Showing papers by "Joost-Pieter Katoen published in 2002"
TL;DR: The main emphasis of this paper is the treatment of operational semantics, notions of equivalence, and (sound and complete) axiomatisations of these equivalences for different types of Markovian process algebras, where delays are governed by exponential distributions.
261 citations
23 Jun 2002
TL;DR: A number of computational procedures are presented to perform model checking of continuous stochastic reward logic (CSRL) over finite Markov reward models, thereby stressing their computational complexity and applicability from a practical point of view.
Abstract: Model checking has been introduced as an automated technique to verify whether functional properties, expressed in a formal logic like computational tree logic (CTL), do hold in a formally-specified system. We present a number of computational procedures to perform model checking of continuous stochastic reward logic (CSRL) over finite Markov reward models, thereby stressing their computational complexity (time and space) and applicability from a practical point of view (accuracy, stability). A case study in the area of ad hoc mobile computing under power constraints shows the merits of CSRL and the new computational procedures.
90 citations
Book•
17 Jan 2002TL;DR: In this article, a cross-fertilization of the field of formal methods, traditionally focused on functionality, with techniques from performance modeling and analysis has been proposed, including extensions of process algebra and Petri nets allowing automatic generation of performance models, the use of formal proof techniques to assess the correctness of randomized algorithms, and extensions of models checking techniques to analysis requirements automatically.
Abstract: Traditionally, models and methods for the analysis of the functional correctness of reactive systems and those for the analysis of their performance (and dependability) aspects have been studied by different research communities. However, in modern systems the difference between their functional features and their performance properties has blurred. During the last decade, this trend has motivated and increased interest in combining insights from the field of formal methods, traditionally focused on functionality, with techniques from performance modeling and analysis. Examples of this cross-fertilization are extensions of process algebra and Petri nets allowing for automatic generation of performance models, the use of formal proof techniques to assess the correctness of randomized algorithms, and extensions of models checking techniques to analysis requirements automatically.
47 citations
01 Jan 2002
TL;DR: This tutorial paper presents a logic-based specification technique to specify performance, dependability and performability measures-ofinterest and shows how for a given finite Markov chain (or Markov reward model) such measures can be evaluated in a fully automated way.
Abstract: Markov chains (and their extensions with rewards) have been widely used to determine performance, dependability and performability characteristics of computer communication systems, such as throughput, delay, mean time to failure, or the probability to accumulate at least a certain amount of reward in a given time.Due to the rapidly increasing size and complexity of systems, Markov chains and Markov reward models are difficult and cumbersome to specify by hand at the state-space level. Therefore, various specification formalisms, such as stochastic Petri nets and stochastic process algebras, have been developed to facilitate the specification of these models at a higher level of abstraction. Uptill now, however, the specification of the measure-of-interest is often done in an informal and relatively unstructured way. Furthermore, some measures-of-interest can not be expressed conveniently at all.In this tutorial paper, we present a logic-based specification technique to specify performance, dependability and performability measures-ofinterest and show how for a given finite Markov chain (or Markov reward model) such measures can be evaluated in a fully automated way. Particular emphasis will be given to so-called path-based measures and hierarchically-specified measures. For this purpose, we extend so-called model checking techniques to reason about discrete- and continuous-time Markov chains and their rewards. We also report on the use of techniques such as (compositional) model reduction and measure-driven state-space generation to combat the infamous state space explosion problem.
45 citations
17 Jan 2002
TL;DR: This paper presents a process algebra for the specification of stochastic discrete-event systems modeled as generalized semi-Markov chains (GSMCs), a novel mixture of timed automata and GSMCs, and discusses various notions of equivalence, present congruence results, and argue how an expansion law in the process algebra can be obtained.
Abstract: This paper is an informal tutorial on stochastic process algebras, i.e., process calculi where action occurrences may be subject to a delay that is governed by a (mostly continuous) random variable. Whereas most stochastic process algebras consider delays determined by negative exponential distributions, this tutorial is concerned with the integration of general, non-exponential distributions into a process algebraic setting. We discuss the issue of incorporating such distributions in an interleaving semantics, and present some existing solutions to this problem. In particular, we present a process algebra for the specification of stochastic discrete-event systems modeled as generalized semi-Markov chains (GSMCs). Using this language stochastic discrete-event systems can be described in an abstract and modular way. The operational semantics of this process algebra is given in terms of stochastic automata, a novel mixture of timed automata and GSMCs. We show that GSMCs are a proper subset of stochastic automata, discuss various notions of equivalence, present congruence results, treat equational reasoning, and argue how an expansion law in the process algebra can be obtained. As a case study, we specify the root contention phase within the standardized IEEE 1394 serial bus protocol and study the delay until root contention resolution. An overview of related work on general distributions in process algebra and a discussion of trends and future work complete this tutorial.
41 citations
09 Sep 2002
TL;DR: This paper introduces means to specify system randomness within UML statecharts, and to verify probabilistic temporal properties over such enhanced state charts which are called probabilistically UMLStatecharts.
Abstract: This paper introduces means to specify system randomness within UML statecharts, and to verify probabilistic temporal properties over such enhanced statecharts which we call probabilistic UML statecharts. To achieve this, we develop a general recipe to extend a statechart semantics with discrete probability distributions, resulting in Markov decision processes as semantic models. We apply this recipe to the requirements-level UML semantics of [8]. Properties of interest for probabilistic statecharts are expressed in PCTL, a probabilistic variant of CTL for processes that exhibit both non-determinism and probabilities. Verification is performed using the model checker PRISM. A model checking example shows the feasibility of the suggested approach.
39 citations
Book•
01 Jan 2002
TL;DR: In this paper, the authors present Alloy, a tool for modeling and analysis of real-time and probabilistic software systems, as well as a set of tools for future space missions.
Abstract: Invited Contributions.- Software Construction and Analysis Tools for Future Space Missions.- Alloy: A New Technology for Software Modelling.- Real-Time and Probabilistic Systems.- Improving the Verification of Timed Systems Using Influence Information.- Digitisation and Full Abstraction for Dense-Time Model Checking.- Probabilistic Symbolic Model Checking with PRISM: A Hybrid Approach.- Scheduling.- Timed Automata with Asynchronous Processes: Schedulability and Decidability.- Validating Timing Constraints of Dependent Jobs with Variable Execution Times in Distributed Real-Time Systems.- An Analysis of Zero-Clairvoyant Scheduling.- Preemptive Job-Shop Scheduling Using Stopwatch Automata.- Miscellaneous.- Explicit Modeling of Influences, and of Their Absence, in Distributed Systems.- A Functional Semantics of Attribute Grammars.- Software Verification.- Relative Completeness of Abstraction Refinement for Software Model Checking.- Towards the Automated Verification of Multithreaded Java Programs.- CLPS-B-A Constraint Solver for B.- Formal Verification of Functional Properties of an SCR-Style Software Requirements Specification Using PVS.- Infinite-State and Parametric Systems.- Beyond Parameterized Verification.- Resource-Constrained Model Checking of Recursive Programs.- Model Checking Large-Scale and Parameterized Resource Allocation Systems.- Model Checking: Logics and Algorithms.- Exploring Very Large State Spaces Using Genetic Algorithms.- Local Model-Checking of Modal Mu-Calculus on Acyclic Labeled Transition Systems.- The ForSpec Temporal Logic: A New Temporal Property-Specification Language.- Fine-Grain Conjunction Scheduling for Symbolic Reachability Analysis.- Model Checking and Testing.- A Temporal Logic Based Theory of Test Coverage and Generation.- Synthesizing Monitors for Safety Properties.- Adaptive Model Checking.- Partial-Order and Simulation Techniques.- Parallelisation of the Petri Net Unfolding Algorithm.- Black Box Unfolding with Local First Search.- Applicability of Fair Simulation.- Simulation as Coarsest Partition Problem.- Debugging with Model Checking.- Temporal Debugging for Concurrent Systems.- Fate and FreeWill in Error Traces.- Tool Papers.- TIMES b- A Tool for Modelling and Implementation of Embedded Systems.- Compositional Verification Using SVL Scripts.- STG: A Symbolic Test Generation Tool.- Real-Time Systems Design with PEP.
6 citations
TL;DR: The basis of model checking is an exhaustive state-space exploration to check whether the property is satisfied in each state of the model, thereby using effective methods (such as symbolic data structures, partial-order reduction, or clever hashing techniques) to combat the state- space explosion problem.