2,539 research outputs found
AADLib, A Library of Reusable AADL Models
The SAE Architecture Analysis and Design Language is now a well-established language for the description of critical embedded systems, but also cyber-physical ones. A wide range of analysis tools is already available, either as part of the OSATE tool chain, or separate ones.
A key missing elements of AADL is a set of reusable building blocks to help learning AADL concepts, but also experiment already existing tool chains on validated real-life examples.
In this paper, we present AADLib, a library of reusable model elements. AADLib is build on two pillars: 1/ a set of ready-to- use examples so that practitioners can learn more about the AADL language itself, but also experiment with existing tools. Each example comes with a full description of available analysis and expected results. This helps reducing the learning curve of the language. 2/ a set of reusable model elements that cover typical building blocks of critical systems: processors, networks, devices with a high level of fidelity so that the cost to start a new project is reduced.
AADLib is distributed under a Free/Open Source License to further disseminate the AADL language. As such, AADLib provides a convenient way to discover AADL concepts and tool chains, and learn about its features
Model-based dependability analysis : state-of-the-art, challenges and future outlook
Abstract: Over the past two decades, the study of model-based dependability analysis has gathered significant research interest. Different approaches have been developed to automate and address various limitations of classical dependability techniques to contend with the increasing complexity and challenges of modern safety-critical system. Two leading paradigms have emerged, one which constructs predictive system failure models from component failure models compositionally using the topology of the system. The other utilizes design models - typically state automata - to explore system behaviour through fault injection. This paper reviews a number of prominent techniques under these two paradigms, and provides an insight into their working mechanism, applicability, strengths and challenges, as well as recent developments within these fields. We also discuss the emerging trends on integrated approaches and advanced analysis capabilities. Lastly, we outline the future outlook for model-based dependability analysis
Collaborative Verification-Driven Engineering of Hybrid Systems
Hybrid systems with both discrete and continuous dynamics are an important
model for real-world cyber-physical systems. The key challenge is to ensure
their correct functioning w.r.t. safety requirements. Promising techniques to
ensure safety seem to be model-driven engineering to develop hybrid systems in
a well-defined and traceable manner, and formal verification to prove their
correctness. Their combination forms the vision of verification-driven
engineering. Often, hybrid systems are rather complex in that they require
expertise from many domains (e.g., robotics, control systems, computer science,
software engineering, and mechanical engineering). Moreover, despite the
remarkable progress in automating formal verification of hybrid systems, the
construction of proofs of complex systems often requires nontrivial human
guidance, since hybrid systems verification tools solve undecidable problems.
It is, thus, not uncommon for development and verification teams to consist of
many players with diverse expertise. This paper introduces a
verification-driven engineering toolset that extends our previous work on
hybrid and arithmetic verification with tools for (i) graphical (UML) and
textual modeling of hybrid systems, (ii) exchanging and comparing models and
proofs, and (iii) managing verification tasks. This toolset makes it easier to
tackle large-scale verification tasks
Bridging the Gap between Enumerative and Symbolic Model Checkers
We present a method to perform symbolic state space generation for languages with existing enumerative state generators. The method is largely independent from the chosen modelling language. We validated this on three different types of languages and tools: state-based languages (PROMELA), action-based process algebras (muCRL, mCRL2), and discrete abstractions of ODEs (Maple).\ud
Only little information about the combinatorial structure of the\ud
underlying model checking problem need to be provided. The key enabling data structure is the "PINS" dependency matrix. Moreover, it can be provided gradually (more precise information yield better results).\ud
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Second, in addition to symbolic reachability, the same PINS matrix contains enough information to enable new optimizations in state space generation (transition caching), again independent from the chosen modelling language. We have also based existing optimizations, like (recursive) state collapsing, on top of PINS and hint at how to support partial order reduction techniques.\ud
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Third, PINS allows interfacing of existing state generators to, e.g., distributed reachability tools. Thus, besides the stated novelties, the method we propose also significantly reduces the complexity of building modular yet still efficient model checking tools.\ud
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Our experiments show that we can match or even outperform existing tools by reusing their own state generators, which we have linked into an implementation of our ideas
The TASTE Toolset: turning human designed heterogeneous systems into computer built homogeneous software.
The TASTE tool-set results from spin-off studies of the ASSERT project, which started in 2004 with the objective to propose innovative and pragmatic solutions to develop real-time software. One of the primary targets was satellite flight software, but it appeared quickly that their characteristics were shared among various embedded systems. The solutions that we developed now comprise a process and several tools ; the development process is based on the idea that real-time, embedded systems are heterogeneous by nature and that a unique UML-like language was not helping neither their construction, nor their validation. Rather than inventing yet another "ultimate" language, TASTE makes the link between existing and mature technologies such as Simulink, SDL, ASN.1, C, Ada, and generates complete, homogeneous software-based systems that one can straightforwardly download and execute on a physical target. Our current prototype is moving toward a marketed product, and sequel studies are already in place to support, among others, FPGA systems
Developing Experimental Models for NASA Missions with ASSL
NASA's new age of space exploration augurs great promise for deep space
exploration missions whereby spacecraft should be independent, autonomous, and
smart. Nowadays NASA increasingly relies on the concepts of autonomic
computing, exploiting these to increase the survivability of remote missions,
particularly when human tending is not feasible. Autonomic computing has been
recognized as a promising approach to the development of self-managing
spacecraft systems that employ onboard intelligence and rely less on control
links. The Autonomic System Specification Language (ASSL) is a framework for
formally specifying and generating autonomic systems. As part of long-term
research targeted at the development of models for space exploration missions
that rely on principles of autonomic computing, we have employed ASSL to
develop formal models and generate functional prototypes for NASA missions.
This helps to validate features and perform experiments through simulation.
Here, we discuss our work on developing such missions with ASSL.Comment: 7 pages, 4 figures, Workshop on Formal Methods for Aerospace (FMA'09
An integrated model checking toolset for kernel P systems
P systems are the computational models introduced in the context of membrane computing, a computational paradigm within the more general area of unconventional computing. Kernel P (kP) systems are defined to unify the specification of different variants of P systems, motivated by challenging theoretical aspects and the need to model different problems. kP systems are supported by a software framework, called kPWORKBENCH, which integrates a set of related simulation and verification methodologies and tools. In this paper, we present an extension to kPWORKBENCH with a new model checking framework supporting the formal verification of kP system models. This framework supports both LTL and CTL properties. To make the property specification an easier task, we propose a property language, composed of natural language statements. We demonstrate our proposed methodology with an example
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