Data structures and network algorithms
Data structures and network algorithms
An Algorithm for Determining the Fault Diagnosability of a System
IEEE Transactions on Computers
Graph Algorithms
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
The complexity of system-level fault diagnosis and diagnosability
The complexity of system-level fault diagnosis and diagnosability
Sequential Diagnosability is Co-NP Complete
IEEE Transactions on Computers
The consensus problem in fault-tolerant computing
ACM Computing Surveys (CSUR)
On Asymmetric Invalidation with Partial Tests
IEEE Transactions on Computers
Weighted Diagnosis with Asymmetric Invalidation
IEEE Transactions on Computers
On Single-Fault Set Diagnosability in the PMC Model
IEEE Transactions on Computers
| Hi-index | 14.99 |
The concepts of the PMC and BGM self-diagnosing system models of F. P. Preparata et al. (1967) and F. Barsi et al. (1976), respectively, including the notions of fault sets, consistency, and diagnosability number, are reviewed. Two one-step diagnosability algorithms are applied, one to the PMC model and the other to the BGM model. In both models, one-step diagnosability refers to a system's ability to determine all the faulty units from single collection of test results. Using the letters n, m, and tau to denote the number of units, the number of tests, and the diagnosability number, respectively, it is shown that in the BGM model the algorithm has a complexity of O(n tau /sup 2//log tau ), and, in the PMC model, the algorithm has a complexity of O(n tau /sup 2.5/).