Knowledge-Centric Systems Engineering is an industrial approach to systems and software engineering that advocates the development and use of knowledge bases that represent system domains. This approach can also exploit artificial intelligence techniques. These means can be used for early V&V (verification and validation) activities, e.g., for system artefact quality analysis and traceability management. This paper presents advances made in these activities with the SES Engineering Studio industrial tool and its underlying methods to meet further early-V& V needs in practice. The methods and the tool have been improved to better address model quality analysis, traceability project management, trace specification, and compliance with standards. For validation, we have initially applied the new features on a medical device. This has also allowed us to study the benefits of the features. The results show that the advances made can lead to wider system artefact analyses, more precise traceability management, better system artefacts, lower V & V effort, and lower issue resolution costs. All in all, the paper presents specific examples of how early- V & V industrial practices and tools can be improved.

In critical domains, assurance corresponds to the set of activities to provide confidence that a system can be deemed dependable, e.g., safe and secure. This essential systems and software engineering process are usually conducted according to standards. For novel applications running at the edge and containing artificial intelligence, and for their corresponding platforms, how to conduct assurance in a systematic way is still undefined. This paper introduces the work in the large-scale REBECCA EU project to contribute to filling this gap. A new assurance framework will be defined, addressing the management of compliance, assurance cases, and assurance evidence. The assurance framework will be based on the results of a systematic study to characterize Edge-AI assurance needs, and four systems will be used to validate the framework via case study research. The assurance framework will provide guidance about what needs to be considered for safety and security assurance of Edge-AI applications, and how.

Society increasingly depends on electronic systems and components (ECS) whose reliability must be ensured throughout their lifecycle. ECS reliability must be addressed since early development stages and the means used to this end must fit other systems engineering practices. Within this context, we present an industrial approach for model-based reliability-oriented system design. It links model-based systems engineering with Arcadia/Capella and knowledge-centric systems engineering with the Systems Engineering Suite. The approach deals with system modelling, ontology development, structured textual requirements specification, traceability management, and model quality analysis, all of them targeted at ECS reliability. We also present the validation steps taken.

Requirements Engineering (RE) has established itself as a software engineering discipline over the past decades. While researchers have been investigating the RE discipline with a plethora of empirical studies, attempts to systematically derive an empirical 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 externally valid foundation for a theory of RE practice, which helps software engineers establish effective and efficient RE processes in a problem-driven manner. We designed a survey instrument and an engineer-focused theory that was first piloted in Germany and, after making substantial modifications, has now been replicated in 10 countries worldwide. We have a theory in the form of a set of propositions inferred from our experiences and available studies, as well as the results from our pilot study in Germany. We evaluate the propositions with bootstrapped confidence intervals and derive potential explanations for the propositions. In this article, we report on the design of the family of surveys, its underlying theory, and the full results obtained from the replication studies conducted in 10 countries with participants from 228 organisations. Our results represent a substantial step forward towards developing an empirical theory of RE practice. 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 are common, that requirements specifications themselves are rarely changed and that requirements engineering (process) improvement endeavours are mostly internally driven. 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.

International audience

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.

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.

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.

Safety cases present the arguments and evidence that can be used to justify the acceptable safety of a system. Many secondary factors such as the tools used, the techniques applied, and the experience of the people who created the evidence, can affect an assessor's confidence in the evidence cited by a safety case. One means of reasoning about this confidence and its inherent uncertainties is to present a `confidence argument' that explicitly justifies the provenance of the evidence used. In this paper, we propose a novel approach to automatically construct these confidence arguments by enabling assessors to provide individual judgements concerning the trustworthiness and the appropriateness of the evidence. The approach is based on Evidential Reasoning and enables the derivation of a quantified aggregate of the overall confidence. The proposed approach is supported by a prototype tool (EviCA) and has been evaluated using the Technology Acceptance Model.

The main focus of Software Engineering discipline is to establishing methods and processes for the effective and efficient development of software projects. One of the most relevant paradigms for achieving this goal is Model-Driven Development (MDD). MDD uses models at different abstraction levels to automatically generate software products by means of model-transformations. However, one of the main issues related to the development of MDD technologies is the lack of standardization in terms of the features that need to be considered to support the current industry needs. This difficults the comparison of existing technologies since there are not a reference point for the creation of new MDD approaches with their corresponding supporting tools. This paper analyses these industry needs through an exploratory study. From the results obtained, it states the main features that must be supported by MDD tools. In addition, this paper presents an analysis about the presence or absence of these features in a set of industrial MDD tools.

Safety assurance and certification are amongst the most expensive and time-consuming tasks in the development of safety-critical systems. Demonstration of compliance with safety standards involves providing evidence that the standards' safety criteria are met. To handle large collections of evidence effectively, safety professionals need knowledge of how to classify different types of evidence, how to structure the evidence, and how to assess it. This paper takes a step towards developing such a body of knowledge by conducting a Systematic Literature Review (SLR). Specifically, the SLR identifies and classifies the information and artefacts considered as evidence for safety, examines existing techniques for evidence structuring and assessment, and summarizes the challenges noted in the literature in relation to safety evidence. The paper, to our knowledge, is the first systematic review on the topic of safety evidence. The results we present are particularly relevant to practitioners seeking to better understand the evidence requirements for safety certification, as well as to researchers conducting research in this area.

Traceability between development artefacts and mainly from and to requirements plays a major role in system lifecycle, supporting activities such as system validation, change impact analysis, and regulation compliance. Many researchers have been working on this topic and have published their work throughout the editions of the Requirements Engineering Conference. This paper aims to analyse the research on traceability published in the past 20 years of this conference and to provide insights into its contribution to the traceability area. We have selected and reviewed 70 papers in the proceedings of the conference and summarised several aspects of traceability that have been addressed and by whom. The paper also discusses the evolution of the topic at the conference, compares the results with those reported in other publications, and proposes aspects on which further research should be conducted.