Boundary Objects and their Use in Agile Systems Engineering

Agile methods are increasingly introduced in automotive companies in the attempt to become more efficient and flexible in the system development. The adoption of agile practices influences communication between stakeholders, but also makes companies rethink the management of artifacts and documentation like requirements, safety compliance documents, and architecture models. Practitioners aim to reduce irrelevant documentation, but face a lack of guidance to determine what artifacts are needed and how they should be managed. This paper presents artifacts, challenges, guidelines, and practices for the continuous management of systems engineering artifacts in automotive based on a theoretical and empirical understanding of the topic. In collaboration with 53 practitioners from six automotive companies, we conducted a design-science study involving interviews, a questionnaire, focus groups, and practical data analysis of a systems engineering tool. The guidelines suggest the distinction between artifacts that are shared among different actors in a company (boundary objects) and those that are used within a team (locally relevant artifacts). We propose an analysis approach to identify boundary objects and three practices to manage systems engineering artifacts in industry

Why and How Your Traceability Should Evolve: Insights from an Automotive Supplier

Traceability is a key enabler of various activities in automotive software and systems engineering and required by several standards. However, most existing traceability management approaches do not consider that traceability is situated in constantly changing development contexts involving multiple stakeholders. Together with an automotive supplier, we analyzed how technology, business, and organizational factors raise the need for flexible traceability. We present how traceability can be evolved in the development lifecycle, from early elicitation of traceability needs to the implementation of mature traceability strategies. Moreover, we shed light on how traceability can be managed flexibly within an agile team and more formally when crossing team borders and organizational borders. Based on these insights, we present requirements for flexible tool solutions, supporting varying levels of data quality, change propagation, versioning, and organizational traceability.Comment: 9 pages, 3 figures, accepted in IEEE Softwar

Safety-Critical Systems and Agile Development: A Mapping Study

In the last decades, agile methods had a huge impact on how software is developed. In many cases, this has led to significant benefits, such as quality and speed of software deliveries to customers. However, safety-critical systems have widely been dismissed from benefiting from agile methods. Products that include safety critical aspects are therefore faced with a situation in which the development of safety-critical parts can significantly limit the potential speed-up through agile methods, for the full product, but also in the non-safety critical parts. For such products, the ability to develop safety-critical software in an agile way will generate a competitive advantage. In order to enable future research in this important area, we present in this paper a mapping of the current state of practice based on {a mixed method approach}. Starting from a workshop with experts from six large Swedish product development companies we develop a lens for our analysis. We then present a systematic mapping study on safety-critical systems and agile development through this lens in order to map potential benefits, challenges, and solution candidates for guiding future research.Comment: Accepted at Euromicro Conf. on Software Engineering and Advanced Applications 2018, Prague, Czech Republi

Why and How to Balance Alignment and Diversity of Requirements Engineering Practices in Automotive

In large-scale automotive companies, various requirements engineering (RE) practices are used across teams. RE practices manifest in Requirements Information Models (RIM) that define what concepts and information should be captured for requirements. Collaboration of practitioners from different parts of an organization is required to define a suitable RIM that balances support for diverse practices in individual teams with the alignment needed for a shared view and team support on system level. There exists no guidance for this challenging task. This paper presents a mixed methods study to examine the role of RIMs in balancing alignment and diversity of RE practices in four automotive companies. Our analysis is based on data from systems engineering tools, 11 semi-structured interviews, and a survey to validate findings and suggestions. We found that balancing alignment and diversity of RE practices is important to consider when defining RIMs. We further investigated enablers for this balance and actions that practitioners take to achieve it. From these factors, we derived and evaluated recommendations for managing RIMs in practice that take into account the lifecycle of requirements and allow for diverse practices across sub-disciplines in early development, while enforcing alignment of requirements that are close to release.Comment: 19 page

Use, potential, and showstoppers of models in automotive requirements engineering

Several studies report that the use of model-centric methods in the automotive domain is widespread and offers several benefits. However, existing work indicates that few modelling frameworks explicitly include requirements engineering (RE), and that natural language descriptions are still the status quo in RE. Therefore, we aim to increase the understanding of current and potential future use of models in RE, with respect to the automotive domain. In this paper, we report our findings from a multiple-case study with two automotive companies, collecting interview data from 14 practitioners. Our results show that models are used for a variety of different purposes during RE in the automotive domain, e.g. to improve communication and to handle complexity. However, these models are often used in an unsystematic fashion and restricted to few experts. A more widespread use of models is prevented by various challenges, most of which align with existing work on model use in a general sense. Furthermore, our results indicate that there are many potential benefits associated with future use of models during RE. Interestingly, existing research does not align well with several of the proposed use cases, e.g. restricting the use of models to informal notations for communication purposes. Based on our findings, we recommend a stronger focus on informal modelling and on using models for multi-disciplinary environments. Additionally, we see the need for future work in the area of model use, i.e. information extraction from models by non-expert modellers

A Compositional Approach to Creating Architecture Frameworks with an Application to Distributed AI Systems

Artificial intelligence (AI) in its various forms finds more and more its way into complex distributed systems. For instance, it is used locally, as part of a sensor system, on the edge for low-latency high-performance inference, or in the cloud, e.g. for data mining. Modern complex systems, such as connected vehicles, are often part of an Internet of Things (IoT). To manage complexity, architectures are described with architecture frameworks, which are composed of a number of architectural views connected through correspondence rules. Despite some attempts, the definition of a mathematical foundation for architecture frameworks that are suitable for the development of distributed AI systems still requires investigation and study. In this paper, we propose to extend the state of the art on architecture framework by providing a mathematical model for system architectures, which is scalable and supports co-evolution of different aspects for example of an AI system. Based on Design Science Research, this study starts by identifying the challenges with architectural frameworks. Then, we derive from the identified challenges four rules and we formulate them by exploiting concepts from category theory. We show how compositional thinking can provide rules for the creation and management of architectural frameworks for complex systems, for example distributed systems with AI. The aim of the paper is not to provide viewpoints or architecture models specific to AI systems, but instead to provide guidelines based on a mathematical formulation on how a consistent framework can be built up with existing, or newly created, viewpoints. To put in practice and test the approach, the identified and formulated rules are applied to derive an architectural framework for the EU Horizon 2020 project ``Very efficient deep learning in the IoT" (VEDLIoT) in the form of a case study

T-Reqs: Tool Support for Managing Requirements in Large-Scale Agile System Development

T-Reqs is a text-based requirements management solution based on the git version control system. It combines useful conventions, templates and helper scripts with powerful existing solutions from the git ecosystem and provides a working solution to address some known requirements engineering challenges in large-scale agile system development. Specifically, it allows agile cross-functional teams to be aware of requirements at system level and enables them to efficiently propose updates to those requirements. Based on our experience with T-Reqs, we i) relate known requirements challenges of large-scale agile system development to tool support; ii) list key requirements for tooling in such a context; and iii) propose concrete solutions for challenges.Comment: Accepted for publication in Proc. of 26th IEEE Int. Requirements Eng. Conf., Demo Track, Banff, Alberta, Canada, 201