Pair-dependent rejection rate and its impact on traffic flow in a scale-free network

Security and Communication Networks

Wang

Liu

et al. 2019

The increasement of software complexity directly results in the augment of software fault and costs a lot in the process of software development and maintenance. The complex network model is used to study the accumulation and accumulation of faults in complex software as a whole. Then key nodes with high fault probability and powerful fault propagation capability can be found, and the faults can be discovered as soon as possible and the severity of the damage to the system can be reduced effectively. In this paper, the algorithm MFS_AN (mining fault severity of all nodes) is proposed to mine the key nodes from software network. A weighted software network model is built by using functions as nodes, call relationships as edges, and call times as weight. Exploiting recursive method, a fault probability metric FP of a function, is defined according to the fault accumulation characteristic, and a fault propagation capability metric FPC of a function is proposed according to the fault propagation characteristic. Based on the FP and FPC, the fault severity metric FS is put forward to obtain the function nodes with larger fault severity in software network. Experimental results on two real software networks show that the algorithm MFS_AN can discover the key function nodes correctly and effectively.

Section: Figure 1 Represents a Portion Of A Weighted Function Executimentioning

confidence: 99%

Section: Experiments and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Mining the Key Nodes from Software Network Based on Fault Accumulation and Propagation

Security and Communication Networks

Wang

Liu

et al. 2019

“…3,4 Discovering some new potential characteristics in the software structure is the key factor to ensure software quality and controlling the software execution. 3,[5][6][7][8] How to simplify the structure and improve the understanding for the complex software becomes a hot-spot issue in research.…”

Section: Introductionmentioning

confidence: 99%

The optimal community detection of software based on complex networks

Zhang

et al. 2016

Int. J. Mod. Phys. C

The community structure is important for software in terms of understanding the design patterns, controlling the development and the maintenance process. In order to detect the optimal community structure in the software network, a method Optimal Partition Software Network (OPSN) is proposed based on the dependency relationship among the software functions. First, by analyzing the information of multiple execution traces of one software, we construct Software Execution Dependency Network (SEDN). Second, based on the relationship among the function nodes in the network, we de¯ne Fault Accumulation (FA) to measure the importance of the function node and sort the nodes with measure results. Third, we select the top K ðK ¼ 1; 2; . . .Þ nodes as the core of the primal communities (only exist one core node). By comparing the dependency relationships between each node and the K communities, we put the node into the existing community which has the most close relationship. Finally, we calculate the modularity with di®erent initial K to obtain the optimal division. With experiments, the method OPSN is veri¯ed to be e±cient to detect the optimal community in various softwares.

“…Studies show that software systems have complex network phenomena, 2-6 namely small-world e®ect and scale-free property. 3,4 With further research on software systems, there is a new way of thinking on execution path of software dynamic network and its application. First of all, it is imperative to¯nd out the paths in network.…”

Section: Introductionmentioning

confidence: 99%

An algorithm to find critical execution paths of software based on complex network

Zhang

Ren

et al. 2015

Int. J. Mod. Phys. C

The critical execution paths play an important role in software system in terms of reducing the numbers of test date, detecting the vulnerabilities of software structure and analyzing software reliability. However, there are no e±cient methods to discover them so far. Thus in this paper, a complex network-based software algorithm is put forward to¯nd critical execution paths (FCEP) in software execution network. First, by analyzing the number of sources and sinks in FCEP, software execution network is divided into AOE subgraphs, and meanwhile, a Software Execution Network Serialization (SENS) approach is designed to generate execution path set in each AOE subgraph, which not only reduces ring structure's in°uence on path generation, but also guarantees the nodes' integrity in network. Second, according to a novel path similarity metric, similarity matrix is created to calculate the similarity among sets of path sequences. Third, an e±cient method is taken to cluster paths through similarity matrices, and the maximum-length path in each cluster is extracted as the critical execution path. At last, a set of critical execution paths is derived. The experimental results show that the FCEP algorithm is e±cient in mining critical execution path under software complex network.