Related papers: openSE: A Systems engineering framework particular…
Open source software is becoming crucial in the design and testing of quantum algorithms. Many of the tools are backed by major commercial vendors with the goal to make it easier to develop quantum software: this mirrors how well-funded…
In this paper, we introduce the concept of the research practice gap as it is perceived in the field of software requirements engineering. An analysis of this gap has shown that two key causes for the research-practice gap are lack of…
The development of Machine Learning (ML) based systems is complex and requires multidisciplinary teams with diverse skill sets. This may lead to communication issues or misapplication of best practices. Process models can alleviate these…
HEP data-processing software must support the disparate physics needs of many experiments. For both collider and neutrino environments, HEP experiments typically use data-processing frameworks to manage the computational complexities of…
Designing and analyzing algorithms with provable performance guarantees enables efficient optimization problem solving in different application domains, e.g.\ communication networks, transportation, economics, and manufacturing. Despite the…
Scalable and efficient numerical simulations continue to gain importance, as computation is firmly established as the third pillar of discovery, alongside theory and experiment. Meanwhile, the performance of computing hardware grows through…
The performance and safe operation of a particle accelerator is closely connected to the transverse emittance of the beams it produces. For this reason many techniques have been developed over the years for monitoring the transverse…
In the upcoming decades, the KM3NeT detectors will produce valuable data that can be used in various scientific contexts from astro- and particle physics to environmental and Earth and Sea science. Based on the Open Science policy…
Open science describes the movement of making any research artefact available to the public and includes, but is not limited to, open access, open data, and open source. While open science is becoming generally accepted as a norm in other…
Particle Accelerators are high power complex machines. To ensure uninterrupted operation of these machines, thousands of pieces of equipment need to be synchronized, which requires addressing many challenges including design, optimization…
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…
Hardware-based Trusted Execution Environments (TEEs) are widely deployed in mobile devices. Yet their use has been limited primarily to applications developed by the device vendors. Recent standardization of TEE interfaces by GlobalPlatform…
Smart system applications (SSAs) built on top of cyber-physical and socio-technical systems are increasingly composed of components that can work both autonomously and by cooperating with each other. Cooperating robots, fleets of cars and…
Using machine learning in clinical practice poses hard requirements on explainability, reliability, replicability and robustness of these systems. Therefore, developing reliable software for monitoring critically ill patients requires close…
Aerial autonomous machines (Drones) has a plethora of promising applications and use cases. While the popularity of these autonomous machines continues to grow, there are many challenges, such as endurance and agility, that could hinder the…
Human-Centric Software Engineering (HCSE) refers to the software engineering (SE) processes that put human needs and requirements as core practice throughout the software development life cycle. A large majority of software projects fail to…
Engineering the software development process in robotics is one of the basic necessities towards industrial-strength service robotic systems. A major challenge is to make the step from code-driven to model-driven systems. This is essential…
This work describes the setup of an advanced technical infrastructure for collaborative software development (CDE) in large, distributed projects based on GitLab. We present its customization and extension, additional features and processes…
AI-based systems are software systems with functionalities enabled by at least one AI component (e.g., for image- and speech-recognition, and autonomous driving). AI-based systems are becoming pervasive in society due to advances in AI.…
Reverse engineering has been a standard practice in the hardware community for some time. It has only been within the last ten years that reverse engineering, or "program comprehension", has grown into the current sub-discipline of software…