摘要
Large-scale object-oriented(OO) software systems have recently been found to share global network characteristics such as small world and scale free,which go beyond the scope of traditional software measurement and assessment methodologies.To measure the complexity at various levels of granularity,namely graph,class(and object) and source code,we propose a hierarchical set of metrics in terms of coupling and cohesion-the most important characteristics of software,and analyze a sample of 12 open-source OO software systems to empirically validate the set.Experimental results of the correlations between cross-level metrics indicate that the graph measures of our set complement traditional software metrics well from the viewpoint of network thinking,and provide more effective information about fault-prone classes in practice.
Large-scale object-oriented(OO) software systems have recently been found to share global network characteristics such as small world and scale free,which go beyond the scope of traditional software measurement and assessment methodologies.To measure the complexity at various levels of granularity,namely graph,class(and object) and source code,we propose a hierarchical set of metrics in terms of coupling and cohesion-the most important characteristics of software,and analyze a sample of 12 open-source OO software systems to empirically validate the set.Experimental results of the correlations between cross-level metrics indicate that the graph measures of our set complement traditional software metrics well from the viewpoint of network thinking,and provide more effective information about fault-prone classes in practice.
基金
Supported by the National Grand Fundamental Research 973 Program of China under Grant No.2007CB310800
the National Natural Science Foundation of China under Grant Nos.60873083 and 60803025
the Research Fund for the Doctoral Program of Higher Education of China under Grant No.20090141120022
the Natural Science Foundation of Hubei Province of China under Grant Nos.2008ABA379 and 2008CDB351
the Fundamental Research Funds for the Central Universities of China under Grant No.6082005