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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.

Assessing and certifying the functional safety of the software of critical systems is of paramount importance, since any failure might produce significant costs as well as harm to people. Some common examples of critical systems are transport vehicles (trains, airplanes, cars…), medical devices, and critical infrastructures (nuclear plants, oil platforms…). Safety certification intends to reduce the risk of failure to an acceptable level in compliance with standards. IEC 61508 is a reference safety standard whose use is specialized in some domains, such ISO 26262 for automotive and EN 50128 for railway. For applying these standards, the use of Model-Driven approaches based on UML Profiles is a suitable alternative. However, UML profiles are usually manually defined, which is a highly time-consuming task and error-prone. In addition, manually defined UML profiles are difficult to validate in relation to the reference standards and to the coverage of safety concepts. This paper presents the adaptation of an existing approach for automatic UML Profile generation to support the generation of UML Profiles for safety specifications that are based on IEC 61508. As a result, it is possible to reduce the time and errors that are common in a manual specification of safety UML Profiles.

The engineering of safety-critical systems is a complex process whose cost-effectiveness is very important. Reuse of system artefacts is an activity that can contribute to improving quality and to saving costs during the process. Reuse must pay attention to artefact configuration management, as an artefact evolves through different versions and such an evolution must be properly managed. An artefact type that is used nowadays in industry for the engineering of safety-critical systems and can be reused is ontologies, which represent system domain information via knowledge representations. However, academic approaches for ontology reuse do not meet industrial needs for their application for systems engineering. As a solution, this paper presents an industrial approach to define and operate ontologies as libraries of knowledge to enable ontology configuration management. The approach supports the reuse and exploitation of domain knowledge through operations for mapping, alignment, and merge of ontology elements. The proposed approach, the current implementation, and validation activities are presented on top of the Knowledge Manager tool.

Context Critical systems in application domains such as automotive, railway, aerospace, and healthcare are required to comply with safety standards. The understanding of the safety compliance needs specified in these standards can be difficult from their text. A possible solution is to use models. Objective We aim to evaluate the use of models to understand safety compliance needs. Method We have studied the effectiveness, efficiency, and perceived benefits in understanding these needs, with models and with the text of safety standards, by means of an experiment. The standards considered are DO-178C and EN 50128. We use SPEM-like diagrams to graphically represent the models. Results The mean effectiveness of 20 undergraduate students in understanding the needs and the mean efficiency were higher with models (22% and 38%, respectively), and the difference is statistically significant (p-value ≤ 0.02). Most of the students agreed upon the ease of understanding the structure of safety compliance needs with models when compared to the text, but on average, the students were undecided about whether the models are easy to understand or easier to understand than the text. Conclusions The results allow us to claim that the use of models can improve the understanding of safety compliance needs. Nonetheless, there seems to be room for improvement in relation to the perceived benefits. It must be noted that our conclusions may differ if the subjects were experienced practitioners.

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.

Requirements Engineering (RE) has established itself as a software engineering discipline during the past decades. While researchers have been investigating the RE discipline with a plethora of empirical studies, attempts to systematically derive an empirically-based theory in context of the RE discipline have just recently been started. However, such a theory is needed if we are to define and motivate guidance in performing high quality RE research and practice. We aim at providing an empirical and valid foundation for a theory of RE, which helps software engineers establish effective and efficient RE processes. We designed a survey instrument and theory that has now been replicated in 10 countries world-wide. We evaluate the propositions of the theory with bootstrapped confidence intervals and derive potential explanations for the propositions. We report on the underlying theory and the full results obtained from the replication studies with participants from 228 organisations. Our results represent a substantial step forward towards developing an empirically-based theory of RE giving insights into current practices with RE processes. The results reveal, for example, that there are no strong differences between organisations in different countries and regions, that interviews, facilitated meetings and prototyping are the most used elicitation techniques, that requirements are often documented textually, that traces between requirements and code or design documents is common, requirements specifications themselves are rarely changed and that requirements engineering (process) improvement endeavours are mostly intrinsically motivated. Our study establishes a theory that can be used as starting point for many further studies for more detailed investigations. Practitioners can use the results as theory-supported guidance on selecting suitable RE methods and techniques., 47 pages, 19 figures, accepted for publication in ACM Transactions on Software Engineering and Methodology (TOSEM)

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: 6th International Conference on Model-Driven Engineering and Software Development (MODELSWARD 2018) January 22-24, 2018, in Funchal, Madeira, Portugal Safety-critical systems are typically subject to assurance processes as way to ensure that they do not pose undue risks to people, property, or the environment, usually in compliance with assurance standards. The planning, execution, and management of assurance processes can be a complex activity in practice because of issues in the application of the standards, the large amount of information to handle, and the need for providing convincing justifications of assurance adequacy, among other difficulties. As a solution, many authors have argued that the use of Model-Driven Engineering principles and techniques can facilitate and improve assurance of safety-critical systems. This paper presents some of the latest advances that have been and are being made towards the use of these principles and techniques in industry. Although models have been used for assurance of safety-critical systems for many years, e.g. to specify safety cases, it has only been recently when the full potential of Model-Driven Engineering has started to be more widely exploited. This includes aspects such as the specification of metamodels and domain specific languages for assurance, the extension and application of UML, and the use of model transformations The research leading to this paper has received funding from the AMASS project (H2020-ECSEL no 692474; Spain’s MINECO ref. PCIN-2015-262).

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).

SACM (Structured Assurance Case Metamodel) is a standard for assurance case specification and exchange. It consists of an argumentation metamodel and an evidence metamodel for justifying that a system satisfies certain requirements. For assurance of safety-critical systems, SACM can be used to manage safety evidence and to specify safety cases. The standard is a promising initiative towards harmonizing and improving system assurance practices, but its suitability for safety evidence management needs to be further studied. To this end, this paper studies how SACM 1.1 supports this activity according to requirements from industry and from prior work. We have analysed the notion of evidence in SACM, its evidence lifecycle, the classes and associations of the evidence metamodel, and the link of this metamodel with the argumentation one. As a result, we have identified several improvement opportunities and extension possibilities in SACM. The notions of evidence and evidence assertion should be clarified, the overlaps between metamodel elements should be reduced, and a wider support to the lifecycle of the artefacts used as safety evidence could be provided. Addressing these aspects will allow SACM to better fit safety evidence management needs and practices, especially beyond the scope of a safety case. The results and the conclusions drawn are especially valuable for practitioners interested in SACM adoption and vendors interested in developing tool support for SACM-based safety evidence management. We present an analysis of how SACM supports safety evidence management.The analysis is based on requirements from industry and from prior work.We have identified nine improvement areas and four extension possibilities.Addressing these aspects will allow SACM to better fit safety evidence management.

Proceedings of: 36th International Conference on Conceptual Modeling, ER 2017, Valencia, Spain, November 6–9, 2017 Context: Most safety-critical systems have to fulfil compliance needs specified in safety standards. These needs can be difficult to understand from the text of the standards, and the use of conceptual models has been proposed as a solution. Goal: We aim to evaluate the understanding of safety compliance needs with models. Method: We have conducted an experiment to study the effectiveness, efficiency, and perceived benefits in understanding these needs, with text of safety standards and with UML object diagrams. Results: Sixteen Bachelor students participated in the experiment. Their average effectiveness in understanding compliance needs and their average efficiency were higher with models (17% and 15%, respectively). However, the difference is not statistically significant. The students found benefits in using models, but on average they are undecided about their ease of understanding. Conclusions: Although the results are not conclusive enough, they suggest that the use of models could improve the understanding of safety compliance needs. 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). We also thank the subjects that participated in the experiment.

Context. In many application domains, critical systems must comply with safety standards. This involves gathering safety evidence in the form of artefacts such as safety analyses, system specifications, and testing results. These artefacts can evolve during a system's lifecycle, creating a need for change impact analysis to guarantee that system safety and compliance are not jeopardised. Objective. We aim to provide new insights into how safety evidence change impact analysis is addressed in practice. The knowledge about this activity is limited despite the extensive research that has been conducted on change impact analysis and on safety evidence management. Method. We conducted an industrial survey on the circumstances under which safety evidence change impact analysis is addressed, the tool support used, and the challenges faced. Results. We obtained 97 valid responses representing 16 application domains, 28 countries, and 47 safety standards. The respondents had most often performed safety evidence change impact analysis during system development, from system specifications, and fully manually. No commercial change impact analysis tool was reported as used for all artefact types and insufficient tool support was the most frequent challenge. Conclusion. The results suggest that the different artefact types used as safety evidence co-evolve. In addition, the evolution of safety cases should probably be better managed, the level of automation in safety evidence change impact analysis is low, and the state of the practice can benefit from over 20 improvement areas.

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

Safety standards prescribe change impact analysis (CIA) during evolution of safety-critical software systems. Although CIA is a fundamental activity, there is a lack of empirical studies about how it is performed in practice. We present a case study on CIA in the context of an evolving automation system, based on 14 interviews in Sweden and India. Our analysis suggests that engineers on average spend 50-100 hours on CIA per year, but the effort varies considerably with the phases of projects. Also, the respondents presented different connotations to CIA and perceived the importance of CIA differently. We report the most pressing CIA challenges, and several ideas on how to support future CIA. However, we show that measuring the effect of such improvement solutions is non-trivial, as CIA is intertwined with other development activities. While this paper only reports preliminary results, our work contributes empirical insights into practical CIA. ORION

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-awareness has emerged as a new perspective for business process modelling. Business processes are strongly influenced by context, the environment where they are executed, and thus context should not be ignored when modelling them. This calls for new approaches that facilitate contextualisation, i.e. identification and representation of the way context influences a business process. In addition, detailed methodological guidance for correct business process contextualisation should be provided. However, existing works on context-aware business process modelling do not deal with these challenges. This paper addresses them by presenting COMPRO, a methodological approach for business process contextualisation. Starting from an initial business process model, context is analysed in order to discover its relevant variations and specify their effect on a business process. Our approach helps process designers to adequately specify context variants and business process variants that accommodate them. Our ultimate goal is to guarantee the correct design of business processes that fit their context. In addition, we report initial results about COMPRO application and evaluation.

[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).

Many cyber–physical systems (CPS) are subject to rigorous assurance and certification processes to provide confidence that undue risks are not posed and thus the systems are trustworthy. These processes are complex and time-consuming and tool support can greatly aid in their execution. In line with other trends for systems and software engineering, the need for and interest in open source tools for assurance and certification is growing and different initiatives have been launched. As a concrete example, we report on our experience in developing the AMASS open source ecosystem. This ecosystem includes (1) an open source tool platform that supports the main CPS assurance and certification activities, (2) external tools with added-value features, and (3) an open community of developers and users. The platform integrates existing solutions for system modelling, process engineering, and compliance and argumentation management. We also present the application of the AMASS tool platform in 11 industrial case studies from five different application domains. The results show that the platform is a feasible means for CPS assurance and certification and that practitioners find benefits in assurance-oriented system modelling and in integrated system assurance information, among other areas. Nonetheless, improvement opportunities also exist, most notably regarding tool interoperability and usability.