Compositional synthesis of temporal fault trees from state machines

Papadopoulos, Yiannis; Walker, Martin; Mahmud, Nidhal

Abstract

Dependability analysis of a dynamic system which is embedded with several complex interrelated components raises two main problems. First, it is difficult to represent in a single coherent and complete picture how the system and its constituent parts behave in conditions of failure. Second, the analysis can be unmanageable due to a considerable number of failure events, which increases with the number of components involved. To remedy this problem, in this paper we outline an analysis approach that converts failure behavioural models (state machines) to temporal fault trees (TFTs), which can then be analysed using Pandora -- a recent technique for introducing temporal logic to fault trees. The approach is compositional and potentially more scalable, as it relies on the synthesis of large system TFTs from smaller component TFTs. We show, by using a Generic Triple Redundant (GTR) system, how the approach enables a more accurate and full analysis of an increasingly complex system.

Citation

Papadopoulos, Y., Walker, M., & Mahmud, N. (2012). Compositional synthesis of temporal fault trees from state machines. Performance Evaluation Review, 39(4), 79-88. https://doi.org/10.1145/2185395.2185444

• Journal Article Type: Article
• Publication Date: Apr 9, 2012
• Deposit Date: Nov 13, 2014
• Publicly Available Date: Nov 23, 2017
• Journal: Performance evaluation review
• Print ISSN: 0163-5999
• Publisher: Association for Computing Machinery (ACM)
• Peer Reviewed: Peer Reviewed
• Volume: 39
• Issue: 4
• Pages: 79-88
• DOI: https://doi.org/10.1145/2185395.2185444
• Keywords: Computer Networks and Communications; Hardware and Architecture; Software
• Public URL: https://hull-repository.worktribe.com/output/465995
• Publisher URL: http://dl.acm.org/citation.cfm?doid=2185395.2185444
• Additional Information: Authors' accepted manuscript of article published in: Performance evaluation review, 2012, v.39, issue 4
• Contract Date: Nov 23, 2017