From Domain Models to Components - A Formal Transformation Approach Towards Dependable Software Development

Many academic, industrial, and government research units have unanimously acknowledged the importance of developing dependable software systems. At the same time they have also concurred on the difficulties and challenges to be surmounted in achieving the goal. The importance of domain analysis and linking domain models to software artifacts were also recognized by various researchers. However, no formal approach to domain analysis was attempted. The primary motivation for this thesis stems from this context. Component-based software engineering offers some attractive mechanisms to tackle the inherent complexity in developing dependable systems. Recently a formal approach has been put forth for such a development. This thesis provides a formal approach for domain analysis, and transforms the domain model to components desired by this development process. Formal Concept Analysis (FCA) is a mathematical theory for identifying and classifying concepts. This thesis taps its potential to formally analyze the domain in a software development context. It turns out that the approach presented in this thesis cannot be fully automated; nevertheless several useful contributions have been made. These include (1) capturing formal concepts and defining them in FCA; (2) defining composition rules to categorize formal concepts and their trustworthy properties; (3) integrating partial formal context tables to build the concept lattice; (4) specifying and developing a model transformation approach to construct trustworthy OWL ontology; (5) implementing a model transformation technique to generate the TADL specification of the reusable component-based system. The proposed approach is applied to CoCoME, as a benchmark case study in the domain of component-based development

A synthesis of logic and bio-inspired techniques in the design of dependable systems

Much of the development of model-based design and dependability analysis in the design of dependable systems, including software intensive systems, can be attributed to the application of advances in formal logic and its application to fault forecasting and verification of systems. In parallel, work on bio-inspired technologies has shown potential for the evolutionary design of engineering systems via automated exploration of potentially large design spaces. We have not yet seen the emergence of a design paradigm that effectively combines these two techniques, schematically founded on the two pillars of formal logic and biology, from the early stages of, and throughout, the design lifecycle. Such a design paradigm would apply these techniques synergistically and systematically to enable optimal refinement of new designs which can be driven effectively by dependability requirements. The paper sketches such a model-centric paradigm for the design of dependable systems, presented in the scope of the HiP-HOPS tool and technique, that brings these technologies together to realise their combined potential benefits. The paper begins by identifying current challenges in model-based safety assessment and then overviews the use of meta-heuristics at various stages of the design lifecycle covering topics that span from allocation of dependability requirements, through dependability analysis, to multi-objective optimisation of system architectures and maintenance schedules

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

A methodology for the generation of efficient error detection mechanisms

A dependable software system must contain error detection mechanisms and error recovery mechanisms. Software components for the detection of errors are typically designed based on a system specification or the experience of software engineers, with their efficiency typically being measured using fault injection and metrics such as coverage and latency. In this paper, we introduce a methodology for the design of highly efficient error detection mechanisms. The proposed methodology combines fault injection analysis and data mining techniques in order to generate predicates for efficient error detection mechanisms. The results presented demonstrate the viability of the methodology as an approach for the development of efficient error detection mechanisms, as the predicates generated yield a true positive rate of almost 100% and a false positive rate very close to 0% for the detection of failure-inducing states. The main advantage of the proposed methodology over current state-of-the-art approaches is that efficient detectors are obtained by design, rather than by using specification-based detector design or the experience of software engineers

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

On cost-effective reuse of components in the design of complex reconfigurable systems

Design strategies that benefit from the reuse of system components can reduce costs while maintaining or increasing dependability—we use the term dependability to tie together reliability and availability. D3H2 (aDaptive Dependable Design for systems with Homogeneous and Heterogeneous redundancies) is a methodology that supports the design of complex systems with a focus on reconfiguration and component reuse. D3H2 systematizes the identification of heterogeneous redundancies and optimizes the design of fault detection and reconfiguration mechanisms, by enabling the analysis of design alternatives with respect to dependability and cost. In this paper, we extend D3H2 for application to repairable systems. The method is extended with analysis capabilities allowing dependability assessment of complex reconfigurable systems. Analysed scenarios include time-dependencies between failure events and the corresponding reconfiguration actions. We demonstrate how D3H2 can support decisions about fault detection and reconfiguration that seek to improve dependability while reducing costs via application to a realistic railway case study