1. Reliability Assessment Model of IMA Partition Software Using Stochastic Petri Nets
- Author
-
Wu Zhijun, Ma Haolin, and Yue Meng
- Subjects
stochastic petri nets ,General Computer Science ,Computer science ,Reliability block diagram ,02 engineering and technology ,partition software ,ARINC 653 ,Software ,0203 mechanical engineering ,0202 electrical engineering, electronic engineering, information engineering ,General Materials Science ,Fault tree analysis ,020301 aerospace & aeronautics ,reliability ,Finite-state machine ,business.industry ,020208 electrical & electronic engineering ,General Engineering ,Computer Science::Software Engineering ,Integrated modular avionics ,Failure rate ,Partition (database) ,Software quality ,fault tree analysis ,Stochastic Petri net ,lcsh:Electrical engineering. Electronics. Nuclear engineering ,business ,lcsh:TK1-9971 ,Algorithm - Abstract
In order to reduce the failure rate of Integrated Modular Avionics (IMA) partition software, due to the reliability block diagram (RBD) method, fault tree analysis (FTA) method and GO method cannot describe the state transition process of partition software, according to the ARINC 653 standard and the actual running status of the partition software, this paper determines the state machine and conversion delay of the partition software, and establishes the stochastic Petri nets (SPN) reliability quantitative model of the partition software. By proving that each transition in the SPN model of the partition software approximately obeying exponential distribution, and according to the reachable state tree of the SPN isomorphic to a homogeneous Markov chain (MC), the steady-state probability of the partition software in the fault state is calculated to be $5.2778^\ast 10^{-9}$ by using MC stochastic process theory. The factors affecting the reliability of the partition software are obtained, and the sensitivity of each factor to the model is studied. Finally, the relevant conclusions are drawn to provide guidance for improving the reliability of partition software.
- Published
- 2021