Nardone, Roberto (2013) A Model-Driven Approach to Quantitative Analysis of Critical Systems. [Tesi di dottorato]

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Abstract

Critical systems are present in our daily life and affect many aspects providing essential support to several human activities; they are employed in several application domains, providing support to economic activities, transportation, communication, health-care. Such systems must meet strict non-functional requirements, including dependability requirements, and should be able to cope with competitive market needs. Their criticality implies the necessity to meet several requirements, often dictated by international standards, whose fulfillment must be demonstrated in order to achieve necessary certifications. Quantitative evaluations are hence needed to assess and demonstrate compliance with target requirements, since design phases of the lifecycle. For this purpose modeling approaches have been investigated during the years; their aim is to have a model of the overall system which allows to assess and demonstrate these properties. It is commonly known that the adoption of formal models in industry, although if strongly recommended when not mandatory, is slowed down by difficulties dictated both by the complexity of the models (which reflects the complexity of the systems) and by the need to have skilled staff in the usage of formal languages. For this reason, also if the academic research trends have focused on complex modeling approaches and techniques, formal models are not so used in industries: in particular only combinatorial models are widely adopted, thanks to their intuitive representation. The great simplifications introduced by combinatorial models lead to approximated results, hence system designers do not trust in them. In the last years the need of a "model engineering" is noticed: there is the necessity to define appropriate methodologies and processes to support development activities of complex models, aiming at improving the model quality/cost ratio. In this way three main research trends have been introduced: formal models generation, multiformalism, and compositional approaches. This thesis aims at defining a methodology for quantitative analysis of critical system that can integrate Model-Based evaluations, conducted by using formal models, with Model-Driven Engineering (MDE) paradigms, taking advantage of the actual research trends. More in detail, according to such approach, critical systems properties can be assessed starting from high level models expressed in proper languages (usually called Domain Specific Modeling Languages - DSMLs), and defining automatic transformation chains, able to generate formal models. The methodology is implementable into cost-effective processes in order to reduce time-to-market specifically during verification stages of critical system development lifecycles. Such objective will be achieved by both improving usability and re-usability of typical Model-Driven artifacts. The adoption of this methodology for railway system dependability analysis may lead to an estimated costs reduction of approximately 30%. The usage of a high-level central language significantly decreases also the training time of new analysts, as they only need to learn the DSML usage (properly developed for the application domain). This thesis defines also two high-level modeling languages: the first, CIP_VAM, has been defined to model vulnerability aspects of physical infrastructures, while the second, DAM-Rail, allows the dependability modeling in railway domain. Another important contribution of this thesis is given in the definition of new methods and formal operators: in detail a reference model architecture for performability and Quality of Service evaluation is defined, as well as the formal concept of Model Template is introduced (to enable model reuse). At last two techniques which deals with scalability are addressed: stub and reduced models. Even if the focus is on quantitative evaluation, the proposed methodology is useful also for the complete design (based on centralized informations), hence it is possible to extend it for automatic generation of documents and, more generally, of all those artifacts which support system development. The proposed approach has been applied with different goals to case studies coming from three different domains: railway systems, conferencing systems, and sensor network. These systems have different and complementary properties in terms of number of involved components, scalability, etc. Produced models are described, and obtained results are shown and commented.

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