14,564 research outputs found
Conditional Transition Systems with Upgrades
We introduce a variant of transition systems, where activation of transitions
depends on conditions of the environment and upgrades during runtime
potentially create additional transitions. Using a cornerstone result in
lattice theory, we show that such transition systems can be modelled in two
ways: as conditional transition systems (CTS) with a partial order on
conditions, or as lattice transition systems (LaTS), where transitions are
labelled with the elements from a distributive lattice. We define equivalent
notions of bisimilarity for both variants and characterise them via a
bisimulation game.
We explain how conditional transition systems are related to featured
transition systems for the modelling of software product lines. Furthermore, we
show how to compute bisimilarity symbolically via BDDs by defining an operation
on BDDs that approximates an element of a Boolean algebra into a lattice. We
have implemented our procedure and provide runtime results
Adaptable transition systems
We present an essential model of adaptable transition systems inspired by white-box approaches to adaptation and based on foundational models of component based systems. The key feature of adaptable transition systems are control propositions, imposing a clear separation between ordinary, functional behaviours and adaptive ones. We instantiate our approach on interface automata yielding adaptable interface automata, but it may be instantiated on other foundational models of component-based systems as well. We discuss how control propositions can be exploited in the specification and analysis of adaptive systems, focusing on various notions proposed in the literature, like adaptability, control loops, and control synthesis
Modelling and analyzing adaptive self-assembling strategies with Maude
Building adaptive systems with predictable emergent behavior is a challenging task and it is becoming a critical need. The research community has accepted the challenge by introducing approaches of various nature: from software architectures, to programming paradigms, to analysis techniques. We recently proposed a conceptual framework for adaptation centered around the role of control data. In this paper we show that it can be naturally realized in a reflective logical language like Maude by using the Reflective Russian Dolls model. Moreover, we exploit this model to specify, validate and analyse a prominent example of adaptive system: robot swarms equipped with self-assembly strategies. The analysis exploits the statistical model checker PVeStA
Probabilistic Model Checking for Energy Analysis in Software Product Lines
In a software product line (SPL), a collection of software products is
defined by their commonalities in terms of features rather than explicitly
specifying all products one-by-one. Several verification techniques were
adapted to establish temporal properties of SPLs. Symbolic and family-based
model checking have been proven to be successful for tackling the combinatorial
blow-up arising when reasoning about several feature combinations. However,
most formal verification approaches for SPLs presented in the literature focus
on the static SPLs, where the features of a product are fixed and cannot be
changed during runtime. This is in contrast to dynamic SPLs, allowing to adapt
feature combinations of a product dynamically after deployment. The main
contribution of the paper is a compositional modeling framework for dynamic
SPLs, which supports probabilistic and nondeterministic choices and allows for
quantitative analysis. We specify the feature changes during runtime within an
automata-based coordination component, enabling to reason over strategies how
to trigger dynamic feature changes for optimizing various quantitative
objectives, e.g., energy or monetary costs and reliability. For our framework
there is a natural and conceptually simple translation into the input language
of the prominent probabilistic model checker PRISM. This facilitates the
application of PRISM's powerful symbolic engine to the operational behavior of
dynamic SPLs and their family-based analysis against various quantitative
queries. We demonstrate feasibility of our approach by a case study issuing an
energy-aware bonding network device.Comment: 14 pages, 11 figure
Reusing Test-Cases on Different Levels of Abstraction in a Model Based Development Tool
Seamless model based development aims to use models during all phases of the
development process of a system. During the development process in a
component-based approach, components of a system are described at qualitatively
differing abstraction levels: during requirements engineering component models
are rather abstract high-level and underspecified, while during implementation
the component models are rather concrete and fully specified in order to enable
code generation. An important issue that arises is assuring that the concrete
models correspond to abstract models. In this paper, we propose a method to
assure that concrete models for system components refine more abstract models
for the same components. In particular we advocate a framework for reusing
testcases at different abstraction levels. Our approach, even if it cannot
completely prove the refinement, can be used to ensure confidence in the
development process. In particular we are targeting the refinement of
requirements which are represented as very abstract models. Besides a formal
model of our approach, we discuss our experiences with the development of an
Adaptive Cruise Control (ACC) system in a model driven development process.
This uses extensions which we implemented for our model-based development tool
and which are briefly presented in this paper.Comment: In Proceedings MBT 2012, arXiv:1202.582
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