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Abstract

This chapter presents the specification of dependability benchmarks for general-purpose operating systems with respect to application erroneous behavior, and shows examples of benchmark results obtained for various versions of Windows and Linux operating systems. The benchmark measures are: operating system robustness (as regards possible erroneous inputs provided by the application software to the operating system (OS) via the application programming interface), the OS reaction, and restart times in the presence of faults. Two workloads are used for implementing the benchmark: PostMark, a file system performance benchmark for operating systems, and the Java Virtual Machine (JVM) middleware, a software layer on top of the OS allowing applications in Java language to be platform independent.

Abstract

ADAPT is a tool that aims at easing the task of evaluating dependability measures in the context of modern model driven engineering processes based on AADL (Architecture Analysis and Design Language). Hence, its input is an AADL architectural model annotated with dependability-related information. Its output is a dependability evaluation model in the form of a Generalized Stochastic Petri Net (GSPN). The latter can be processed by existing dependability evaluation tools, to compute quantitative measures such as reliability, availability, etc.. ADAPT interfaces OSATE (the Open Source AADL Tool Environment) on the AADL side and SURF-2, on the dependability evaluation side. In addition, ADAPT provides the GSPN in XML/XMI format, which represents a gateway to other dependability evaluation tools, as the processing techniques for XML files allow it to be easily converted to a tool-specific GSPN.

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This paper summarizes the state of knowledge and ongoing research on methods and techniques for resilience evaluation, taking into account the resilience-scaling challenges and properties related to the ubiquitous computerized systems. We mainly focus on quantitative evaluation approaches and, in particular, on model-based evaluation techniques that are commonly used to evaluate and compare, from the dependability point of view, different architecture alternatives at the design stage. We outline some of the main modeling techniques aiming at mastering the largeness of analytical dependability models at the construction level. Actually, addressing the model largeness problem is important with respect to the investigation of the scalability of current techniques to meet the complexity challenges of ubiquitous systems. Finally we present two case studies in which some of the presented techniques are applied for modeling web services and General Packet Radio Service (GPRS) mobile telephone networks, as prominent examples of large and evolving systems.

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Performing dependability evaluation along with other analyses at architectural level allows both making architectural tradeoffs and predicting the effects of architectural decisions on the dependability of an application. This paper gives guidelines for building architectural dependability models for software systems using the AADL (Architecture Analysis and Design Language). It presents reusable modeling patterns for fault-tolerant applications and shows how the presented patterns can be used in the context of a subsystem of a real-life application.

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The aim of this paper is to provide qualitative models characterizing interdependencies related failures of two critical infrastructures: the electricity infrastructure and the associated information infrastructure. The interdependencies of these two infrastructures are increasing due to a growing connection of the power grid networks to the global information infrastructure, as a consequence of market deregulation and opening. These interdependencies increase the risk of failures. We focus on cascading, escalating and common-cause failures, which correspond to the main causes of failures due to interdependencies. We address failures in the electricity infrastructure, in combination with accidental failures in the information infrastructure, then we show briefly how malicious attacks in the information infrastructure can be addressed.

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