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Measuring software stability based on complex networks in software
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DOI：10.1007/s10586-017-1353-y.png)
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Software maintenance is regarded as an activity of high cost. Developing meaningful metrics to assess the quality characteristics of software has become one of the most effective ways to reduce the cost. In this paper, we propose metrics to quantify the software stability from a complex network perspective. First, the topological structure of software at the class level is represented by a Class Coupling Network (CCN). Second, based on the CCN, we further propose a Node Influence Network (NIN) which considers both the directed and indirected (transitive) coupling strength between classes. Finally, based on NIN, we propose a metric to quantify the class stability and further propose a metric to quantify the stability of software as a whole. The proposed metrics are validated theoretically using widely accepted Weyuker's criteria and empirically using Java programs. The theoretical evaluation shows the proposed metrics satisfy most of Weyuker's properties, and the empirical evaluation shows the effectiveness of our proposed metrics as indicators of the external software qualities such as scalability and change proneness.
Keyword:
Software stability
Complex networks
Software metrics
Object-oriented software
Software maintenance
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