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

Realising the open virtual commissioning of modular automation systems

To address the challenges in the automotive industry posed by the need to rapidly manufacture more product variants, and the resultant need for more adaptable production systems, radical changes are now required in the way in which such systems are developed and implemented. In this context, two enabling approaches for achieving more agile manufacturing, namely modular automation systems and virtual commissioning, are briefly reviewed in this contribution. Ongoing research conducted at Loughborough University which aims to provide a modular approach to automation systems design coupled with a virtual engineering toolset for the (re)configuration of such manufacturing automation systems is reported. The problems faced in the virtual commissioning of modular automation systems are outlined. AutomationML - an emerging neutral data format which has potential to address integration problems is discussed. The paper proposes and illustrates a collaborative framework in which AutomationML is adopted for the data exchange and data representation of related models to enable efficient open virtual prototype construction and virtual commissioning of modular automation systems. A case study is provided to show how to create the data model based on AutomationML for describing a modular automation system

You Cannot Fix What You Cannot Find! An Investigation of Fault Localization Bias in Benchmarking Automated Program Repair Systems

Properly benchmarking Automated Program Repair (APR) systems should contribute to the development and adoption of the research outputs by practitioners. To that end, the research community must ensure that it reaches significant milestones by reliably comparing state-of-the-art tools for a better understanding of their strengths and weaknesses. In this work, we identify and investigate a practical bias caused by the fault localization (FL) step in a repair pipeline. We propose to highlight the different fault localization configurations used in the literature, and their impact on APR systems when applied to the Defects4J benchmark. Then, we explore the performance variations that can be achieved by `tweaking' the FL step. Eventually, we expect to create a new momentum for (1) full disclosure of APR experimental procedures with respect to FL, (2) realistic expectations of repairing bugs in Defects4J, as well as (3) reliable performance comparison among the state-of-the-art APR systems, and against the baseline performance results of our thoroughly assessed kPAR repair tool. Our main findings include: (a) only a subset of Defects4J bugs can be currently localized by commonly-used FL techniques; (b) current practice of comparing state-of-the-art APR systems (i.e., counting the number of fixed bugs) is potentially misleading due to the bias of FL configurations; and (c) APR authors do not properly qualify their performance achievement with respect to the different tuning parameters implemented in APR systems.Comment: Accepted by ICST 201

The cyber-physical e-machine manufacturing system : virtual engineering for complete lifecycle support

Electric machines (e-machines) will form a fundamental part of the powertrain of the future. Automotive manufacturers are keen to develop emachine manufacturing and assembly knowledge in-house. An on-going project, which aims to deliver an e-machine pilot assembly line, is being supported by a set of virtual engineering tools developed by the Automation Systems Group at the University of Warwick. Although digital models are a useful design aid providing visualization and simulation, the opportunity being exploited in this research paper is to have a common model throughout the lifecycle of both the manufacturing system and the product. The vision is to have a digital twin that is consistent with the real system and not just used in the early design and deployment phases. This concept, commonly referred to as Cyber Physical Systems (CPS), is key to realizing efficient system reconfigurability to support alternative product volumes and mixes. These tools produce modular digital models that can be rapidly modified preventing the simulation, test, and modification processes forming a bottleneck to the development lifecycles. In addition, they add value at more mature phases when, for example, a high volume line based on the pilot is created as the same models can be reused and modified as required. This research paper therefore demonstrates how the application of the virtual engineering tools support the development of a CPS using an e-machine assembly station as a case study. The main contribution of the work is to further validate the CPS philosophy by extending the concept into practical applications in pilot production systems with prototype products

Distribution of machine information using Blackboard designed component for remote monitoring of reconfigurable manufacturing systems

A blackboard-based design for a system component called the "Broadcaster" is described in this paper. It supports remote monitoring of reconfigurable manufacturing systems using a novel system architecture coupled with the Component-Based system paradigm. The design of this component has been evaluated using a case study on a web services-enabled test rig funded by the Ford Motor Company, U. K. The test rig has been implemented using a fully distributed control device called FTB, designed by the Schneider Electric Company. Evaluation of this component has been carried out using three scenario test cases which demonstrate the potentials offered when deploying this solution to a real production environment. The system component not only operates in a heterogeneous reconfigurable manufacturing environment, offering a vendor-independent solution to monitoring machines, but it also supports remote monitoring of the machines throughout their development and management lifecycles

Tool Paper: A Lightweight Formal Encoding of a Constraint Language for DSMLs

International audienceDomain Specific Modeling Languages (dsmls) plays a key role in the development of Safety Critical Systems to model system requirements and implementation. They often need to integrate property and query sub-languages. As a standardized modeling language, ocl can play a key role in their definition as they can rely both on its concepts and textual syntax which are well known in the Model Driven Engineering community. For example, most dsmls are defined using mof for their abstract syntax and ocl for their static semantics as a metamodeling dsml. OCLinEcore in the Eclipse platform is an example of such a metamodeling dsml integrating ocl as a language component in order to benefit from its property and query facilities. dsmls for Safety Critical Systems usually provide formal model verification activities for checking models completeness or consistency, and implementation correctness with respect to requirements. This contribution describes a framework to ease the definition of such formal verification tools by relying on a common translation from a subset of ocl to the Why3 verification toolset. This subset was selected to ease efficient automated verification. This framework is illustrated using a block specification language for data flow languages where a subset of ocl is used as a component language