics are not appropriate for measuring the traffic load of object messages which is closely related to the system performance. In this paper, we propose a set of metrics which considers the relevant weights on the various class relationships and estimates the static and dynamic message flow among the objects at the detailed level of member functions. By applying these metrics along with OMT or UML, we believe that clusters can be defined more efficiently and systematically, yielding high performance distributed applications. <s> BIB001 </s> A Survey of Dynamic Software Metrics <s> Dynamic Metrics for Object Clustering <s> A charge coupled device (CCD) wherein clocking or charge transfer at relatively high frequencies is obtained by the use of a slow-wave structure in the form of a metallized meander line fabricated on a relatively thin region of silicon dioxide contiguously formed on the surface of a silicon semiconductor substrate. <s> BIB002
Cho et al. BIB001 propose dynamic coupling and cohesion metrics, which can be used to cluster objects logically. The proposed dynamic metrics are measured by the number of messages passed between functions contained in objects at runtime. The clustering of objects reduces network traffic and the load of client/server so that it can improve system performance. In client/server applications, the quality of object clustering plays a key role in determining the overall performance of the system. Thus, a set of objects with higher exchange of number of messages between objects should be grouped into a single cluster so that each cluster can have a higher cohesion. As a result, the overall message traffic among objects can be minimized. Various dynamic as well as static metrics are used in order to measure the dynamic message traffic and to tune up the system performance. The proposed object-oriented design metrics mainly deal with static coupling and cohesion, and they only consider the basic class relationships such as association, inheritance, and composition. Thus, these metrics are not appropriate for measuring the traffic load of object messages, which is closely related to the system performance. Authors propose a set of metrics that consider the relevant weights on various class relationships and estimate the static and dynamic message flow among the objects at the detailed level of member functions. By applying these metrics along with UML BIB002 , it is believed that clusters can be defined more efficiently and systematically, yielding high performance distributed applications.