Identifying function level complex modules based on complex coupled networks
Wei Liu, Ping Fan, Jiahao Nie · 2024
Current software evaluation work based on complex networks rarely considers the complexity of nodes themselves and the multiple coupling between nodes, making it difficult to accurately identify high complexity and high coupling modules in software. This paper proposes a method for evaluating software node complexity in complex functional granularity networks. By analyzing the static structure of complex software and clarifying the different types of dependencies between functions in the software, a function level complex coupling network is constructed. Propose a node risk importance index, considering the criticality of nodes in the network and the complexity of nodes themselves, to identify highly complex modules in software. Experimental results demonstrate that the NRI method proposed in this paper can more effectively identify complex nodes in software.