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The software engineering research community is productive, yet it faces a constellation of challenges: swamped review processes, metric-driven incentives, distorted publication practices, and increasing pressures from AI, scale, and…
This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our…
The ever-increasing amount, variety as well as generation and processing speed of today's data pose a variety of new challenges for developing Data-Intensive Software Systems (DISS). As with developing other kinds of software systems,…
Context: Advancements in machine learning (ML) lead to a shift from the traditional view of software development, where algorithms are hard-coded by humans, to ML systems materialized through learning from data. Therefore, we need to…
Sustainable software ecosystems are difficult to build, and require concerted effort, community norms and collaborations. In science it is especially important to establish communities in which faculty, staff, students and open-source…
In the dynamic field of Software Engineering (SE), where practice is constantly evolving and adapting to new technologies, conducting research is a daunting quest. This poses a challenge for researchers: how to stay relevant and effective…
Many scientific-software projects test their codes inadequately, or not at all. Despite its well-known benefits, adopting routine testing is often not easy. Development teams may have doubts about establishing effective test procedures,…
It is impossible to separate the human factors from software engineering expertise during software development, because software is developed by people and for people. The intangible nature of software has made it a difficult product to…
Computational methods and associated software implementations are central to every field of scientific investigation. Modern biological research, particularly within systems biology, has relied heavily on the development of software tools…
Deep learning (DL) techniques have gained significant popularity among software engineering (SE) researchers in recent years. This is because they can often solve many SE challenges without enormous manual feature engineering effort and…
A key function of a software system is its ability to facilitate the manipulation of data, which is often implemented using a flavour of the Structured Query Language (SQL). To develop the data operations of software (i.e, creating,…
Programming is ubiquitous in applied biostatistics; adopting software engineering skills will help biostatisticians do a better job. To explain this, we start by highlighting key challenges for software development and application in…
Open Source Software (OSS) security and resilience are worldwide phenomena hampering economic and technological innovation. OSS vulnerabilities can cause unauthorized access, data breaches, network disruptions, and privacy violations,…
Orientation of modern software systems towards data-intensive processing raises new difficulties in software engineering on how to build and maintain such systems. Some of the important challenges concern the design of software…
Software development relies on effective collaboration between Software Development Engineers (SDEs) and User eXperience Designers (UXDs) to create software products of high quality and usability. While this collaboration issue has been…
Surprisingly promising results have been achieved by deep learning (DL) systems in recent years. Many of these achievements have been reached in academic settings, or by large technology companies with highly skilled research groups and…
The profile of research software engineering has been greatly enhanced by developments at institutions around the world to form groups and communities that can support effective, sustainable development of research software. We observe,…
Distribution of software development is becoming more and more common in order to save the production cost and reduce the time to market. Large geographical distance, different time zones and cultural differences in distributed software…
Software is primarily developed for people by people and human factors must be studied in all software engineering phases. Creativity is the source to improvise solutions to problems for dominating complex systems such as software…
Context: Software engineering researchers and practitioners rely on empirical evidence from the field. Thus, education of software engineers must include strong and applied education in empirical research methods. For most students, the…