The increasement of software complexity directly results in the augment of software fault and costs a lot in the process of software\ndevelopment and maintenance. The complex network model is used to study the accumulation and accumulation of faults in\ncomplex software as a whole.Then key nodes with high fault probability and powerful fault propagation capability can be found,\nand the faults can be discovered as soon as possible and the severity of the damage to the system can be reduced effectively. In\nthis paper, the algorithm MFS AN (mining fault severity of all nodes) is proposed to mine the key nodes fromsoftware network. A\nweighted software networkmodel is built by using functions as nodes, call relationships as edges, and call times asweight. Exploiting\nrecursive method, a fault probability metric FP of a function, is defined according to the fault accumulation characteristic, and a\nfault propagation capability metric FPC of a function is proposed according to the fault propagation characteristic. Based on the\nFP and FPC, the fault severity metric FS is put forward to obtain the function nodes with larger fault severity in software network.\nExperimental results on two real software networks show that the algorithm MFS _AN can discover the key function nodes correctly\nand effectively.
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