Reliability assessment method of SOA architecture software system based on complex network

Author(s):  
Ming Yang ◽  
Feilong Wang ◽  
Shihai Wang ◽  
Daqing Li
2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Hebing Luan ◽  
Jiachen Wang ◽  
Guowei Ma ◽  
Ke Zhang

Roof cutting has long been a potential hazard factor in longwall panels in some diggings in China. Meanwhile, the key strata structural reliability, which provides an assessment on the stability of overlying roof strata, may be a significant reference for support design in underground coal mines. This paper aims to investigate a practical nonprobabilistic reliability assessment method on key strata. The mechanical tests and the hollow inclusion triaxial strain tests were conducted to measure relevant mechanical parameters and in situ stress. Furthermore, against the typical failure features in Datong Diggings, China, a shear failure mechanical model of key strata is proposed. Then, an allowable-safety-factor based nonprobabilistic stability probability assessment method is given. The sensitivity of geometrical dimensions and uncertainty levels of friction angle and cohesion are further studied. It is found that thickness and span of key strata have more dominative effect on key strata’s stability compared with the other factor and the increase of uncertainty levels results in decrease of stability probability.


Author(s):  
Petr Janas ◽  
Krejsa Martin

Abstract In probabilistic tasks, input random variables are often statistically dependent. This fact should be considered in correct computational procedures. In case of the newly developed Direct Optimized Probabilistic Calculation (DOProC), the statistically dependent variables can be expressed by the socalled multidimensional histograms, which can be used e.g. for probabilistic calculations and reliability assessment in the software system ProbCalc.


2014 ◽  
Vol 651-653 ◽  
pp. 1741-1747
Author(s):  
Xiao Lin Zhao ◽  
Gang Hao ◽  
Chang Zhen Hu ◽  
Zhi Qiang Li

With the increasing scale of software system, the interaction between software elements becomes more and more complex, which lead to the increased dirty data in running software system. This may reduce the system performance and cause system collapse. In this paper, we proposed a discovery method of the dirty data transmission path based on complex network. Firstly, the binary file is decompiled and the function call graph is drawn by using the source code. Then the software structure is described as a weighted directed graph based on the knowledge of complex network. In addition, the dirty data node is marked by using the power-law distribution characteristics of the scale-free network construction of complex network chart. Finally, we found the dirty data transmission path during software running process. The experimental results show the transmission path of dirty data is accurate, which confirmed the feasibility of the method.


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