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In the context of fast-growing digitization of industrial environments, Industry 4.0 aims to improve key elements to achieve more efficient processes, flexibility in customizing products and reduction in energy consumption, among other objectives. This paper presents a system that exploits the Internet of Things (IoT), massive data computation, and human-robot collaboration to reach these goals. The described system combines technological and human-centered aspects to enhance human-robot interaction. In fact, the human factor cannot be left aside when technological advances affecting society are foreseen. The proposal has been tested on a gesture control system that enables a natural interaction with a robotic arm through the use of IoT-oriented inertial measurement unit devices. These devices capture the movements of both human’s arms. Experiments of a technical nature have been run to measure accuracy and latency. In addition, human-centered tests have been conducted with real users to determine the level of intuitiveness and acceptance of the proposed gesture control. The results obtained demonstrate that the proposal meets the demands in terms of real-time, success rate, flexibility and scalability, which are fundamental requirements in Industry 4.0. The usability results have enabled drawing useful conclusions on the use of such human-robot interaction systems.

As our dependence on automated systems grows, so does the need for guaranteeing their safety, cybersecurity, and privacy (SCP). Dedicated methods for verification and validation (V&V) must be used to this end and it is necessary that the methods and their characteristics can be clearly differentiated. This can be achieved via method classifications. However, we have experienced that existing classifications are not suitable to categorise V&V methods for SCP of automated systems. They do not pay enough attention to the distinguishing characteristics of this system type and of these quality concerns. As a solution, we present a new classification developed in the scope of a large-scale industry-academia project. The classification considers both the method type, e.g., testing, and the concern addressed, e.g., safety. Over 70 people have successfully used the classification on 53 methods. We argue that the classification is a more suitable means to categorise V&V methods for SCP of automated systems and that it can help other researchers and practitioners.

Unmanned aerial vehicles (UAVs) represent a new model of social robots for home care of dependent persons. In this regard, this article introduces a study on people’s feeling of safety and comfort while watching the monitoring trajectory of a quadrotor dedicated to determining their condition. Three main parameters are evaluated: the relative monitoring altitude, the monitoring velocity and the shape of the monitoring path around the person (ellipsoidal or circular). For this purpose, a new trajectory generator based on a state machine, which is successfully implemented and simulated in MATLAB/Simulink®, is described. The study is carried out with 37 participants using a virtual reality (VR) platform based on two modules, UAV simulator and VR Visualiser, both communicating through the MQTT protocol. The participants’ preferences have been a high relative monitoring altitude, a high monitoring velocity and a circular path. These choices are a starting point for the design of trustworthy socially assistive UAVs flying in real homes.

Assurance and certification are usually required for critical systems. The underlying activities can be complex and labour-intensive, thus tool support can greatly facilitate them. Companies are also adopting the notion of Knowledge-Centric Systems Engineering, which is based on the principle that there exists a knowledge base about any system that tools can exploit for e.g. system quality analysis. This paper presents the initial results towards the integration of both types of tool support to enhance systems engineering and certification. We have worked on the integration of the AMASS Platform for assurance and certification with the tools developed by The REUSE Company. The integration allows the latter tools to analyse the quality of assurance assets, trace them, and support semantic asset search, whereas the Platform can collect assurance evidence from quality analyses on different artefact types. This way, a unified approach for Knowledge-Centric Systems Engineering, assurance, and certification is enabled.

Safety-critical systems are subject to rigorous verification and validation activities to guarantee that their quality is sufficient and acceptable. Quality analysis does not only need to be performed on the systems themselves, but also on their associated artefacts, e.g. system specifications. Such an analysis is essential for early quality assessment and so that system development progresses in compliance with standards. However, the analysis is challenging and labour-intensive for large complex systems, thus practitioners need means that facilitate it. This paper presents recent advances in artefact quality analysis for safety-critical systems. The presented industrial tools and practices are part of the products and services provided by The REUSE Company, have been developed in collaborative research projects, and are already available to its customers. We introduce the management and use of requirements metrics, model metrics, checklists, quality evolution, and connectors. This information demonstrates (1) how artefact quality analysis is progressing in practice and (2) what artefact quality analysis needs are being fulfilled.

Context: The increasing adoption of process-aware information systems together with the high variability in business processes has resulted in collections of process families. These families correspond to a business process model and its variants, which can comprise hundreds or thousands of different ways of realizing this process. Managing process variability in this context can be very challenging, labor-intensive, and error-prone, and new approaches for managing process families are necessary. Objective: We aim to facilitate variability management in process families, ensure process family correctness, and reduce the effort needed for such purposes. Method: We have derived a set of change patterns for process families from variability-specific language constructs identified in the literature. For validation, we have conducted a case study with a safety standard in which we have measured the number of operations needed to model and evolve the variability of the standard with and without the patterns. Results: We present 10 change patterns for managing variability in process families and show how they can be implemented. The patterns support the modeling and evolution of process families and ensure process family correctness by automatically introducing and deleting modeling elements. The case study results show that the application of the defined change patterns can reduce the number of operations when modeling a process family by 34% and when evolving it by 40%. Conclusions: The application of the change patterns can help in effectively modeling and evolving large and highly-variable process families. Their application can also considerably reduce variability management effort. (C) 2016 Elsevier B.V. All rights reserved., This work has been developed with the financial support of Spanish Ministry of Economy and Competitiveness under the project SMART-ADAPT TIN2013-42981-P. We also want to thank Barbara Weber and Manfred Reichert for their valuable input and feedback on the design and development of the set of change patterns for process families.

We present a metamodel for the specification of safety compliance needs.The metamodel abstracts concepts and criteria from different safety standards.Its application results in models for structuring and managing compliance information.It can be used for most critical computer-based and software-intensive systems. Context: Many critical systems must comply with safety standards as a way of providing assurance that they do not pose undue risks to people, property, or the environment. Safety compliance is a very demanding activity, as the standards can consist of hundreds of pages and practitioners typically have to show the fulfilment of thousands of safety-related criteria. Furthermore, the text of the standards can be ambiguous, inconsistent, and hard to understand, making it difficult to determine how to effectively structure and manage safety compliance information. These issues become even more challenging when a system is intended to be reused in another application domain with different applicable standards.Objective: This paper aims to resolve these issues by providing a metamodel for the specification of safety compliance needs for critical systems.Method: The metamodel is holistic and generic, and abstracts common concepts for demonstrating safety compliance from different standards and application domains. Its application results in the specification of "reference assurance frameworks" for safety-critical systems, which correspond to a model of the safety criteria of a given standard. For validating the metamodel with safety standards, parts of several standards have been modelled by both academic and industry personnel, and other standards have been analysed. We further augment this with feedback from practitioners, including feedback during a workshop.Results: The results from the validation show that the metamodel can be used to specify safety compliance needs for aerospace, automotive, avionics, defence, healthcare, machinery, maritime, oil and gas, process industry, railway, and robotics. Practitioners consider that the metamodel can meet their needs and find benefits in its use.Conclusion: The metamodel supports the specification of safety compliance needs for most critical computer-based and software-intensive systems. The resulting models can provide an effective means of structuring and managing safety compliance information.

Proceedings of: 40th International Conference on Software Engineering in Gothenburg, Sweden, May 27 - June 03, 2018 A fundamental aspect in the requirements engineering process is to know the quality of a specification, including how the quality evolves over time. This paper introduces an industrial approach for analysis of requirements quality evolution. The approach has been implemented in the System Quality Analyzer tool, exploits quality metrics for requirements correctness, consistency, and completeness, and is based on the storage of quality information in snapshots that are combined and displayed in charts. This can help practitioners to assess the progress and status of a requirements engineering process and to make decisions. The AMASS project (H2020-ECSEL grant agreement no 692474; Spain's MINECO ref. PCIN-2015-262) has funded this work.

Proceedings of: 36th International Conference on Computer Safety, Reliability, and Security, (SAFECOMP 2017). Trento, Italy, September 13-15, 2017 Understanding and following safety standards with their text can be difficult. Ambiguity and inconsistency, among other issues, can easily arise. As a solution, several authors argue for the explicit representation of the standards with models, which can be created with semantic technologies such as ontologies. However, this possibility has received little attention. The few authors that have addressed it have also only dealt with a subset of safety standard aspects and have used technologies not usually applied for critical systems engineering. As a first step towards addressing these issues, this position paper presents our initial work on the representation of safety standards with Knowledge Manager, a tool used in industrial environments that exploits semantic technologies to manage domain information. The proposal also builds on prior work on the specification of safety compliance needs with a holistic generic metamodel. We describe how to use Knowledge Manager to specify the concepts and relationships of the metamodel for a given safety standard, and discuss the application and benefits of the corresponding representation. The research leading to this paper has received funding from the AMASS project (H2020-ECSEL no. 692474; Spain’s MINECO ref. PCIN-2015-262).

Context. Many critical systems must meet safety compliance needs from safety standards. These standards are usually large textual documents whose compliance needs can be hard to understand. As a solution, the use of models has been proposed. Goal. We aim to provide evidence of the extent to which models improve the understanding of safety compliance needs. Method. We designed an experiment and ran a pilot to study the effectiveness, efficiency, and perceived benefits of understanding these needs, with the text of standards and with models in the form of UML object diagrams. Results. The overall results from 15 Bachelor students show that the effectiveness of understanding safety compliance needs increases very little with models (2%), and the efficiency even decreases (24%). Nonetheless, the results improve when the potential complexity in navigating the models is taken into account (15% effectiveness increase). The students find benefits in using the models but most consider that the models are hard to understand. Conclusions. The extent to which models improve the understanding of safety compliance needs seems to be lower than what the research community expects. New studies are necessary to confirm our initial insights. European Commission The research leading to this paper has received funding from the AMASS project (H2020-ECSEL grant agreement no 692474; Spain’s MINECO ref. PCIN-2015-262) and the AMoDDI project (Ref. 11130583).

Unlike practices in electrical and mechanical equipment engineering, Cyber-Physical Systems (CPS) do not have a set of standardized and harmonized practices for assurance and certification that ensures safe, secure and reliable operation with typical software and hardware architectures. This paper presents a recent initiative called AMASS (Architecture-driven, Multi-concern and Seamless Assurance and Certification of Cyber-Physical Systems) to promote harmonization, reuse and automation of labour-intensive certification-oriented activities via using model-based approaches and incremental techniques. AMASS will develop an integrated and holistic approach, a supporting tool ecosystem and a self-sustainable community for assurance and certification of CPS. The approach will be driven by architectural decisions (fully compatible with standards, e.g. AUTOSAR and IMA), including multiple assurance concerns such as safety, security and reliability. AMASS will support seamless interoperability between assurance/certification and engineering activities along with third-party activities (external assessments, supplier assurance). The ultimate aim is to lower certification costs in face of rapidly changing product features and market needs. This project has received funding from the Electronic Component Systems for European Leadership Joint Undertaking under grant agreement No 692474. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and Spain, Czech Republic, Germany, Sweden, Austria, Italy, United Kingdom, France

Context Critical systems in domains such as aviation, railway, and automotive are often subject to a formal process of safety certification. The goal of this process is to ensure that these systems will operate safely without posing undue risks to the user, the public, or the environment. Safety is typically ensured via complying with safety standards. Demonstrating compliance to these standards involves providing evidence to show that the safety criteria of the standards are met. Objective In order to cope with the complexity of large critical systems and subsequently the plethora of evidence information required for achieving compliance, safety professionals need in-depth knowledge to assist them in classifying different types of evidence, and in structuring and assessing the evidence. This paper is a step towards developing such a body of knowledge that is derived from a large-scale empirically rigorous literature review. Method We use a Systematic Literature Review (SLR) as the basis for our work. The SLR builds on 218 peer-reviewed studies, selected through a multi-stage process, from 4963 studies published between 1990 and 2012. Results We develop a taxonomy that classifies the information and artefacts considered as evidence for safety. We review the existing techniques for safety evidence structuring and assessment, and further study the relevant challenges that have been the target of investigation in the academic literature. We analyse commonalities in the results among different application domains and discuss implications of the results for both research and practice. Conclusion The paper is, to our knowledge, the largest existing study on the topic of safety evidence. The results are particularly relevant to practitioners seeking a better grasp on evidence requirements as well as to researchers in the area of system safety. As a major finding of the review, the results strongly suggest the need for more practitioner-oriented and industry-driven empirical studies in the area of safety certification.

[Context and motivation] Safety-critical systems in application domains such as aerospace, automotive, healthcare, and railway are subject to assurance processes to provide confidence that the systems do not pose undue risks to people, property, or the environment. The development of safety cases is usually part of these processes to justify that a system satisfies its safety requirements and thus is dependable. [Question/problem] Although safety cases have been used in industry for over two decades, their management still requires improvement. Important weaknesses have been identified and means to assess the quality of safety cases are limited. [Principal ideas/results] This paper presents a research preview on the assessment of the quality of safety cases. We explain how the area should develop and present our preliminary work towards enabling the assessment with Verification Studio, an industrial tool for system artefact quality analysis. [Contribution] The insights provided allow researchers and practitioners to gain an understanding of why safety case quality requires further investigation, what aspects must be considered, and how quality assessment could be performed in practice.

Most safety-critical systems must undergo assurance and certification processes. The associated activities can be complex and labour-intensive, thus practitioners need suitable means to execute them. The activities are further becoming more challenging as a result of the evolution of the systems towards cyber-physical ones, as these systems have new assurance and certification needs. The AMASS project (Architecture-driven, Multi-concern and Seamless Assurance and Certification of Cyber-Physical Systems) tackled these issues by creating and consolidating the de-facto European-wide open tool platform, ecosystem, and self-sustainable community for assurance and certification of cyber-physical systems. The project defined a novel holistic approach for architecture-driven assurance, multi-concern assurance, seamless interoperability, and cross- and intra-domain reuse of assurance assets. AMASS results were applied in 11 industrial case studies to demonstrate the reduction of effort in assurance and certification, the reduction of (re)certification cost, the reduction of assurance and certification risks, and the increase in technology harmonisation and interoperability. The research leading to this paper has received funding from the AMASS project (H2020-ECSEL grant agreement no 692474; Spain’s MINECO ref. PCIN-2015-262; Sweden’s Vinnova) and the Ramon y Cajal Program (Spain’s MICINN ref. RYC-2017-22836; EC’s European Social Fund). We are also grateful to all the AMASS partners. Their work and results are summarised in this paper.

The Systems Modeling Language (SysML) is spreading very fast. Most modelling tool vendors support it and practitioners have adopted it for Systems Engineering. The number of SysML models is growing, increasing the need for and the potential benefit from platforms that allow a user to reuse the knowledge represented in the models. However, SysML model reuse remains challenging. Each tool has its own implementation of SysML, hindering reuse between tools. The search capabilities of most tools are also very limited and finding reusable models can be difficult. This paper presents our vision and initial work towards enabling an effective reuse of the knowledge contained in SysML models. The proposed solution is based on a universal information representation model called RSHP and on existing technology for indexing and retrieval. The solution has been used to index models of all SysML diagram types and preliminary validated with requirements diagrams. The results from the validation show that the solution has very high precision and recall. This makes us confident that the solution can be a suitable means for effective SysML model reuse. European Commission The research leading to this paper has received funding from the AMASS project (H2020-ECSEL grant agreement no 692474; Spain's MINECO ref. PCIN-2015-262).