20,151 research outputs found
A Formal Approach based on Fuzzy Logic for the Specification of Component-Based Interactive Systems
Formal methods are widely recognized as a powerful engineering method for the
specification, simulation, development, and verification of distributed
interactive systems. However, most formal methods rely on a two-valued logic,
and are therefore limited to the axioms of that logic: a specification is valid
or invalid, component behavior is realizable or not, safety properties hold or
are violated, systems are available or unavailable. Especially when the problem
domain entails uncertainty, impreciseness, and vagueness, the appliance of such
methods becomes a challenging task. In order to overcome the limitations
resulting from the strict modus operandi of formal methods, the main objective
of this work is to relax the boolean notion of formal specifications by using
fuzzy logic. The present approach is based on Focus theory, a model-based and
strictly formal method for componentbased interactive systems. The contribution
of this work is twofold: i) we introduce a specification technique based on
fuzzy logic which can be used on top of Focus to develop formal specifications
in a qualitative fashion; ii) we partially extend Focus theory to a fuzzy one
which allows the specification of fuzzy components and fuzzy interactions.
While the former provides a methodology for approximating I/O behaviors under
imprecision, the latter enables to capture a more quantitative view of
specification properties such as realizability.Comment: In Proceedings FESCA 2015, arXiv:1503.0437
Probabilistic Model-Based Safety Analysis
Model-based safety analysis approaches aim at finding critical failure
combinations by analysis of models of the whole system (i.e. software,
hardware, failure modes and environment). The advantage of these methods
compared to traditional approaches is that the analysis of the whole system
gives more precise results. Only few model-based approaches have been applied
to answer quantitative questions in safety analysis, often limited to analysis
of specific failure propagation models, limited types of failure modes or
without system dynamics and behavior, as direct quantitative analysis is uses
large amounts of computing resources. New achievements in the domain of
(probabilistic) model-checking now allow for overcoming this problem.
This paper shows how functional models based on synchronous parallel
semantics, which can be used for system design, implementation and qualitative
safety analysis, can be directly re-used for (model-based) quantitative safety
analysis. Accurate modeling of different types of probabilistic failure
occurrence is shown as well as accurate interpretation of the results of the
analysis. This allows for reliable and expressive assessment of the safety of a
system in early design stages
Quantitative Verification: Formal Guarantees for Timeliness, Reliability and Performance
Computerised systems appear in almost all aspects of our daily lives, often in safety-critical scenarios such as embedded control systems in cars and aircraft
or medical devices such as pacemakers and sensors. We are thus increasingly reliant on these systems working correctly, despite often operating in unpredictable or unreliable environments. Designers of such devices need ways to guarantee that they will operate in a reliable and efficient manner.
Quantitative verification is a technique for analysing quantitative aspects of a system's design, such as timeliness, reliability or performance. It applies formal methods, based on a rigorous analysis of a mathematical model of the system, to automatically prove certain precisely specified properties, e.g. ``the airbag will always deploy within 20 milliseconds after a crash'' or ``the probability of both sensors failing simultaneously is less than 0.001''.
The ability to formally guarantee quantitative properties of this kind is beneficial across a wide range of application domains. For example, in safety-critical systems, it may be essential to establish credible bounds on the probability with which certain failures or combinations of failures can occur. In embedded control systems, it is often important to comply with strict constraints on timing or resources. More generally, being able to derive guarantees on precisely specified levels of performance or efficiency is a valuable tool in the design of, for example, wireless networking protocols, robotic systems or power management algorithms, to name but a few.
This report gives a short introduction to quantitative verification, focusing in particular on a widely used technique called model checking, and its generalisation to the analysis of quantitative aspects of a system such as timing, probabilistic behaviour or resource usage.
The intended audience is industrial designers and developers of systems such as those highlighted above who could benefit from the application of quantitative verification,but lack expertise in formal verification or modelling
Applying Formal Methods to Networking: Theory, Techniques and Applications
Despite its great importance, modern network infrastructure is remarkable for
the lack of rigor in its engineering. The Internet which began as a research
experiment was never designed to handle the users and applications it hosts
today. The lack of formalization of the Internet architecture meant limited
abstractions and modularity, especially for the control and management planes,
thus requiring for every new need a new protocol built from scratch. This led
to an unwieldy ossified Internet architecture resistant to any attempts at
formal verification, and an Internet culture where expediency and pragmatism
are favored over formal correctness. Fortunately, recent work in the space of
clean slate Internet design---especially, the software defined networking (SDN)
paradigm---offers the Internet community another chance to develop the right
kind of architecture and abstractions. This has also led to a great resurgence
in interest of applying formal methods to specification, verification, and
synthesis of networking protocols and applications. In this paper, we present a
self-contained tutorial of the formidable amount of work that has been done in
formal methods, and present a survey of its applications to networking.Comment: 30 pages, submitted to IEEE Communications Surveys and Tutorial
QuantUM: Quantitative Safety Analysis of UML Models
When developing a safety-critical system it is essential to obtain an
assessment of different design alternatives. In particular, an early safety
assessment of the architectural design of a system is desirable. In spite of
the plethora of available formal quantitative analysis methods it is still
difficult for software and system architects to integrate these techniques into
their every day work. This is mainly due to the lack of methods that can be
directly applied to architecture level models, for instance given as UML
diagrams. Also, it is necessary that the description methods used do not
require a profound knowledge of formal methods. Our approach bridges this gap
and improves the integration of quantitative safety analysis methods into the
development process. All inputs of the analysis are specified at the level of a
UML model. This model is then automatically translated into the analysis model,
and the results of the analysis are consequently represented on the level of
the UML model. Thus the analysis model and the formal methods used during the
analysis are hidden from the user. We illustrate the usefulness of our approach
using an industrial strength case study.Comment: In Proceedings QAPL 2011, arXiv:1107.074
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