The demand for digital twins and suitable modeling techniques in the automotive industry is increasing rapidly. Yet, there is no common understanding of digital twins in automotive, nor are there modeling techniques established to create automotive digital twins. Recent studies on digital twins focus on the analysis of the literature on digital twins for automotive or in general and, thus, neglect the industrial perspective of automotive practitioners. To mitigate this gap between scientific literature and the industrial perspective, we conducted a questionnaire survey among experts in the German automotive industry to identify i) the desired purposes for and capabilities of digital twins and ii) the modeling techniques related to engineering and operating digital twins across the phases of automotive development. To this end, we contacted 189 members of the Software-Defined Car research project and received 96 responses. The results show that digital twins are considered most useful in the usage and support phase of automotive development, representing vehicles as-operated. Moreover, simulation models, source code, and business process models are currently considered the most important models to be integrated into a digital twin alongside the associated, established tools.

Background: Taxonomies are crucial for the development of a research field, as they play a major role in structuring a complex body of knowledge and help to classify processes, approaches, and solutions. While there is an increasing interest in taxonomies in the software engineering (SE) research field, we observe that SE taxonomies are rarely evaluated. Aim: To raise awareness and provide operational guidance on how to evaluate a taxonomy, this paper presents a three step evaluation method evaluating its structure, applicability, and purpose. Method: To show the feasibility and applicability of our approach, we provide a running example and additionally illustrate our approach to a practical case study in SE research. Results and Conclusion: Our method with operational guidance enables SE researchers to systematically evaluate and improve the quality of their taxonomies and support reviewers to systematically assess a taxonomy’s quality.

Coping with different and changing requirements leads to concurrent products (variability in space) and subsequent revisions (variability in time). Moreover, products consist of interrelated models that represent different kinds of artifacts. Dependencies and redundancies between interrelated models within a product and across products can quickly lead to inconsistencies during evolution. Thus, dealing with both variability dimensions uniformly while preserving consistency of interrelated models is a major challenge when developing large and long-living variable systems. Recent research addresses uniform management of variability in space and time by unifying concepts and operations from software product line engineering and software configuration management. However, consistency preservation for interrelated models, which is a major research topic in model-driven software development, has hardly been considered in variability management. We propose an approach that builds on recent efforts for unifying variability in space and time and leverages view-based consistency preservation for systems comprised of different kinds of interrelated models. We evaluate our approach by applying it to two real-world case studies: the well-known ArgoUML-SPL, that is based on the UML modeling tool ArgoUML, and MobileMedia, a mobile application for media management. Our results show that, by manually evolving only the Java models of products, other interrelated models (i.e.,~UML class diagrams) and the remaining affected products can be kept consistent fully automatically.

Context: Software architecture (SA) as research area experienced an increase in empirical research, as identified by Galster and Weyns in 2016 [1]. Empirical research builds a sound foundation for the validity and comparability of the research. A current overview on the evaluation and replicability of SA research objects could help to discuss our empirical standards as a community. However, no such current overview exists.Objective: We aim at assessing the current state of practice of evaluating SA research objects and replication artifact provision in full technical conference papers from 2017 to 2021.Method: We first create a categorization of papers regarding their evaluation and provision of replication artifacts. In a systematic literature review (SLR) with 153 papers we then investigate how SA research objects are evaluated and how artifacts are made available.Results: We found that technical experiments (28%) and case studies (29%) are the most frequently used evaluation methods over all research objects. Functional suitability (46% of evaluated properties) and performance (29%) are the most evaluated properties. 17 papers (11%) provide replication packages and 97 papers (63%) explicitly state threats to validity. 17% of papers reference guidelines for evaluations and 14% of papers reference guidelines for threats to validity.Conclusions: Our results indicate that the generalizability and repeatability of evaluations could be improved to enhance the maturity of the field; although, there are valid reasons for contributions to not publish their data. We derive from our findings a set of four proposals for improving the state of practice in evaluating software architecture research objects. Researchers can use our results to find recommendations on relevant properties to evaluate and evaluation methods to use and to identify reusable evaluation artifacts to compare their novel ideas with other research. Reviewers can use our results to compare the evaluation and replicability of submissions with the state of the practice.

Abstract With the increasing demand for customized systems and rapidly evolving technology, software engineering faces many challenges. A particular challenge is the development and maintenance of systems that are highly variable both in space (concurrent variations of the system at one point in time) and time (sequential variations of the system, due to its evolution). Recent research aims to address this challenge by managing variability in space and time simultaneously. However, this research originates from two different areas, software product line engineering and software configuration management, resulting in non-uniform terminologies and a varying understanding of concepts. These problems hamper the communication and understanding of involved concepts, as well as the development of techniques that unify variability in space and time. To tackle these problems, we performed an iterative, expert-driven analysis of existing tools from both research areas to derive a conceptual model that integrates and unifies concepts of both dimensions of variability. In this article, we first explain the construction process and present the resulting conceptual model. We validate the model and discuss its coverage and granularity with respect to established concepts of variability in space and time. Furthermore, we perform a formal concept analysis to discuss the commonalities and differences among the tools we considered. Finally, we show illustrative applications to explain how the conceptual model can be used in practice to derive conforming tools. The conceptual model unifies concepts and relations used in software product line engineering and software configuration management, provides a unified terminology and common ground for researchers and developers for comparing their works, clarifies communication, and prevents redundant developments.

Model-driven Software Development (MDSD) approaches struggle when modeling context-dependent and dynamic systems, as their underlying metamodels cannot capture context-dependent concepts and relations. By contrast, role-based modeling has been studied for more than 35 years as a promising paradigm to model context-dependent and dynamic systems. Although some approaches have considered the application of roles on the metamodel level, no approach employed a contextual and relational role-based metamodel as the basis of a modeling framework. To remedy this, we employ the Compartment Role Object Model (CROM) which is a contextual and relational role-based modeling language, as the underlying metamodel of a novel Role-based Modeling Framework (RMF). In particular, our framework is able to generate inter-operable Java source code that permits the programmatic creation, manipulation, and persistence of role-based models. We illustrate the applicability of RMF by modeling a small system with context-dependent concepts and relations, generating corresponding Java source code, and employing it to load, manipulate, and store role-based models.

Model-driven Software Development (MDSD) promotes the use of multiple related models to realize a software system systematically. These models usually contain redundant information but are independently edited. This easily leads to inconsistencies among them. To ensure consistency among multiple models, model synchronizations have to be employed, e.g., by means of model transformations, trace links, or triple graph grammars. Model synchronization poses three main problems for MDSD. First, classical model synchronization approaches have to be manually triggered to perform the synchronization. However, to support the consistent evolution of multiple models, it is necessary to immediately and continuously update all of them. Second, synchronization rules are specified at design time and, in classic approaches, cannot be extended at runtime, which is necessary if metamodels evolve at runtime. Finally, most classical synchronization approaches focus on bilateral model synchronization, i.e., the synchronization between two models. Consequently, for more than two models, they require the definition of pairwise model synchronizations leading to a combinatorial explosion of synchronization rules. To remedy these issues, we propose a role-based approach for runtime model synchronization. In particular, we propose role-based synchronization rules that enable the immediate and continuous propagation of changes to multiple interrelated models (and back again). Additionally, our approach permits adding new and customized synchronization rules at runtime. We illustrate the benefits of role-based runtime model synchronization using the Families to Persons case study from the Transformation Tool Contest 2017.

Just like current software systems, models are characterised by increasing complexity and rate of change. Yet, these models only become useful if they can be continuously evaluated and validated. To achieve sufficiently low response times for large models, incremental analysis is required. Reference Attribute Grammars (RAGs) offer mechanisms to perform an incremental analysis efficiently using dynamic dependency tracking. However, not all features used in conceptual modelling are directly available in RAGs. In particular, support for non-containment model relations is only available through manual implementation. We present an approach to directly model uni- and bidirectional non-containment relations in RAGs and provide efficient means for navigating and editing them. This approach is evaluated using a scalable benchmark for incremental model editing and the JastAdd RAG system. Our work demonstrates the suitability of RAGs for validating complex and continuously changing models of current software systems.

Software Product Lines (SPLs) have a long tradition and aim at reducing development costs by increasing reuse. They have been successfully applied to develop families of languages, ultimately establishing the field of Language Product Lines (LPLs). Currently, LPLs facilitate a family of textual languages by defining an SPL of compilers/interpreters. In contrast, this work aims at supporting families of graphical languages by defining an SPL of graphical editors, whereas each language variant is supported by a corresponding product of a Graphical Editor Product Line (GEPL). Thus far, there exists no modular approach for the development of GEPLs for families of visual languages. To remedy this, this paper introduces a feature-oriented development approach for GEPLs that ensures modularity, maintainability, and extensibility of the resulting product line. To showcase the suitability and applicability of our approach, we developed a modular GEPL for the family of role-based modeling languages, a feature rich family of conceptual modeling languages. Finally, we illustrate its extensibility by adding a complex language feature.

Over the past decade language development tools have been significantly improved. This permitted both practitioners and researchers to design a wide variety of domain-specific languages (DSL) and extensions to programming languages. Moreover, multiple researchers have combined different language variants to form families of DSLs as well as programming languages. Unfortunately, current language development tools cannot directly support the development of these families. To overcome this limitation, researchers have recently applied ideas from software product lines (SPL) to create product lines of compilers/interpreters for language families, denoted language product lines (LPL). Similar to SPLs, however, these product lines can be created either using a top-down or a bottom-up approach. Yet, there exist no case study comparing the suitability of both approaches to the development of LPLs, making it unclear how language development tools should evolve. Accordingly, this paper compares both feature modeling approaches by applying them to the development of an LPL for the family of role-based programming languages and discussing their applicability, feasibility and overall suitability for the development of LPLs. Although one might argue that this compares apples and oranges, we believe that this case still provides crucial insights into the requirements, assumptions, and challenges of each approach.

Role-based modeling has been investigated for over 35 years as a promising paradigm to model complex, dynamic systems. Although current software systems are characterized by increasing complexity and context-dependence, all this research had almost no influence on current software development practice, still being discussed in recent literature. One reason for this is the lack of a coherent, comprehensive, readily applicable notion of roles. Researchers focused either on relational roles or context-dependent roles rather then combining both natures. Currently, there is no role-based modeling language sufficiently incorporating both the relational and context-dependent nature of roles together with the various proposed constraints. Hence, this paper formalizes a full-fledged role-based modeling language supporting both natures. To show its sufficiency and adequacy, a real world example is employed.

Although most programming languages naturally share several language features, they are typically implemented as a monolithic product. Language features cannot be plugged and unplugged from a language and reused in another language. Some modular approaches to language construction do exist but composing language features requires a deep understanding of its implementation hampering their use. The choose and pick approach from software product lines provides an easy way to compose a language out of a set of language features. However, current approaches to language product lines are not sufficient enough to cope with the complexity and evolution of real world programming languages. In this work, we propose a general light-weight bottom-up approach to automatically extract a feature model from a set of tagged language components. We applied this approach to the Neverlang language development framework and developed the AiDE tool to guide language developers towards a valid language composition. The approach has been evaluated on a decomposed version of Javascript to highlight the benefits of such a language product line.

Database Management Systems (DBMS) are used by software applications, to store, manipulate, and retrieve large sets of data. However, the requirements of current software systems pose various challenges to established DBMS. First, most software systems organize their data by means of objects rather than relations leading to increased maintenance, redundancy, and transformation overhead when persisting objects to relational databases. Second, complex objects are separated into several objects resulting in Object Schizophrenia and hard to persist Distributed State. Last but not least, current software systems have to cope with increased complexity and changes. These challenges have lead to a general paradigm shift in the development of software systems. Unfortunately, classical DBMS will become intractable, if they are not adapted to the new requirements imposed by these software systems. As a result, we propose an extension of DBMS with roles to represent complex objects within a relational database and support the flexibility required by current software systems. To achieve this goal, we introduces RSQL, an extension to SQL with the concept of objects playing roles when interacting with other objects. Additionally, we present a formal model for the logical representation of roles in the extended DBMS.