In previous work, we have provided a substantive amount of evidence that shows that Calibrated Peer Reviews to facilitate a feeling of “quality” in software engineering students have a strongly positive impact on student learning. Peer reviews repeatedly expose students to examples of different quality and force students to articulate engineering tradeoffs. Using calibration examples of different quality guides students in their evaluation of peer solutions and fosters an appreciation between good and bad solutions to exercise problems in requirements engineering and testing. The result is a significant improvement in test scores and theory retention, however, the overhead for the instructor to facilitate the peer review process outweighs the time saved for grading. In this article, we introduce “CPRtool” to automate collection and distribution of student solutions and peer feedback.

From theory and technical skills to self-management and interpersonal skills, and to role-specific knowledge such as DevOps or Requirements Engineering, students struggle to become proficient in all aspects to Software Engineering before graduating, while instructors struggle to prepare students for industry. Project-based instruction has become a de-facto standard to teach skills and knowledge. Many project-based courses focus on implementation, wherein students tend to adopt third-party technologies without critical reflection. This leads to insufficient knowledge about supply chain risk management (SCRM). The result is that students are inadequately prepared to handle risks to project success due to third-party acquisitions, including usage rights, introduction of security vulnerabilities, or their ability to identify and mitigate acquisition risks. In this paper, we present a capstone-style project-based course to deliver an industry-realistic and teamwork-centric software development approach. We propose incorporating Technology Acquisition Plans, which are based on an existing SCRM curriculum, and add acquisition planning, bidding, and risk monitoring activities to the project and development activities. Empirical evaluation and classroom observations show that while students' ability to justify the need for third-party acquisitions remains the same, self-reported ability to evaluate and bid on alternatives is improved. Furthermore, statistically significant improvement can be seen in areas pertaining to risk monitoring, problem detection, and problem resolution.

Autonomous systems are susceptible to unknown safety issues due to overlooked dependencies among components of the system and the entities that are part of its operating environment. The current safety analysis techniques aids in identifying known safety issues but not overlooked/unknown safety issues. To identify unknown safety issues due to problematic interactions between components, in our previous work, we proposed safety assessment for concurrent components (SACC). Despite being more effective than FMEA and goal modeling, SACC suffers from some limitations such as not considering environmental entities and their properties, and a manual process for identifying associated components for the collective analysis. For a complex system with a large number of components, such an analysis can result in overlooking safety issues. To address these limitations, in this paper, we propose an association-driven safety analysis (ADSA) approach, which is extended and built on SACC. The approach uses a property-relation (PR) table and modified association rule mining algorithm to identify components and environmental entities that need to be considered together to detect overlooked or unknown safety issues. We evaluated our approach using four robotic systems and compared with SACC and systems theoretic process analysis (STPA). Our results show that our proposed approach, in particular using behavioral dependencies, is effective at exposing unknown safety issues.

Requirements engineering (RE) is an essential part of the software development process. Good RE, among others, is the basis for high quality software, considerably reduces the risk for software projects to fail entirely or with budget-overspending and is crucial for coordinating systems and software engineering. Thus, RE education is a vital part of software engineering curricula. However, a central concept of what RE education comprise and how to best teach RE is lacking. Therefore, we conducted a systematic literature review of the field and provide a systematic map describing the state of the RE education field. Results for key trends in RE instruction of the past decade include involvement of real or realistic stakeholders, teaching predominantly elicitation as an RE activity, and increasing student factors such as motivation or communication skills.

One of the key aspects of software engineering is to ensure the developed software meets stakeholder expectations in terms of functional requirements as well as the apparent quality. But achieving high software quality is not just a question of conducting thorough requirements engineering and quality assurance, it is also a question of doing so meticulously and with the necessary level of attention to detail. Yet, software engineering education is mostly concerned with instructing technical knowledge (e.g., unit testing) and organizational soft skills (e.g., working in teams). Teaching the learner proper appreciation of quality, not just in terms of executing techniques, but also in terms of alternative solutions, design trade-offs, advantages, and limitations of engineering decisions is rarely an explicit learning outcome in specialized software engineering courses. We therefore propose the systematic application of calibrated peer reviews as a mechanism to expose the learner to as many different solutions as possible during skill-based knowledge acquisition. In this paper, we discuss in detail the application of calibrated peer reviews in a requirements engineering course and in a quality assurance course. Application results show that using calibrated peer reviews during skill acquisition (i.e., homework assignments) positively affects students’ ability to apply theory and skills in both specification and quality assurance tasks. Our results show further that while calibrated peer reviews have a positive significant effect to apply and retain course theory, the effect on their ability to produce high quality engineering documents is marginally positive and limited to specification tasks.

Requirements engineering (RE) has established itself as a core software engineering discipline. It is well acknowledged that good RE leads to higher quality software and considerably reduces the risk of failure or budget-overspending of software development projects. It is of vital importance to train future software engineers in RE and educate future requirements engineers to adequately manage requirements in various projects. To this date, there exists no central concept of what RE education shall comprise. To lay a foundation, we report on a systematic literature review of the field and provide a systematic map describing the current state of RE education. Doing so allows us to describe how the educational landscape has changed over the last decade. Results show that only a few established author collaborations exist and that RE education research is predominantly published in venues other than the top RE research venues (i.e., in venues other than the RE conference and journal). Key trends in RE instruction of the past decade include involvement of real or realistic stakeholders, teaching predominantly elicitation as an RE activity, and increasing student factors such as motivation or communication skills. Finally, we discuss open opportunities in RE education, such as training for security requirements and supply chain risk management, as well as developing a pedagogical foundation grounded in evidence of effective instructional approaches.

Abstract When developing cyber‐physical systems (CPS), the context is of vital importance. CPS interact with the world not only through sensing the environment and acting upon it (like embedded systems) but also by communicating with other CPS (like systems in the Internet of Things [IoT]). This means that the context interactions CPS must deal with are much greater than regular embedded or IoT systems: On the one hand, external systems and human users constrain the specific interaction among them. On the other hand, properties of these external systems, human users, and laws, regulations, or standards constrain the way the CPS must be developed. In this paper, we propose a comprehensive, ontologically grounded context modeling framework to systematically explore the problem space in which a CPS under development will operate. This allows for the systematic elicitation of requirements for the CPS, early validation and verification of its properties, and safety assessment of its context interactions at runtime.

Abstract In cyber‐physical systems such as robots and automated vehicles that rely heavily on batteries, safety, and energy conservation can result conflicting requirements when not considered together. In systems engineering, the development begins at a concept phase where we have high‐level information of different components of the system. During the concept phase, we perform hazard analysis and risk assessment, define safety goals, and derive safety requirements. This means requirement engineering occurs at the end of the concept phase. However, energy conservation recommendations are not taken into consideration until the detailed design with specific hardware and software is known. Hence, it is possible to recommend energy conservation behaviors that can compromise system's safety. If we perform a trade‐off analysis between safety and energy conservation at a concept phase, we can propose various design alternatives and choose the best one that offers a safe and energy saving architecture. To achieve this goal, we propose an approach for identifying safety issues that can be caused by energy conservation recommendations. To evaluate the effectiveness of our approach, we performed an empirical study on four robotic systems. Our results show that we can find energy conservation recommendations that can compromise safety at a concept phase.

Abstract One central aspect of software engineering research is the transfer of the proposed approaches into industrial practice. In the past, a number of technology transfer approaches and experiences from technology transfer projects in software engineering have already been reported. However, many researchers still struggle to get their research results noticed by practitioners. To investigate what is important to practitioners, we conducted a mixed‐methods study that provides us with reliable quantitative data as well as deeper insights from qualitative data. Our results show that there is a mismatch between industry professionals' needs and commonly proposed technology transfer approaches in the software engineering field. For instance, collaboration between industry and academia as well as participation in empirical evaluations is not deemed important from an industry point of view. In contrast, industry professionals emphasize the use of company‐specific pilot projects conducted by industry and the need for experts to be available in every phase of technology transfer.

This work in progress paper reports the software engineering activities involved in designing and implementing an institutional peer code review (IPCR) tool. The platform aims to help novice computer science (CS1) students at a particular institution understand Java introductory programming concepts and improve their programming skills while learning from instructors and peers. Over 200 students enrolled in CS1 programming course experience difficulty understanding basic concept such as loops, methods, and classes. Consequently, students may be forced to repeat CS1 courses or, discouraged from continuing their major resulting in a discontinuation of their CS education. Prior studies show that peer code review(PCR) can help address this problem as a collaborative learning approach. However, the methods used in those studies were not done using a tool that was built to help students with little or no programming experience. The goal of this research is therefore to develop an IPCR tool using software engineering principles that facilitates instructor-to-student and peer-to-peer learning. Students shall be able to access the platform 24/7, submit java code and receive feedback from instructors or peers. This will not only help students understand programming principles and identify common novice programmers’ mistakes but will also improve students understanding and programming skills. We report on the progress of our tool.

Requirements engineering (RE) has established itself as a core software engineering discipline. It is well acknowledged that good RE leads to higher quality software and considerably reduces the risk of failure or exceeding budgets of software development projects. Therefore, it is of vital importance to train future software engineers in RE and educate future requirements engineers to adequately manage requirements in various projects. However, to date there exists no central concept of what the most useful educational approaches are in RE education in order to best interweave theory with practice. To lay the foundation for this important mission, we conducted a systematic literature review. In this paper, we report on the results and provide a synthesis of instructional approaches in RE education. Findings show that experiential learning through projects, collaboration, and realistic stakeholder involvement are among the most promising trends to teach both RE theory and develop student soft skills.

In the last 30 years, the demands placed on software engineers have increased considerably. This is because the systems they develop increase in complexity, size, and criticality as well. Novel system types like adaptive systems or cyber physical systems and new technologies, like artificial intelligence and virtual reality, change the technology landscape. Professionals creating such systems hence need to stay on the cutting edge to face the challenges of the future.

In recent years, there has been an increase in automation of safety critical systems such as self-driving cars, caretaking robots, or rescue drones. With increase in automation, the risk of systems behaving in an undesired manner has also risen. Most safety analysis approaches predominantly concentrate on identifying or assessing how the failure of a component can affect the behavior of a system based on the system's requirements. Yet, undesired behaviors can also occur when multiple components concurrently exert opposite effects on a shared resource. To identify safety-critical issues due to undesired concurrent component behaviors, we propose a property-driven approach called safety assessment for concurrent components (SACC). SACC uses a combinatorial technique that considers the requirements specification of a system, expressed as the states and properties of the system's components for identifying undesired combinations of component behaviors. To evaluate SACC, we performed a study using a requirements document on a caretaking robot. Our results show that SACC identified 38%-80% more undesired system behaviors when compared to the control techniques.

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.

Cyber-physical systems interact closely at runtime with their operational context, i.e., other systems, users, and external entities. Therefore, eliciting and documenting interactions with the operational context allows documenting rationales for design decisions, which is essential to define a system architecture that suits the system’s purpose. For cyber-physical systems acting in system networks, this task becomes challenging since these networks can change at runtime, because individual systems can leave or join a network spontaneously. Hence, it becomes impossible to predict at design time the operational contexts at runtime. To aid context analysis and specification of such systems, this paper contributes a solution approach where the context of a system is not defined based on a static system boundary but depends on the specific intended use. We propose a view-centric perception of the operational context to leverage the functionality of external systems. This allows differentiating between functionality offered by the cyber-physical system network as a whole and the functionality provided by each individual system. An evaluation with an industrial case example and industry collaboration shows that this approach allows making suitable assumptions of the operational context at design time to guide architecture decisions.

In software and IT systems engineering, personal characteristics are expected to impact performance and attitude. To clarify the optimal composition in a team of students in academic education, we researched the relationship between student personality characteristics and learning effectiveness of teams using the Five Factor and Stress theory (FFS). The results taken from a Project-based Learning (PBL) course at Waseda University showed that educational effectiveness is highest when a team consists of management and anchor types without leadership types. In addition to FFS, we are currently adopting the Five Factor Model (FFM), which is a well-accepted personal characteristic model, to dig deeper the relationship in different courses on IT systems and software development conducted at various universities. Preliminary results show that although individual characteristics are not strongly correlated to learning effectiveness, there are a few strong team correlations. As our future work, we plan to acquire more data and investigate relationship between FFS measurements and FFM ones in terms of learning effectiveness.

Although working in teams is an effective method for students to learn skills necessary for information systems, the optimal combination of team members to maximize the learning effectiveness has yet to be clarified. This study investigates the relationship between the combination of students' personality characteristics and learning effectiveness in three information system lecture courses. Two Five Factor Model (FFM) questionnaires were used to determine each student's personality characteristic. For each course, which has different styles, several different relationships are found. This study should assist educators in maximizing students' learning effectiveness in information systems courses involving teamwork.

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.

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.