Abstract Model inspections are important to ensure high‐quality software and to satisfy legal obligations in model‐based engineering processes. As model‐based specifications are typically documented on type‐level, errors concerning the interactions between multiple system instances can go unnoticed. For collaborative cyber‐physical systems (CPS), a plethora of possible instance‐level configurations need to be taken into account. Therefore, we propose the definition of instance‐level review diagrams that show representative interactions of instance‐level configurations that help detect defects in the system specification. To evaluate the approach, we conducted a controlled experiment whose results indicate that instance‐level review diagrams have—compared with type‐level diagrams—important positive effects on reviewing processes for behavioral specifications of CPS. Specifically, the experiment provides empirical evidence that instance‐level review diagrams are significantly more expressive and effective than type‐level diagrams.

In the field of safety-critical systems, manual reviews are important to ensure high-quality software and to satisfy legal obligations. When applying model-based engineering approaches, no longer are only textual requirements specifications or software code under review, but also model-based specification artifacts like behavioral requirements models. As such behavioral specifications are typically documented on a type-level, errors concerning the interactions between multiple system instances can go unnoticed in manual reviews. This is particularly the case when multiple system instances of the same system type are interacting during runtime, which is typical for cyber-physical systems where networks of cyber-physical systems form dynamically to fulfill an overall purpose. In this paper, we report on a controlled experiment whose results indicate that instance-level review diagrams have -- compared to type-level diagrams - important positive effects on reviewing processes for behavioral specifications of cyber-physical systems. Specifically, the experiment provides empirical evidence that instance-level review diagrams are significantly more expressive and effective than type-level diagrams.

Software-intensive cyber-physical systems (CPS) perform essential tasks such as controlling automated production processes in industrial production plants. The required levels of autonomy, openness, and self-adaptation, as well as the dynamic nature of the context of such CPS, result in challenging tasks for their engineering. During operation, unexpected situations in which the system has insufficient knowledge about the current state of the system itself as well as its context may occur. Engineering CPS, e.g., for industrial production sites, must account for such uncertainties the system will have to cope with during its lifetime in a structured and systematic way. Since the development of CPS requires consideration of different system perspectives, current uncertainty modeling approaches cannot be applied right away, as they do not explicitly consider uncertainty aspects that affect different artifacts. To aid the engineering of CPS, this article presents a model-based approach to document uncertainty. We propose “Orthogonal Uncertainty Models,” which closely integrate with other engineering artifacts from different perspectives, as a means for capturing a dedicated uncertainty viewpoint. Our approach has been evaluated in the industry automation domain. The application shows that the idea of regarding uncertainty within a dedicated perspective is highly beneficial. Particularly, our approach helps to uncover and document uncertainties related to behavioral, functional, and structural properties of a system, as well as uncertainties related to business models that would otherwise possibly remain covert. Note to Practitioners-Identifying and documenting uncertainties, which may occur during operation of a system, is a common problem in engineering processes. Such uncertainties may lead to severe damage, and thus need to be mitigated appropriately. It is crucial to account for these uncertainties during engineering, especially in the early phases. Depending on the specific project characteristics, a multitude of different diagram types are used to model a system. Uncertainties thus reflect in many artifacts, which leads to: 1) redundancies in the specified uncertainty attached to diagram elements and 2) uncertainty information (e.g., about the cause or effect of uncertainty) that is spread across different diagrams. The latter makes it difficult to structure uncertainty information and trace it throughout the engineering process so that uncertainty can be systematically considered. Our approach provides a graphical modeling language that employs a dedicated perspective on uncertainty in separate diagrams that can be linked to any engineering artifact.

Background: In model-based engineering models need to be regularly validated by manual assessment. Therefore, review processes have established. This commonly means that a visual inspection of the respective models is conducted. Aims: In this paper, we report a study that aims at investigating whether automatically generated review models can aid the manual review of model-based specifications. We investigate this for the case of embedded systems' functional design. Method: For that purpose, we compared the manual review of the functional design with the review of an automatically generated review model. In this paper, we report on a controlled experiment to compare effectiveness, efficiency, user confidence, and subjective supportiveness of both review artifacts. Results: The experiment results show that the use of the review model as review artifact for the functional design is significantly more effective, leads to a significantly higher user confidence in decision making and is valued as significantly more supportive than the review of the original functional design. Conclusions: Our experiment provides evidences that reviewing a generated review model instead of the original model-based specification of the functional design increases the quality of the reviews. Our findings also indicate that the use of generated review models have the potential to improve the review of model-based specifications in general.

[Background] Systematic literature reviews and maps have become well-established research methods in software engineering research. Of the three commonly suggested and used search methods: manual search, database search, or snowball search; systematic literature reviews and maps typically employ one or a combination of two or three of those as their search strategy. As systematic literature reviews and maps raise a claim to result in a representative set of relevant papers for a certain area of investigation, it is of importance to understand the impact the search strategy has on achieving this goal. [Aim] This paper contributes a study to compare all three search methods. This study aims at providing evidence as to what advantages and disadvantages of these three search methods are. [Method] We conducted three systematic literature reviews on the same topic, which affects multiple software engineering related disciplines, using different search methods, while keeping other parameters like inclusion and exclusion criteria consistent among all three reviews. [Results] Our results show a similar effectiveness for snowball and database search and the highest efficiency for database searches. However, our literature reviews led to three barely overlapping sets of papers, which in turn led to distinct impressions of the same field. [Conclusion] Our results show that the use of a single search method can lead to a set of included papers, which misrepresents the research field under investigation. Hence, particularly when conducting literature reviews that affect different software engineering sub-disciplines and related disciplines, researchers should not just rely on the single most effective and/or efficient search method.

Abstract Introduction Technology transfer aims at supporting the transfer of results from software engineering research from academia to industrial application. Objective This paper reports on the current state of technology transfer in software engineering. Method We conducted a systematic literature review, in which we investigated 3070 papers. We identified in total 70 relevant papers, which were subject of a detailed analysis. Results Many different approaches are proposed to foster technology transfer in software engineering. The majority of these approaches suggest direct collaboration between industry and academia or teaching new technologies in industrial training or university education. In addition, a considerable number of experience reports on technology transfer exist. Hence, a multitude of best practices, success stories, and lessons learned is reported. Among others, empirical evidence, maturity, and adaptability of the technology seem important preconditions for successful transfer, while social and organizational factors seem important barriers to successful technology transfer. Conclusion Our findings can aid software engineering researchers in determining how best to support the transfer of their research results into practice. Furthermore, analysis of the literature also revealed that no reports exist on the combination of various technology transfer approaches, which could increase advantages of existing approaches while reducing their disadvantages.

A significant challenge within university education, especially with regard to the teaching of highly theoretical topics like requirements engineering, is to maintain students' interest and motivation whilst addressing the core concepts that will enable students to work in industry upon graduation. It has long been established that experience-based learning can aid in both these feats: On the one hand, providing students with industrial case examples rather than "dry" academic assignments can increase student interest and motivation. On the other hand, a case example-centric classroom approach can yield a rich learning environment which fosters collaboration, communication, and self-directed exploration of the instructed principles. In previous work, we have reported on our experience in changing a graduate requirements engineering course towards using case examples based on real industry projects. As more and more curricula change in advance of project-based teaching paradigms, this paper discusses results from the long-term application of such a course design in a graduate setting. In addition, this paper reports our findings from the replication in an undergraduate requirements engineering course indicating that project-based learning techniques foster different teaching goals in graduate and undergraduate settings.

In empirical software engineering research, graduate students are often seen as legitimate substitutes for industry professionals. It has been also argued in the literature that the generalizability of empirical results from experiments with undergraduate students as participants holds to a much lower extent. In this paper, we report on a controlled experiment conducted separately with graduate students and undergraduate students in order to gain deeper insights whether the results from experiments with graduates and undergraduates in the software engineering field are equal or significantly different with respect to the conclusions that can be drawn. During the experiment, the students apply a specific validation technique for behavioral requirements of embedded software. We observed that graduates were significantly more effective, efficient, and confident in their tasks than the undergraduates. Nevertheless, the experiment with undergraduates also shows significant results, even though with a smaller effect size.

University education in software engineering instructs sound theoretical concepts together with method competence. It seeks to provide hands-on experience with the learning content along with insights into its application in practice. Even theoretical disciplines are beginning to adopt more experience-oriented instruction as opposed to passive, lecture-oriented instruction. One favored way for experience-oriented instructions is using case studies in lecture-accompanying assignments and/or tutorials. Compared with real-world scenarios, such case studies are often simplified in order to illustrate specific challenges related to the instructed material. This paper reports on our experience in using realistic industry-oriented case studies in a requirements engineering course with graduate students. The experience indicates a strong positive effect on student motivation as well as the degree of comprehension of the instructed theoretical material. These findings are confirmed by evaluations of the learning experience as self-reported through students' questionnaires. Comparing the exam results with previous years indicates substantial improvement in final exam scores.

Research in engineering disciplines has to keep track of current developments and challenges in industry to provide adequate solutions. As function-centered engineering of embedded systems is commonly used in industry to cope with several challenges (e.g., to deal with the increasing number of functions realized in software rather than in hardware, to reduce redundancy among functions implemented, to reduce the number of cost-intensive electronic control units and sensors, or to foster re-use of developed functions in multiple systems and environments), it is of importance for research to identify challenges and needs arising from function-centered engineering and to provide fitting solution concepts. To identify these industry needs, we recently conducted a study among German embedded industry. We used a combination of different investigation techniques (i.e. questionnaires, workshops and expert interviews, and case studies) to identify, concretize, and verify industry needs. Furthermore, possible solution ideas were developed and evaluated to (i) check appropriateness of identified needs and to gain more insights, as well as to (ii) provide first solution concepts suitable for industry. This paper discusses the evaluation method, the major results and the current state of the solution approach.

In the embedded systems industry, function-centered engineering is commonly applied to address the increasing number and complexity of system functions. During function-centered engineering, the functional design that is created based on the defined requirements for the system is the main artifact that serves as a basis for subsequent development activities. If stakeholder intentions change and modifications become necessary, they are frequently incorporated directly into the functional design without updating the behavioral requirements accordingly. As a consequence, the correctness of the interplay of system functions as defined in the functional design cannot be assessed by checking it against the defined requirements (since they are outdated) but needs to be checked against the current stakeholder intentions. More precisely, the requirements engineer has to validate the functional design against the stakeholder intentions because he is the expert concerning the stakeholder intentions and can communicate with the stakeholders regarding them, if necessary. However, the requirements engineer is typically not familiar with the functional design and its notation on the one hand, and, on the other hand, the overall behavior of the system is spread across various diagrams in the functional design. Therefore, the requirements engineer needs a more abstract and consolidated view of the functional design in order to be able to validate its correctness with regard to the current stakeholder intentions. In this paper, we present an approach which is based on a specific kind of review model that is automatically generated from the functional design and supports the requirements engineer in her task. The approach that is presented in this paper is subject of ongoing research.