Integrating Security into the Undergraduate Software Engineering Curriculum

This research included a thorough examination of the existing software assurance or what is commonly called software security knowledge, methodologies and what information security technologies is currently being recommended by the information technology community. Finally it is demonstrated how this security knowledge could be incorporated into the curriculum for undergraduate software engineering

The content of software production course

Software production is an integral activity that encompasses the majority of computer science and information technologies knowledge and skills such as algorithms, programming, databases, networking etc. Referring to this, an introductory course on software production summarizes and upgrades the learning achievements of students in bachelor programs of computing. This paper focuses on some curriculum issues in software engineering course. The main discussion concerns the choice of the topics and learning activities. The course should expose fundamental concepts and principles that underlie current and emerging methods, tools, and techniques for cost-effective production of high-quality software systems

Global Perspectives on Cybersecurity Education for 2030: A Case for a Meta-discipline

Information security has been an area of research and teaching within various computing disciplines in higher education almost since the beginnings of modern computers. The need for security in computing curricula has steadily grown over this period. Recently, with an emerging global crisis, because of the limitations of security within the nascent information technology infrastructure, the field of “cybersecurity” is emerging with international interest and support. Recent evolution of cybersecurity shows that it has begun to take shape as a true academic perspective, as opposed to simply being a training domain for certain specialized jobs. This report starts from the premise that cybersecurity is a “meta-discipline.” That is, cybersecurity is used as an aggregate label for a wide variety of similar disciplines, much in the same way that the terms “engineering” and “computing” are commonly used. Thus, cybersecurity should be formally interpreted as a meta-discipline with a variety of disciplinary variants, also characterized through a generic competency model. The intention is that this simple organizational concept will improve the clarity with which the field matures, resulting in improved standards and goals for many different types of cybersecurity programs

An Investigation Dimension for Understanding and Characterizing Computing Disciplines

Computing disciplines are diverse and overlap extensively. ACM provides two dimensions, theory and target level, as a tool to describe the problem spaces of five disciplines of computing: computer science, information systems, information technology, computer engineering, and software engineering. However, there are still many studies reporting that even majors are not entirely clear about the scopes and tasks of their computing disciplines. Various supplementary approaches and models have been proposed to assist the understanding and characterization of computing disciplines, such as through computing traditions, research-focuses, and positions in the business-technology continuum. This paper proposes a new investigation dimension based on a popular inquiry approach as a complementary third dimension to serve as an additional high order lens for understanding computing disciplines. The application of the model on understanding and characterizing the five ACM disciplines and data science is discussed. The model encourages systematic critical thinking, meaningful learning, and deep reasoning

Teaching and practicing RE for agility

During the development of an information system, requirements might constantly change. The practice of Information Systems Engineering clearly evolved because of the adoption of agile methods. However, after practice and theory of agile development, teaching agile development should follow. We have to let our students experience agile development and to teach them how to deal with it, not only in theory but also in practice. E.g., in practice it is difficult to keep everything consistent in a constantly changing situation. Also, for students it is (very) strange that something which is judged good in an earlier stage might be judged wrong in a later stage. In this paper, we describe how we simulate agility in our course and how we let the students experience constantly changing requirements, and how we teach them how to handle that. And because of a sudden pandemic (COVID), we were forced to teach all this on-line, with all its educational restrictions (e.g., no personal meetings, limited human interaction/dynamics, etc.).</p

Teaching and practicing RE for agility

During the development of an information system, requirements might constantly change. The practice of Information Systems Engineering clearly evolved because of the adoption of agile methods. However, after practice and theory of agile development, teaching agile development should follow. We have to let our students experience agile development and to teach them how to deal with it, not only in theory but also in practice. E.g., in practice it is difficult to keep everything consistent in a constantly changing situation. Also, for students it is (very) strange that something which is judged good in an earlier stage might be judged wrong in a later stage. In this paper, we describe how we simulate agility in our course and how we let the students experience constantly changing requirements, and how we teach them how to handle that. And because of a sudden pandemic (COVID), we were forced to teach all this on-line, with all its educational restrictions (e.g., no personal meetings, limited human interaction/dynamics, etc.).</p

Modelling competencies for computing education beyond 2020: a research based approach to defining competencies in the computing disciplines.

How might the content and outcomes of tertiary education programmes be described and analysed in order to understand how they are structured and function? To address this question we develop a framework for modelling graduate competencies linked to tertiary degree programmes in the computing disciplines. While the focus of our work is computing the framework is applicable to education more broadly. The work presented here draws upon the pioneering curricular document for information technology (IT2017), curricular competency frameworks, other related documents such as the software engineering competency model (SWECOM), the Skills Framework for the Information Age (SFIA), current research in competency models, and elicitation workshop results from recent computing conferences. The aim is to inform the ongoing Computing Curricula (CC2020) project, an endeavour supported by the Association for Computing Machinery (ACM) and the IEEE Computer Society. We develop the Competency Learning Framework (CoLeaF), providing an internationally relevant tool for describing competencies. We argue that this competency based approach is well suited for constructing learning environments and assists degree programme architects in dealing with the challenge of developing, describing and including competencies relevant to computer and IT professionals. In this paper we demonstrate how the CoLeaF competency framework can be applied in practice, and though a series of case studies demonstrate its effectiveness and analytical power as a tool for describing and comparing degree programmes in the international higher education landscape

Teaching and practicing RE for agility

During the development of an information system, requirements might constantly change. The practice of Information Systems Engineering clearly evolved because of the adoption of agile methods. However, after practice and theory of agile development, teaching agile development should follow. We have to let our students experience agile development and to teach them how to deal with it, not only in theory but also in practice. E.g., in practice it is difficult to keep everything consistent in a constantly changing situation. Also, for students it is (very) strange that something which is judged good in an earlier stage might be judged wrong in a later stage. In this paper, we describe how we simulate agility in our course and how we let the students experience constantly changing requirements, and how we teach them how to handle that. And because of a sudden pandemic (COVID), we were forced to teach all this on-line, with all its educational restrictions (e.g., no personal meetings, limited human interaction/dynamics, etc.).</p

Teaching and practicing RE for agility

During the development of an information system, requirements might constantly change. The practice of Information Systems Engineering clearly evolved because of the adoption of agile methods. However, after practice and theory of agile development, teaching agile development should follow. We have to let our students experience agile development and to teach them how to deal with it, not only in theory but also in practice. E.g., in practice it is difficult to keep everything consistent in a constantly changing situation. Also, for students it is (very) strange that something which is judged good in an earlier stage might be judged wrong in a later stage. In this paper, we describe how we simulate agility in our course and how we let the students experience constantly changing requirements, and how we teach them how to handle that. And because of a sudden pandemic (COVID), we were forced to teach all this on-line, with all its educational restrictions (e.g., no personal meetings, limited human interaction/dynamics, etc.).</p

Teaching and practicing RE for agility

During the development of an information system, requirements might constantly change. The practice of Information Systems Engineering clearly evolved because of the adoption of agile methods. However, after practice and theory of agile development, teaching agile development should follow. We have to let our students experience agile development and to teach them how to deal with it, not only in theory but also in practice. E.g., in practice it is difficult to keep everything consistent in a constantly changing situation. Also, for students it is (very) strange that something which is judged good in an earlier stage might be judged wrong in a later stage. In this paper, we describe how we simulate agility in our course and how we let the students experience constantly changing requirements, and how we teach them how to handle that. And because of a sudden pandemic (COVID), we were forced to teach all this on-line, with all its educational restrictions (e.g., no personal meetings, limited human interaction/dynamics, etc.).</p