18,844 research outputs found
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
Modeling and Analyzing Adaptive User-Centric Systems in Real-Time Maude
Pervasive user-centric applications are systems which are meant to sense the
presence, mood, and intentions of users in order to optimize user comfort and
performance. Building such applications requires not only state-of-the art
techniques from artificial intelligence but also sound software engineering
methods for facilitating modular design, runtime adaptation and verification of
critical system requirements.
In this paper we focus on high-level design and analysis, and use the
algebraic rewriting language Real-Time Maude for specifying applications in a
real-time setting. We propose a generic component-based approach for modeling
pervasive user-centric systems and we show how to analyze and prove crucial
properties of the system architecture through model checking and simulation.
For proving time-dependent properties we use Metric Temporal Logic (MTL) and
present analysis algorithms for model checking two subclasses of MTL formulas:
time-bounded response and time-bounded safety MTL formulas. The underlying idea
is to extend the Real-Time Maude model with suitable clocks, to transform the
MTL formulas into LTL formulas over the extended specification, and then to use
the LTL model checker of Maude. It is shown that these analyses are sound and
complete for maximal time sampling. The approach is illustrated by a simple
adaptive advertising scenario in which an adaptive advertisement display can
react to actions of the users in front of the display.Comment: In Proceedings RTRTS 2010, arXiv:1009.398
Extending the Real-Time Maude Semantics of Ptolemy to Hierarchical DE Models
This paper extends our Real-Time Maude formalization of the semantics of flat
Ptolemy II discrete-event (DE) models to hierarchical models, including modal
models. This is a challenging task that requires combining synchronous
fixed-point computations with hierarchical structure. The synthesis of a
Real-Time Maude verification model from a Ptolemy II DE model, and the formal
verification of the synthesized model in Real-Time Maude, have been integrated
into Ptolemy II, enabling a model-engineering process that combines the
convenience of Ptolemy II DE modeling and simulation with formal verification
in Real-Time Maude.Comment: In Proceedings RTRTS 2010, arXiv:1009.398
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
A Compositional Approach for Schedulability Analysis of Distributed Avionics Systems
This work presents a compositional approach for schedulability analysis of
Distributed Integrated Modular Avionics (DIMA) systems that consist of
spatially distributed ARINC-653 modules connected by a unified AFDX network. We
model a DIMA system as a set of stopwatch automata in UPPAAL to verify its
schedulability by model checking. However, direct model checking is infeasible
due to the large state space. Therefore, we introduce the compositional
analysis that checks each partition including its communication environment
individually. Based on a notion of message interfaces, a number of message
sender automata are built to model the environment for a partition. We define a
timed selection simulation relation, which supports the construction of
composite message interfaces. By using assume-guarantee reasoning, we ensure
that each task meets the deadline and that communication constraints are also
fulfilled globally. The approach is applied to the analysis of a concrete DIMA
system.Comment: In Proceedings MeTRiD 2018, arXiv:1806.09330. arXiv admin note: text
overlap with arXiv:1803.1105
Model Checking Classes of Metric LTL Properties of Object-Oriented Real-Time Maude Specifications
This paper presents a transformational approach for model checking two
important classes of metric temporal logic (MTL) properties, namely, bounded
response and minimum separation, for nonhierarchical object-oriented Real-Time
Maude specifications. We prove the correctness of our model checking
algorithms, which terminate under reasonable non-Zeno-ness assumptions when the
reachable state space is finite. These new model checking features have been
integrated into Real-Time Maude, and are used to analyze a network of medical
devices and a 4-way traffic intersection system.Comment: In Proceedings RTRTS 2010, arXiv:1009.398
Formal Verification of Probabilistic SystemC Models with Statistical Model Checking
Transaction-level modeling with SystemC has been very successful in
describing the behavior of embedded systems by providing high-level executable
models, in which many of them have inherent probabilistic behaviors, e.g.,
random data and unreliable components. It thus is crucial to have both
quantitative and qualitative analysis of the probabilities of system
properties. Such analysis can be conducted by constructing a formal model of
the system under verification and using Probabilistic Model Checking (PMC).
However, this method is infeasible for large systems, due to the state space
explosion. In this article, we demonstrate the successful use of Statistical
Model Checking (SMC) to carry out such analysis directly from large SystemC
models and allow designers to express a wide range of useful properties. The
first contribution of this work is a framework to verify properties expressed
in Bounded Linear Temporal Logic (BLTL) for SystemC models with both timed and
probabilistic characteristics. Second, the framework allows users to expose a
rich set of user-code primitives as atomic propositions in BLTL. Moreover,
users can define their own fine-grained time resolution rather than the
boundary of clock cycles in the SystemC simulation. The third contribution is
an implementation of a statistical model checker. It contains an automatic
monitor generation for producing execution traces of the
model-under-verification (MUV), the mechanism for automatically instrumenting
the MUV, and the interaction with statistical model checking algorithms.Comment: Journal of Software: Evolution and Process. Wiley, 2017. arXiv admin
note: substantial text overlap with arXiv:1507.0818
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
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