Related papers: POE-$\Delta$: a framework for change engineering
The Circular Economy (CE) is regarded as a solution to the environmental crisis. However, mainstream CE measures skirt around challenging the ethos of ever-increasing economic growth, overlooking social impacts and under-representing…
Evolving a software process model without a retrospective and, in consequence, without an understanding of the process evolution, can lead to severe problems for the software development organization, e.g., inefficient performance as a…
Brownfield engineering work involving legacy systems, incomplete documentation, and fragmented architectural knowledge poses unique challenges for the effective use of large language models (LLMs). Prior research has largely focused on…
[Context & Motivation] Adaptive systems are an important research area. The dominant reason for adaptivity in systems are changes in the environment. Thus, it is an important question how to model the environment and how to determine the…
Many organizations seek to ensure that machine learning (ML) and artificial intelligence (AI) systems work as intended in production but currently do not have a cohesive methodology in place to do so. To fill this gap, we propose MLTE…
Big data solutions are designed to cope with data of huge Volume and wide Variety, that need to be ingested at high Velocity and have potential Veracity issues, challenging characteristics that are usually referred to as the "4Vs of Big…
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…
Background: Diversity, equity, and inclusion are rooted in the very origins of software engineering, shaped by the contributions from many individuals from underrepresented groups to the field. Yet today, DEI efforts in the industry face…
Modeling environmental ecosystems is essential for effective resource management, sustainable development, and understanding complex ecological processes. However, traditional methods frequently struggle with the inherent complexity,…
Our aim in this paper is to outline how the design space for the ontologization process is broader than current practice would suggest. We point out that engineering processes as well as products need to be designed and identify some…
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…
Modern software systems undergo frequent updates, continuously evolving with new versions and variants to offer new features, improve functionality, and expand usability. Given the rapid pace of software evolution, organizations require…
Creating open-ended algorithms, which generate their own never-ending stream of novel and appropriately challenging learning opportunities, could help to automate and accelerate progress in machine learning. A recent step in this direction…
Background: Sustainable software engineering (SSE) means creating software in a way that meets present needs without undermining our collective capacity to meet our future needs. It is typically conceptualized as several intersecting…
In recent years Open Innovation (OI) has gained much attention and made firms aware that they need to consider the open environment surrounding them. To facilitate this shift Requirements Engineering (RE) needs to be adapted in order to…
Nowadays, scientific databases have become the bread-and-butter of particle physicists. These databases must be maintained and checked repeatedly to insure the accuracy of their content. The COMPETE collaboration aims at motivating data…
Pattern-Oriented Analysis and Design (POAD) is the practice of building complex software by applying proven designs to specific problem domains. Although a great deal of research and practice has been devoted to formalizing existing design…
The latest advancements in machine learning, specifically in foundation models, are revolutionizing the frontiers of existing software engineering (SE) processes. This is a bi-directional phenomona, where 1) software systems are now…
The proliferation of data across the system lifecycle presents both a significant opportunity and a challenge for Engineering Design and Systems Engineering (EDSE). While this "digital thread" has the potential to drive innovation, the…
As modern software systems expand in scale and complexity, the challenges associated with their modeling and formulation grow increasingly intricate. Traditional approaches often fall short in effectively addressing these complexities,…