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 order to enable a collaborative Model-based Systems Engineering (MBSE) environment through computer systems, it is completely necessary to enable the possibility of communicating tools (interoperability) and reusing previous engineering designs saving costs and time. In this context, the understanding of the underlying concepts and relationships em-bedded in the system artifacts becomes a cornerstone to properly exploit engineering artifacts. MBSE tool-chains and suites, such as Matlab Simulink, can be applied to different engineering activities: architecture design (descriptive modeling), simulation (analytical modeling) or verification. Reuse capabilities in specific engineering tools are a kind of non-functional aspect that is usually covered providing a type of search capability based on artifact metadata. In this work, we aim to ease the reuse of the knowledge embedded in Simulink models through a solution called PhysicalModel2Simulink. The proposed approach makes use of an ontology for representing, indexing and retrieving information following a meta-model (mainly to semantically represent concepts and relationships). Under this schema, both meta-data and contents are represented using a common domain vocabulary and taxonomy creating a property graph that can be exploited for system artifact discovery. To do so, a mapping between the Matlab Simulink meta-model and the RSHP (RelationShHiP) meta-model is defined to represent and serialize physical models in a repository. Then, a retrieval process is implemented on top of this repository to allow users to perform text-based queries and look up similar artifacts. To validate the proposed solution, 38 Simulink models have been used and 20 real user queries have been designed to study the effectiveness, in terms or precision and recall, of the proposed solution against the Matlab Simulink searching capabilities.

This paper introduces a mechanism to recover traceability links between the requirements and logical models in the context of critical systems development. Currently, lifecycle processes are covered by a good number of tools that are used to generate different types of artifacts. One of the cornerstone capabilities in the development of critical systems lies in the possibility of automatically recovery traceability links between system artifacts generated in different lifecycle stages. To do so, it is necessary to establish to what extent two or more of these work products are similar, dependent or should be explicitly linked together. However, the different types of artifacts and their internal representation depict a major challenge to unify how system artifacts are represented and, then, linked together. That is why, in this work, a concept-based representation is introduced to provide a semantic and unified description of any system artifact. Furthermore, a traceability function is defined and implemented to exploit this new semantic representation and to support the recovery of traceability links between different types of system artifacts. In order to evaluate the traceability function, a case study in the railway domain is conducted to compare the precision and recall of recovery traceability links between text-based requirements and logical model elements. As the main outcome of this work, the use of a concept-based paradigm to represent that system artifacts are demonstrated as a building block to automatically recover traceability links within the development lifecycle of critical systems.

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.