43,063 research outputs found
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
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
Specification Patterns for Robotic Missions
Mobile and general-purpose robots increasingly support our everyday life,
requiring dependable robotics control software. Creating such software mainly
amounts to implementing their complex behaviors known as missions. Recognizing
the need, a large number of domain-specific specification languages has been
proposed. These, in addition to traditional logical languages, allow the use of
formally specified missions for synthesis, verification, simulation, or guiding
the implementation. For instance, the logical language LTL is commonly used by
experts to specify missions, as an input for planners, which synthesize the
behavior a robot should have. Unfortunately, domain-specific languages are
usually tied to specific robot models, while logical languages such as LTL are
difficult to use by non-experts. We present a catalog of 22 mission
specification patterns for mobile robots, together with tooling for
instantiating, composing, and compiling the patterns to create mission
specifications. The patterns provide solutions for recurrent specification
problems, each of which detailing the usage intent, known uses, relationships
to other patterns, and---most importantly---a template mission specification in
temporal logic. Our tooling produces specifications expressed in the LTL and
CTL temporal logics to be used by planners, simulators, or model checkers. The
patterns originate from 245 realistic textual mission requirements extracted
from the robotics literature, and they are evaluated upon a total of 441
real-world mission requirements and 1251 mission specifications. Five of these
reflect scenarios we defined with two well-known industrial partners developing
human-size robots. We validated our patterns' correctness with simulators and
two real robots
Robustness-Driven Resilience Evaluation of Self-Adaptive Software Systems
An increasingly important requirement for certain classes of software-intensive systems is the ability to self-adapt their structure and behavior at run-time when reacting to changes that may occur to the system, its environment, or its goals. A major challenge related to self-adaptive software systems is the ability to provide assurances of their resilience when facing changes. Since in these systems, the components that act as controllers of a target system incorporate highly complex software, there is the need to analyze the impact that controller failures might have on the services delivered by the system. In this paper, we present a novel approach for evaluating the resilience of self-adaptive software systems by applying robustness testing techniques to the controller to uncover failures that can affect system resilience. The approach for evaluating resilience, which is based on probabilistic model checking, quantifies the probability of satisfaction of system properties when the target system is subject to controller failures. The feasibility of the proposed approach is evaluated in the context of an industrial middleware system used to monitor and manage highly populated networks of devices, which was implemented using the Rainbow framework for architecture-based self-adaptation
A compositional method for reliability analysis of workflows affected by multiple failure modes
We focus on reliability analysis for systems designed as workflow based compositions of components. Components are characterized by their failure profiles, which take into account possible multiple failure modes. A compositional calculus is provided to evaluate the failure profile of a composite system, given failure profiles of the components. The calculus is described as a syntax-driven procedure that synthesizes a workflows failure profile. The method is viewed as a design-time aid that can help software engineers reason about systems reliability in the early stage of development. A simple case study is presented to illustrate the proposed approach
- âŚ