Applying Formal Methods to Gossiping Networks with mCRL and Groove

In this paper we explore the practical possibilities of using formal methods to analyze gossiping networks. In particular, we use mCRL and Groove to model the peer sampling service, and analyze it through a series of model transformations to CTMCs and finally MRMs. Our tools compute the expected value of various network quality indicators, such as average path lengths, over all possible system runs. Both transient and steady state analysis are supported. We compare our results with the simulation and emulation results found in [10]

Formal Analysis of a Fault-Tolerant Routing Algorithm for a Network-on-Chip

International audienceA fault-tolerant routing algorithm in Network-on-Chip architectures provides adaptivity for on-chip communications. Adding fault-tolerance adaptivity to a routing algorithm increases its design complexity and makes it prone to deadlock and other problems if improperly implemented. Formal verification techniques are needed to check the correctness of the design. This paper performs formal analysis on an extension of the link-fault tolerant Network-on-Chip architecture introduced by Wu et al. that supports multiflit wormhole routing. This paper describes several lessons learned during the process of constructing a formal model of this routing architecture. Finally, this paper presents how the deadlock freedom and tolerance to a single-link fault is verified for a two-by-two mesh version of this routing architecture

On-the-fly Uniformization of Time-Inhomogeneous Infinite Markov Population Models

This paper presents an on-the-fly uniformization technique for the analysis of time-inhomogeneous Markov population models. This technique is applicable to models with infinite state spaces and unbounded rates, which are, for instance, encountered in the realm of biochemical reaction networks. To deal with the infinite state space, we dynamically maintain a finite subset of the states where most of the probability mass is located. This approach yields an underapproximation of the original, infinite system. We present experimental results to show the applicability of our technique

A tutorial on interactive Markov chains

Interactive Markov chains (IMCs) constitute a powerful sto- chastic model that extends both continuous-time Markov chains and labelled transition systems. IMCs enable a wide range of modelling and analysis techniques and serve as a semantic model for many industrial and scientific formalisms, such as AADL, GSPNs and many more. Applications cover various engineering contexts ranging from industrial system-on-chip manufacturing to satellite designs. We present a survey of the state-of-the-art in modelling and analysis of IMCs.\ud We cover a set of techniques that can be utilised for compositional modelling, state space generation and reduction, and model checking. The significance of the presented material and corresponding tools is highlighted through multiple case studies

Reduction and Abstraction Techniques for BIP

Reduction and abstraction techniques have been proposed to address the state space explosion problem in verification. In this paper, we present reduction and abstraction techniques for component-based systems modeled in BIP (Behavior, Interaction and Priority). Given a BIP system consisting of several atomic components, we compute the product of two selected atomic components. The product operation often exposes opportunities for constant propagation in the product component that were hidden originally. Moreover, the product operation introduces states that are branching bisimilar. Our method detects and merges those states resulting in a behavior that may overapproximate the original one. The presented method is fully implemented. Our results show a drastic improvement in verifying BIP systems

A compositional semantics for Dynamic Fault Trees in terms of Interactive Markov Chains

Dynamic fault trees (DFTs) are a versatile and common formalism to model and analyze the reliability of computer-based systems. This paper presents a formal semantics of DFTs in terms of input/output interactive Markov chains (I/O-IMCs), which extend continuous-time Markov chains with discrete input, output and internal actions. This semantics provides a rigorous basis for the analysis of DFTs. Our semantics is fully compositional, that is, the semantics of a DFT is expressed in terms of the semantics of its elements (i.e. basic events and gates). This enables an efficient analysis of DFTs through compositional aggregation, which helps to alleviate the state-space explosion problem by incrementally building the DFT state space. We have implemented our methodology by developing a tool, and showed, through four case studies, the feasibility of our approach and its effectiveness in reducing the state space to be analyzed

Architectural dependability evaluation with Arcade ∗

This paper proposes a formally well-rooted and extensible framework for dependability evaluation: Arcade (architectural dependability evaluation). It has been designed to combine the strengths of previous approaches to the evaluation of dependability. A key feature is its formal semantics in terms of Input/Output-Interactive Markov Chains, which enables both compositional modeling and compositional state space generation and reduction. The latter enables great computational reductions for many models. The Arcade approach is extensible, hence adaptable to new circumstances or application areas. The paper introduces the new modeling approach, discusses its formal semantics and illustrates its use with two case studies.