2,717 research outputs found
Modeling and analysis of distributed state space generation for timed Petri nets
The performance of distributed generation of the state space for timed Petri nets is rather sensitive to the type of analyzed nets. In order to analyze the performance of such an application, the distributed generation is represented by a timed Petri net and the behavior of this net is studied, using a simulation technique, for different combinations of modeling parameters
Test of preemptive real-time systems
Time Petri nets with stopwatches not only model system/environment interactions and time constraints. They further enable modeling of suspend/resume operations in real-time systems. Assuming the modelled systems are non deterministic and partially observable, the paper proposes a test generation approach which implements an online testing policy and outputs test results that are valid for the (part of the) selected environment. A relativized conformance relation named rswtioco is defined and a test generation algorithm is presented. The proposed approach is illustrated on an example
Formal Model Engineering for Embedded Systems Using Real-Time Maude
This paper motivates why Real-Time Maude should be well suited to provide a
formal semantics and formal analysis capabilities to modeling languages for
embedded systems. One can then use the code generation facilities of the tools
for the modeling languages to automatically synthesize Real-Time Maude
verification models from design models, enabling a formal model engineering
process that combines the convenience of modeling using an informal but
intuitive modeling language with formal verification. We give a brief overview
six fairly different modeling formalisms for which Real-Time Maude has provided
the formal semantics and (possibly) formal analysis. These models include
behavioral subsets of the avionics modeling standard AADL, Ptolemy II
discrete-event models, two EMF-based timed model transformation systems, and a
modeling language for handset software.Comment: In Proceedings AMMSE 2011, arXiv:1106.596
Dependability Analysis of Control Systems using SystemC and Statistical Model Checking
Stochastic Petri nets are commonly used for modeling distributed systems in
order to study their performance and dependability. This paper proposes a
realization of stochastic Petri nets in SystemC for modeling large embedded
control systems. Then statistical model checking is used to analyze the
dependability of the constructed model. Our verification framework allows users
to express a wide range of useful properties to be verified which is
illustrated through a case study
Testing real-time systems using TINA
The paper presents a technique for model-based black-box conformance testing of real-time systems using the Time Petri Net Analyzer TINA. Such test suites are derived from a prioritized time Petri net composed of two concurrent sub-nets specifying respectively the expected behaviour of the system under test and its environment.We describe how the toolbox TINA has been extended to support automatic generation of time-optimal test suites. The result is optimal in the sense that the set of test cases in the test suite have the shortest possible accumulated time to be executed. Input/output conformance serves as the notion of implementation correctness, essentially timed trace inclusion taking environment assumptions into account. Test cases selection is based either on using manually formulated test purposes or automatically from various coverage criteria specifying structural criteria of the model to be fulfilled by the test suite. We discuss how test purposes and coverage criterion are specified in the linear temporal logic SE-LTL, derive test sequences, and assign verdicts
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Variable grouping in multivariate time series via correlation
The decomposition of high-dimensional multivariate time series (MTS) into a number of low-dimensional MTS is a useful but challenging task because the number of possible dependencies between variables is likely to be huge. This paper is about a systematic study of the “variable groupings” problem in MTS. In particular, we investigate different methods of utilizing the information regarding correlations among MTS variables. This type of method does not appear to have been studied before. In all, 15 methods are suggested and applied to six datasets where there are identifiable mixed groupings of MTS variables. This paper describes the general methodology, reports extensive experimental results, and concludes with useful insights on the strength and weakness of this type of grouping metho
Parallel symbolic state-space exploration is difficult, but what is the alternative?
State-space exploration is an essential step in many modeling and analysis
problems. Its goal is to find the states reachable from the initial state of a
discrete-state model described. The state space can used to answer important
questions, e.g., "Is there a dead state?" and "Can N become negative?", or as a
starting point for sophisticated investigations expressed in temporal logic.
Unfortunately, the state space is often so large that ordinary explicit data
structures and sequential algorithms cannot cope, prompting the exploration of
(1) parallel approaches using multiple processors, from simple workstation
networks to shared-memory supercomputers, to satisfy large memory and runtime
requirements and (2) symbolic approaches using decision diagrams to encode the
large structured sets and relations manipulated during state-space generation.
Both approaches have merits and limitations. Parallel explicit state-space
generation is challenging, but almost linear speedup can be achieved; however,
the analysis is ultimately limited by the memory and processors available.
Symbolic methods are a heuristic that can efficiently encode many, but not all,
functions over a structured and exponentially large domain; here the pitfalls
are subtler: their performance varies widely depending on the class of decision
diagram chosen, the state variable order, and obscure algorithmic parameters.
As symbolic approaches are often much more efficient than explicit ones for
many practical models, we argue for the need to parallelize symbolic
state-space generation algorithms, so that we can realize the advantage of both
approaches. This is a challenging endeavor, as the most efficient symbolic
algorithm, Saturation, is inherently sequential. We conclude by discussing
challenges, efforts, and promising directions toward this goal
A hazard analysis via an improved timed colored petri net with time–space coupling safety constraint
AbstractPetri nets are graphical and mathematical tools that are applicable to many systems for modeling, simulation, and analysis. With the emergence of the concept of partitioning in time and space domains proposed in avionics application standard software interface (ARINC 653), it has become difficult to analyze time–space coupling hazards resulting from resource partitioning using classical or advanced Petri nets. In this paper, we propose a time–space coupling safety constraint and an improved timed colored Petri net with imposed time–space coupling safety constraints (TCCP-NET) to fill this requirement gap. Time–space coupling hazard analysis is conducted in three steps: specification modeling, simulation execution, and results analysis. A TCCP-NET is employed to model and analyze integrated modular avionics (IMA), a real-time, safety-critical system. The analysis results are used to verify whether there exist time–space coupling hazards at runtime. The method we propose demonstrates superior modeling of safety-critical real-time systems as it can specify resource allocations in both time and space domains. TCCP-NETs can effectively detect underlying time–space coupling hazards
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