Confluence reduction for Markov automata

Markov automata are a novel formalism for specifying systems exhibiting nondeterminism, probabilistic choices and Markovian rates. Recently, the process algebra MAPA was introduced to efficiently model such systems. As always, the state space explosion threatens the analysability of the models generated by such specifications. We therefore introduce confluence reduction for Markov automata, a powerful reduction technique to keep these models small. We define the notion of confluence directly on Markov automata, and discuss how to syntactically detect confluence on the MAPA language as well. That way, Markov automata generated by MAPA specifications can be reduced on-the-fly while preserving divergence-sensitive branching bisimulation. Three case studies demonstrate the significance of our approach, with reductions in analysis time up to an order of magnitude

Advancing Dynamic Fault Tree Analysis

This paper presents a new state space generation approach for dynamic fault trees (DFTs) together with a technique to synthesise failures rates in DFTs. Our state space generation technique aggressively exploits the DFT structure --- detecting symmetries, spurious non-determinism, and don't cares. Benchmarks show a gain of more than two orders of magnitude in terms of state space generation and analysis time. Our approach supports DFTs with symbolic failure rates and is complemented by parameter synthesis. This enables determining the maximal tolerable failure rate of a system component while ensuring that the mean time of failure stays below a threshold

DFTCalc: reliability centered maintenance via fault tree analysis (tool paper)

Reliability, availability, maintenance and safety (RAMS) analysis is essential in the evaluation of safety critical systems like nuclear power plants and the railway infrastructure. A widely used methodology within RAMS analysis are fault trees, representing failure propagations throughout a system. We present DFTCalc, a tool-set to conduct quantitative analysis on dynamic fault trees including the effect of a maintenance strategy on the system dependability

Towards Realizability Checking of Contracts using Theories

Virtual integration techniques focus on building architectural models of systems that can be analyzed early in the design cycle to try to lower cost, reduce risk, and improve quality of complex embedded systems. Given appropriate architectural descriptions and compositional reasoning rules, these techniques can be used to prove important safety properties about the architecture prior to system construction. Such proofs build from "leaf-level" assume/guarantee component contracts through architectural layers towards top-level safety properties. The proofs are built upon the premise that each leaf-level component contract is realizable; i.e., it is possible to construct a component such that for any input allowed by the contract assumptions, there is some output value that the component can produce that satisfies the contract guarantees. Without engineering support it is all too easy to write leaf-level components that can't be realized. Realizability checking for propositional contracts has been well-studied for many years, both for component synthesis and checking correctness of temporal logic requirements. However, checking realizability for contracts involving infinite theories is still an open problem. In this paper, we describe a new approach for checking realizability of contracts involving theories and demonstrate its usefulness on several examples.Comment: 15 pages, to appear in NASA Formal Methods (NFM) 201

Automatic Generation of Failure Scenarios for SoC

International audienceAs process technology downscales, testing difficulties and susceptibility of circuits to random hardware faults arise. This trend, combined with increasing complexity of functions to be performed by Systems-on-Chip, poses crucial concerns when system engineers have to quantify the dependability achieved by their SoC design. In this paper we propose an extension of the existing approaches to the fault analysis of SoCs describing (1) an algorithm for the automatic generation of failure scenarios based on Bounded Model Checking (BMC) (2) a methodology and Simulink-based tool for the automatic execution of SoC safety analysis and (3) an application of the proposed analysis flow to a concrete SoC use case

MeGARA: Menu-based Game Abstraction and Abstraction Refinement of Markov Automata

Markov automata combine continuous time, probabilistic transitions, and nondeterminism in a single model. They represent an important and powerful way to model a wide range of complex real-life systems. However, such models tend to be large and difficult to handle, making abstraction and abstraction refinement necessary. In this paper we present an abstraction and abstraction refinement technique for Markov automata, based on the game-based and menu-based abstraction of probabilistic automata. First experiments show that a significant reduction in size is possible using abstraction.Comment: In Proceedings QAPL 2014, arXiv:1406.156

compass 3 0

COMPASS (COrrectness, Modeling and Performance of AeroSpace Systems) is an international research effort aiming to ensure system-level correctness, safety, dependability and performability of on-board computer-based aerospace systems. In this paper we present COMPASS 3.0, which brings together the results of various development projects since the original inception of COMPASS. Improvements have been made both to the frontend, supporting an updated modeling language and user interface, as well as to the backend, by adding new functionalities and improving the existing ones. New features include Timed Failure Propagation Graphs, contract-based analysis, hierarchical fault tree generation, probabilistic analysis of non-deterministic models and statistical model checking

Symbolic Model Checking and Safety Assessment of Altarica models

Altarica is a language used to describe critical systems. In this paper we present a novel approach to the analysis of Altarica models, based on a translation into an extended version of NuSMV. This approach opens up the possibility to carry out functional verification and safety assessment with symbolic techniques. An experimental evaluation on a set of industrial case studies demonstrates the advantages of the approach over currently available tools.

Verification of Open Interactive Markov Chains

Interactive Markov chains (IMC) are compositional behavioral models extending both labeled transition systems and continuous-time Markov chains. IMC pair modeling convenience - owed to compositionality properties - with effective verification algorithms and tools - owed to Markov properties. Thus far however, IMC verification did not consider compositionality properties, but considered closed systems. This paper discusses the evaluation of IMC in an open and thus compositional interpretation. For this we embed the IMC into a game that is played with the environment. We devise algorithms that enable us to derive bounds on reachability probabilities that are assured to hold in any composition context

Model-based dependability analysis : state-of-the-art, challenges and future outlook

Abstract: Over the past two decades, the study of model-based dependability analysis has gathered significant research interest. Different approaches have been developed to automate and address various limitations of classical dependability techniques to contend with the increasing complexity and challenges of modern safety-critical system. Two leading paradigms have emerged, one which constructs predictive system failure models from component failure models compositionally using the topology of the system. The other utilizes design models - typically state automata - to explore system behaviour through fault injection. This paper reviews a number of prominent techniques under these two paradigms, and provides an insight into their working mechanism, applicability, strengths and challenges, as well as recent developments within these fields. We also discuss the emerging trends on integrated approaches and advanced analysis capabilities. Lastly, we outline the future outlook for model-based dependability analysis