Abstract Modeling is often associated with complex and heavy tooling, leading to a negative perception among practitioners. However, alternative paradigms, such as everything-as-code or low-code, are gaining acceptance due to their perceived ease of use. This paper explores the dichotomy between these perceptions through the lens of “modeler experience” (MX). MX includes factors such as user experience, motivation, integration, collaboration and versioning, and language complexity. We examine the relationships between these factors and their impact on different modeling usage scenarios. Our findings highlight the importance of considering MX when understanding how developers interact with modeling tools and the complexities of modeling and associated tooling.

Abstract Context Model driven development envisages the use of model transformations to evolve models. Model transformation languages, developed for this task, are touted with many benefits over general purpose programming languages. However, a large number of these claims have not yet been substantiated. They are also made without the context necessary to be able to critically assess their merit or built meaningful empirical studies around them. Objective The objective of our work is to elicit the reasoning, influences and background knowledge that lead people to assume benefits or drawbacks of model transformation languages. Method We conducted a large-scale interview study involving 56 participants from research and industry. Interviewees were presented with claims about model transformation languages and were asked to provide reasons for their assessment thereof. We qualitatively analysed the responses to find factors that influence the properties of model transformation languages as well as explanations as to how exactly they do so. Results Our interviews show, that general purpose expressiveness of GPLs, domain specific capabilities of MTLs as well as tooling all have strong influences on how people view properties of model transformation languages. Moreover, the Choice of MTL , the Use Case for which a transformation should be developed as well as the Skill s of involved stakeholders have a moderating effect on the influences, by changing the context to consider. Conclusion There is a broad body of experience, that suggests positive and negative influences for properties of MTLs. Our data suggests, that much needs to be done in order to convey the viability of model transformation languages. Efforts to provide more empirical substance need to be undergone and lacklustre language capabilities and tooling need to be improved upon. We suggest several approaches for this that can be based on the results of the presented study.

Abstract Automotive test case specifications document test cases to be performed for a specific test object at a defined test level. They are a fundamental part of a structured automotive testing process, as required by the ISO 26262. The aim of our research is to identify challenges from a practitioner’s point of view that lead to poor quality of test case specifications and thus negatively impact time, cost, and probability of defect detection. We designed an exploratory case study to systematically identify challenges focusing on (C) creation, (P) processing, and (Q) quality assurance related aspects of test case specifications. We conducted 17 semi-structured interviews covering a German OEM as well as three of its automotive suppliers and analyzed them qualitatively. We investigated causes and consequences arising from the challenges. Additionally, we conducted a descriptive survey to assess frequency and criticality. The identified challenges were summarized in a taxonomy consisting of nine main categories: (1) availability and (2) content-related problems with input artifacts, problems related to (3) a lack of knowledge, (4) the test case description, (5) the test case specification content, (6) processes, (7) communication, (8) quality assurance, and (9) tools. The challenges were assessed by 26 internal and 10 external employees. Hence, we identified differences between these groups in terms of access to documents, incomplete requirements, scope of model series, process, and tool-related aspects. Overall, the study results underline the necessity of quality assurance measures for test case specifications. Based on the assessments, our research indicates a broad range of test case description related challenges that are promising candidates for improving test case specification quality.

The introduction of major innovations in industry requires a collaboration across the whole supply chain. A common way to organize such a collaboration is the use of technology roadmaps, which act as an industry-wide long-term planning tool. Technology roadmaps are used to identify industry needs, estimate the availability of technological solutions, and identify the need for innovation in the future. Roadmaps are inherently both time-dependent and based on uncertain values, i.e., properties and structural components can change over time. Current approaches for model-driven engineering do not inherently support these aspects. We present a novel model-driven approach treating those aspects as first-class citizens. To address the problem of missing support for time in the context of roadmap modeling, we introduce the concepts of a common global time, time-dependent properties, and time-dependent availability. This includes requirements, properties, and the structure of the model or its components as well. These concepts result in a continuous range of various valid models over time instead of a single valid model at a certain point of time. We present concepts for an interactive graphical user interface to enable the user to efficiently interact with those models. We illustrate the application of these concepts on an industrial example of a next generation electrical fuse.

Automotive Test Case Specifications (TestSpecs) are a fundamental part of a structured test process in the automotive domain. For system and integration tests, acceptance and customer experience test cases are executed manually by human testers in a prototype vehicle. To ensure that these test cases are understood by humans, they are usually described in natural language, which often leads to ambiguities, misunderstandings, or incomplete test cases. In addition, the description of test cases vary significantly depending on the system to be tested and the respective test level. Test Designers want individual assistance in documenting their test cases with respect to system-specific characteristics, instead of using programming languages or standardized languages such as UML. Thus, Domain Specific Languages (DSLs) are a possible solution to satisfy this demand and to improve the quality of test cases, for example in terms of preciseness, uniformity, and completeness. The contribution of this paper is a systematic approach to support the development of system-specific automotive Testing DSLs that achieve high acceptance by test designers and testers. Therefore, we focus on the analysis phase in the DSL development process. We adapted domain analysis activities and defined a domain analysis method tailored to the analysis of automotive TestSpecs. We demonstrate the applicability of our method by means of five different automotive systems. Our evaluation shows that the derived system-specific Testing DSLs cover between 70% and 95% of the test steps contained in TestSpecs with only 11 to 35 conceptual templates. Moreover, a usability study with practitioners revealed a good usability of the Testing DSLs and the corresponding tool as well as that this eases the specification of test cases.

Test case specifications are a fundamental part of a structured test process and required by standards like ISO 26262 in the automotive domain. Test cases are usually derived from requirements and provide a necessary basis for test implementation and execution. The aim of this work is to gain insights into the creation and processing of test case specifications from a practitioner's point of view. We decided on an explorative case study to identify challenges related to three problem areas: creation, processing and quality assessment related aspects of test case specifications. We conducted 17 semi-structured interviews covering a German OEM and three automotive suppliers. Afterwards, we analyzed the collected data qualitatively to identify challenges as well as causes and consequences arising from them. The identified challenges were categorized in a taxonomy consisting of nine main categories: (1) availability and (2) content-related problems with input artifacts, problems related to (3) a lack of knowledge, (4) the test case description, (5) the content of a test case specification, (6) quality assurance, (7) processes, (8) communication, and (9) tools. Overall, we observed a present awareness of the identified challenges, which is evident from different solutions to handle these challenges. Nevertheless, some of the current solutions are not efficient and still require a lot of manual work, for instance phrasing-based problems in test cases.