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

Dependability modeling and evaluation – From AADL to stochastic Petri nets

Conduire des analyses de sûreté de fonctionnement conjointement avec d'autres analyses au niveau architectural permet à la fois de prédire les effets des décisions architecturales sur la sûreté de fonctionnement du système et de faire des compromis. Par conséquent, les industriels et les universitaires se concentrent sur la définition d'approches d'ingénierie guidées par des modèles (MDE) et sur l'intégration de diverses analyses dans le processus de développement. AADL (Architecture Analysis and Design Language) a prouvé son aptitude pour la modélisation d'architectures et ce langage est actuellement jugé efficace par les industriels dans de telles approches. Notre contribution est un cadre de modélisation permettant la génération de modèles analytiques de sûreté de fonctionnement à partir de modèles AADL dans l‘objectif de faciliter l'évaluation de mesures de sûreté de fonctionnement comme la fiabilité et la disponibilité. Nous proposons une approche itérative de modélisation. Dans ce contexte, nous fournissons un ensemble de sous-modèles génériques réutilisables pour des architectures tolérantes aux fautes. Le modèle AADL de sûreté de fonctionnement est transformé en un RdPSG (Réseau de Petri Stochastique Généralisé) en appliquant des règles de transformation de modèle. Nous avons implémenté un outil de transformation automatique. Le RdPSG résultant peut être traité par des outils existants pour obtenir des mesures de sûreté de fonctionnement. L'approche est illustrée sur un ensemble du Système Informatique Français de Contrôle de Trafic Aérien. ABSTRACT : Performing dependability evaluation along with other analyses at architectural level allows both predicting the effects of architectural decisions on the dependability of a system and making tradeoffs. Thus, both industry and academia focus on defining model driven engineering (MDE) approaches and on integrating several analyses in the development process. AADL (Architecture Analysis and Design Language) has proved to be efficient for architectural modeling and is considered by industry in the context presented above. Our contribution is a modeling framework allowing the generation of dependability-oriented analytical models from AADL models, to facilitate the evaluation of dependability measures, such as reliability or availability. We propose an iterative approach for system dependability modeling using AADL. In this context, we also provide a set of reusable modeling patterns for fault tolerant architectures. The AADL dependability model is transformed into a GSPN (Generalized Stochastic Petri Net) by applying model transformation rules. We have implemented an automatic model transformation tool. The resulting GSPN can be processed by existing tools to obtain dependability measures. The modeling approach is illustrated on a subsystem of the French Air trafic Control System

Software dependability modeling using an industry-standard architecture description language

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

Modelling, reduction and analysis of Markov automata (extended version)

Markov automata (MA) constitute an expressive continuous-time compositional modelling formalism. They appear as semantic backbones for engineering frameworks including dynamic fault trees, Generalised Stochastic Petri Nets, and AADL. Their expressive power has thus far precluded them from effective analysis by probabilistic (and statistical) model checkers, stochastic game solvers, or analysis tools for Petri net-like formalisms. This paper presents the foundations and underlying algorithms for efficient MA modelling, reduction using static analysis, and most importantly, quantitative analysis. We also discuss implementation pragmatics of supporting tools and present several case studies demonstrating feasibility and usability of MA in practice

Multi-Dimensional Model Based Engineering for Performance Critical Computer Systems Using the AADL

International audienceThe Architecture Analysis & Design Language, (AADL), Society of Automotive Engineers (SAE), AS5506, was developed to support quantitative analysis of the runtime architecture of the embedded software system in computer systems with multiple critical operational properties, such as responsiveness, safety-criticality, security, and reliability by allowing a model of the system to be annotated with information relevant to each of these quality concerns and AADL to be extended with analysis-specific properties. It supports modelling of the embedded software runtime architecture, the computer system hardware, and the interface to the physical environment of embedded computer systems and system of systems. It was designed to support a full Model Based Engineering lifecycle including system specification, analysis, system tuning, integration, and upgrade by supporting modelling and analysis at multiple levels of fidelity. A system can be automatically integrated from AADL models when fully specified and when source code is provided for the software components

Dynamic model-based safety analysis: from state machines to temporal fault trees

Finite state transition models such as State Machines (SMs) have become a prevalent paradigm for the description of dynamic systems. Such models are well-suited to modelling the behaviour of complex systems, including in conditions of failure, and where the order in which failures and fault events occur can affect the overall outcome (e.g. total failure of the system). For the safety assessment though, the SM failure behavioural models need to be converted to analysis models like Generalised Stochastic Petri Nets (GSPNs), Markov Chains (MCs) or Fault Trees (FTs). This is particularly important if the transformed models are supported by safety analysis tools.This thesis, firstly, identifies a number of problems encountered in current safety analysis techniques based on SMs. One of the existing approaches consists of transforming the SMs to analysis-supported state-transition formalisms like GSPNs or MCs, which are very powerful in capturing the dynamic aspects and in the evaluation of safety measures. But in this approach, qualitative analysis is not encouraged; here the focus is primarily on probabilistic analysis. Qualitative analysis is particularly important when probabilistic data are not available (e.g., at early stages of design). In an alternative approach though, the generation of combinatorial, Boolean FTs has been applied to SM-based models. FTs are well-suited to qualitative analysis, but cannot capture the significance of the temporal order of events expressed by SMs. This makes the approach potentially error prone for the analysis of dynamic systems. In response, we propose a new SM-based safety analysis technique which converts SMs to Temporal Fault Trees (TFTs) using Pandora — a recent technique for introducing temporal logic to FTs. Pandora provides a set of temporal laws, which allow the significance of the SM temporal semantics to be preserved along the logical analysis, and thereby enabling a true qualitative analysis of a dynamic system. The thesis develops algorithms for conversion of SMs to TFTs. It also deals with the issue of scalability of the approach by proposing a form of compositional synthesis in which system large TFTs can be generated from individual component SMs using a process of composition. This has the dual benefits of allowing more accurate analysis of different sequences of faults, and also helping to reduce the cost of performing temporal analysis by producing smaller, more manageable TFTs via the compositionality.The thesis concludes that this approach can potentially address limitations of earlier work and thus help to improve the safety analysis of increasingly complex dynamic safety-critical systems

Analysis of Timed and Long-Run Objectives for Markov Automata

Markov automata (MAs) extend labelled transition systems with random delays and probabilistic branching. Action-labelled transitions are instantaneous and yield a distribution over states, whereas timed transitions impose a random delay governed by an exponential distribution. MAs are thus a nondeterministic variation of continuous-time Markov chains. MAs are compositional and are used to provide a semantics for engineering frameworks such as (dynamic) fault trees, (generalised) stochastic Petri nets, and the Architecture Analysis & Design Language (AADL). This paper considers the quantitative analysis of MAs. We consider three objectives: expected time, long-run average, and timed (interval) reachability. Expected time objectives focus on determining the minimal (or maximal) expected time to reach a set of states. Long-run objectives determine the fraction of time to be in a set of states when considering an infinite time horizon. Timed reachability objectives are about computing the probability to reach a set of states within a given time interval. This paper presents the foundations and details of the algorithms and their correctness proofs. We report on several case studies conducted using a prototypical tool implementation of the algorithms, driven by the MAPA modelling language for efficiently generating MAs.Comment: arXiv admin note: substantial text overlap with arXiv:1305.705

From software architecture to analysis models and back: Model-driven refactoring aimed at availability improvement

Abstract Context With the ever-increasing evolution of software systems, their architecture is subject to frequent changes due to multiple reasons, such as new requirements. Appropriate architectural changes driven by non-functional requirements are particularly challenging to identify because they concern quantitative analyses that are usually carried out with specific languages and tools. A considerable number of approaches have been proposed in the last decades to derive non-functional analysis models from architectural ones. However, there is an evident lack of automation in the backward path that brings the analysis results back to the software architecture. Objective In this paper, we propose a model-driven approach to support designers in improving the availability of their software systems through refactoring actions. Method The proposed framework makes use of bidirectional model transformations to map UML models onto Generalized Stochastic Petri Nets (GSPN) analysis models and vice versa. In particular, after availability analysis, our approach enables the application of model refactoring, possibly based on well-known fault tolerance patterns, aimed at improving the availability of the architectural model. Results We validated the effectiveness of our approach on an Environmental Control System. Our results show that the approach can generate: (i) an analyzable availability model from a software architecture description, and (ii) valid software architecture models back from availability models. Finally, our results highlight that the application of fault tolerance patterns significantly improves the availability in each considered scenario. Conclusion The approach integrates bidirectional model transformation and fault tolerance techniques to support the availability-driven refactoring of architectural models. The results of our experiment showed the effectiveness of the approach in improving the software availability of the system

The SAE Architecture Analysis & Design Language (AADL) A Standard for Engineering Performance Critical Systems

International audienceThe Society of Automotive Engineers (SAE) Architecture Analysis & Design Language, AS5506, provides a means for the formal specification of the hardware and software architecture of embedded computer systems and system of systems. It was designed to support a full Model Based Development lifecycle including system specification, analysis, system tuning, integration, and upgrade over the lifecycle. It was designed to support the integration of multiple forms of analyses and to be extensible in a standard way for additional analysis approaches. A system can be automatically integrated from AADL models when fully specified and when source code is provided for the software components. Analysis of large complex systems has been demonstrated in the avionics domain

Modeling and Analysis of Mixed Synchronous/Asynchronous Systems

Practical safety-critical distributed systems must integrate safety critical and non-critical data in a common platform. Safety critical systems almost always consist of isochronous components that have synchronous or asynchronous interface with other components. Many of these systems also support a mix of synchronous and asynchronous interfaces. This report presents a study on the modeling and analysis of asynchronous, synchronous, and mixed synchronous/asynchronous systems. We build on the SAE Architecture Analysis and Design Language (AADL) to capture architectures for analysis. We present preliminary work targeted to capture mixed low- and high-criticality data, as well as real-time properties in a common Model of Computation (MoC). An abstract, but representative, test specimen system was created as the system to be modeled