Automatic instantiation of abstract tests on specific configurations for large critical control systems

Computer-based control systems have grown in size, complexity, distribution and criticality. In this paper a methodology is presented to perform an abstract testing of such large control systems in an efficient way: an abstract test is specified directly from system functional requirements and has to be instantiated in more test runs to cover a specific configuration, comprising any number of control entities (sensors, actuators and logic processes). Such a process is usually performed by hand for each installation of the control system, requiring a considerable time effort and being an error prone verification activity. To automate a safe passage from abstract tests, related to the so called generic software application, to any specific installation, an algorithm is provided, starting from a reference architecture and a state-based behavioural model of the control software. The presented approach has been applied to a railway interlocking system, demonstrating its feasibility and effectiveness in several years of testing experience

Semantic Support for Log Analysis of Safety-Critical Embedded Systems

Testing is a relevant activity for the development life-cycle of Safety Critical Embedded systems. In particular, much effort is spent for analysis and classification of test logs from SCADA subsystems, especially when failures occur. The human expertise is needful to understand the reasons of failures, for tracing back the errors, as well as to understand which requirements are affected by errors and which ones will be affected by eventual changes in the system design. Semantic techniques and full text search are used to support human experts for the analysis and classification of test logs, in order to speedup and improve the diagnosis phase. Moreover, retrieval of tests and requirements, which can be related to the current failure, is supported in order to allow the discovery of available alternatives and solutions for a better and faster investigation of the problem.Comment: EDCC-2014, BIG4CIP-2014, Embedded systems, testing, semantic discovery, ontology, big dat

MAGDA: A Mobile Agent based Grid Architecture

Mobile agents mean both a technology and a programming paradigm. They allow for a flexible approach which can alleviate a number of issues present in distributed and Grid-based systems, by means of features such as migration, cloning, messaging and other provided mechanisms. In this paper we describe an architecture (MAGDA – Mobile Agent based Grid Architecture) we have designed and we are currently developing to support programming and execution of mobile agent based application upon Grid systems

Automatic instantiation of abstract tests to specific configurations for large critical control systems

Computer-based control systems have grown in size, complexity, distribution and criticality. In this paper a methodology is presented to perform an ‘abstract testing’ of such large control systems in an efficient way: an abstract test is specified directly from system functional requirements and has to be instantiated in more test runs to cover a specific configuration, comprising any number of control entities (sensors, actuators and logic processes). Such a process is usually performed by hand for each installation of the control system, requiring a considerable time effort and being an error-prone verification activity. To automate a safe passage from abstract tests, related to the so-called generic software application, to any specific installation, an algorithm is provided, starting from a reference architecture and a statebased behavioural model of the control software. The presented approach has been applied to a railway interlocking system, demonstrating its feasibility and effectiveness in several years of testing experience

Advancing synthesis of decision tree-based multiple classifier systems: an approximate computing case study

AbstractSo far, multiple classifier systems have been increasingly designed to take advantage of hardware features, such as high parallelism and computational power. Indeed, compared to software implementations, hardware accelerators guarantee higher throughput and lower latency. Although the combination of multiple classifiers leads to high classification accuracy, the required area overhead makes the design of a hardware accelerator unfeasible, hindering the adoption of commercial configurable devices. For this reason, in this paper, we exploit approximate computing design paradigm to trade hardware area overhead off for classification accuracy. In particular, starting from trained DT models and employing precision-scaling technique, we explore approximate decision tree variants by means of multiple objective optimization problem, demonstrating a significant performance improvement targeting field-programmable gate array devices

A HIERARCHICAL DISTRIBUTED SHARED MEMORY PARALLEL BRANCH & BOUND APPLICATION WITH PVM AND OPENMP FOR MULTIPROCESSOR CLUSTERS

Branch&Bound (B&B) is a technique widely used to solve combinatorial optimization problems in physics and engineering science. In this paper we show how the combined use of PVM and OpenMP libraries can be a promising approach to exploit the intrinsic parallel nature of this class of application and to obtain efficient code for hybrid computational architectures. We described how both the shared memory and the distributed memory programming models can be applied to implement the same algorithm for the inter-nodes and intra-node parallelization. Some experimental tests on a local area network (LAN) of workstations are finally discussed

A Model Driven Approach to Water Resource Analysis based on Formal Methods and Model Transformation

AbstractSeveral frameworks have been proposed in literature in order to cope with critical infrastructure modelling issues, and almost all rely on simulation techniques. Anyway simulation is not enough for critical systems, where any problem may lead to consistent loss in money and even human lives. Formal methods are widely used in order to enact exhaustive analyses of these systems, but their complexity grows with system dimension and heterogeneity. In addition, experts in application domains could not be familiar with formal modelling techniques. A way to manage complexity of analysis is the use of Model Based Transformation techniques: analysts can express their models in the way they use to do and automatic algorithms translate original models into analysable ones, reducing analysis complexity in a completely transparent way.In this work we describe an automatic transformation algorithm generating hybrid automata for the analysis of a natural water supply system. We use real system located in the South of Italy as case study