Showing papers by "Joost-Pieter Katoen published in 2001"

Lectures on Formal Methods and Performance Analysis

Abstract: Formal Methods for Performance Evaluation.- Markovian Models for Performance and Dependability Evaluation.- to Stochastic Petri Nets.- Non-Markovian Analysis.- Process Algebra and Markov Chains.- Verification of Randomized Distributed Algorithms.- Constructing Automata from Temporal Logic Formulas: A Tutorial?.- Exploiting Structure in Solution: Decomposing Compositional Models.- Stochastic Activity Networks: Formal Definitions and Concepts?.- Distributed and Structured Analysis Approaches to Study Large and Complex Systems?.- General Distributions in Process Algebra.

Faster and Symbolic CTMC Model Checking

Abstract: This paper reports on the implementation and the experiments with symbolic model checking of continuous-time Markov chains using multi-terminal binary decision diagrams (MTBDDs). Properties are expressed in Continuous Stochastic Logic (CSL) [7] which includes the means to express both transient and steady-state performance measures. We show that all CSL operators can be treated using standard operations on MTBDDs, thus allowing a rather straightforward implementation of symbolic CSL model checking on existing MTBDD-based platforms such as the verifier PRISM. The main result of the paper is an improvement of O(N) in the time complexity of checking time-bounded until-formulas, where N is the number of states in the CTMC under consideration. This result yields a drastic speed-up in the verification time of model checking CTMCs, both in the symbolic and non-symbolic case.

Beyond Memoryless Distributions: Model Checking Semi-Markov Chains

Abstract: Recent investigations have shown that the automated verification of continuous-time Markov chains (CTMCs) against CSL (Continuous Stochastic Logic) can be performed in a rather efficient manner. The state holding time distributions in CTMCs are restricted to negative exponential distributions. This paper investigates model checking of semi-Markov chains (SMCs), a model in which state holding times are governed by general distributions. We report on the semantical issues of adopting CSL for specifying properties of SMCs and present model checking algorithms for this logic.

MoDeST - A Modelling and Description Language for Stochastic Timed Systems

Abstract: This paper presents a modelling language, called MoDeST, for describing the behaviour of discrete event systems. The language combines conventional programming constructs - such as iteration, alternatives, atomic statements, and exception handling - with means to describe complex systems in a compositional manner. In addition, MoDeST incorporates means to describe important phenomena such as non-determinism, probabilistic branching, and hard real-time as well as soft real-time (i.e., stochastic) aspects. The language is influenced by popular and user-friendly specification languages such as Promela, and deals with compositionality in a light-weight process-algebra style. Thus, MoDeST (i) covers a very broad spectrum of modelling concepts, (ii) possesses a rigid, process-algebra style semantics, and (iii) yet provides modern and flexible specification constructs.

Performance Evaluation: = (Process Algebra + Model Checking) × Markov Chains

Abstract: Markov chains are widely used in practice to determine system performance and reliability characteristics. The vast majority of applications considers continuous-time Markov chains (CTMCs). This tutorial paper shows how successful model specification and analysis techniques from concurrency theory can be applied to performance evaluation. The specification of CTMCs is supported by a stochastic process algebra, while the quantitative analysis of these models is tackled by means of model checking. Process algebra provides: (i) a high-level specification formalism for describing CTMCs in a precise, modular and constraint-oriented way, and (ii) means for the automated generation and aggregation of CTMCs. Temporal logic model checking provides: (i) a formalism to specify complex measures-of-in terest in a lucid, compact and flexible way, (ii) automated means to quantify these measures over CTMCs, and (iii) automated measure-driven aggregation (lumping) of CTMCs. Combining process algebra and model checking constitutes a coherent framework for performance evaluation based on CTMCs.

Modelling stochastic timed systems

Abstract: Real-time, performance and reliability aspects are of vital importance in the entire system design trajectory. Therefore, modelling techniques are needed that cover quantitative system aspects. This paper presents MoDeST, a modelling language that allows us to specify soft real-time constraints (i.e., stochastic timing) as well as hard real-time constraints. MoDeST combines conventional programming constructs – such as iteration, alternatives, atomic statements, and exception handling – with means to describe complex systems in a compositional manner. The language is influenced by popular and user-friendly specification languages, and deals with compositionality in a light-weight process-algebra style. In summary, MoDeST (i) covers a very broad spectrum of modelling concepts, (ii) possesses a rigid, process-algebra style semantics, and (iii) yet provides modern and flexible specification constructs.

Model Checking Dynamic Allocation and Deallocation

Abstract: This paper proposes Allocational Temporal Logic (ATL) as a formalism to express properties concerning the dynamic allocation (birth) and de-allocation (death) of entities, such as the objects in an object-based system. The logic is interpreted on History-Dependent Automata, extended with a symbolic representation for certain cases of unbounded allocation. The paper also presents a simple imperative language with primitive statements for (de)allocation, with an operational semantics, to demonstrate the kind of behaviour that can be modelled. The main contribution of the paper is a tableau-based model checking algorithm for ATL, along the lines of Lichtenstein and Pnueli's algorithm for LTL.

A model checker for performance and dependability properties

Abstract: Markov chains are widely used in the context of performance and reliability evaluation of systems of various nature. Model checking of such chains with respect to a given (branching) temporal logic formula has been proposed for both the discrete [8] and the continuous time setting [1], [3]. In this short paper, we describe the prototype model checker $E \vdash M C^2$ for discrete and continuous-time Markov chains, where properties are expressed in appropriate extensions of CTL.We illustrate the general benefits of this approach and discuss the structure of the tool.