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Abstract: Recently, an increasingly growing number of companies is focusing on achieving self-driving systems towards SAE level 3 and higher. Such systems will have much more complex capabilities than today's advanced driver assistance systems (ADAS) like adaptive cruise control and lane-keeping assistance. For complex software systems in the Web-application domain, the logical successor for Continuous Inte...
Abstract: Model-based development and continuous integration each separately are methods to improve the productivity of development of complex modern software systems. We investigate industrial adoption of these two phenomena in combination, i.e., applying continuous integration practices in model-based development projects. Through semi-structured interviews, eleven engineers at three companies with differ...
Abstract: Metrics, often visualized with dashboards, are considered crucial to help software start-ups focus on the right aspects during the first years. However, earlier research indicates, metric choices in emerging ecosystems are not necessarily the same as in literature, which mostly focuses on developed countries. More knowledge is required to provide dashboards that suite East African software startup...
Abstract: Deep learning is one of the most exciting and fast-growing techniques in Artificial Intelligence. The unique capacity of deep learning models to automatically learn patterns from the data differentiates it from other machine learning techniques. Deep learning is responsible for a significant number of recent breakthroughs in AI. However, deep learning models are highly dependent on the underlying ...
Abstract: Fog computing has been recently introduced to bridge the gap between cloud resources and the network edge. Fog enables low latency and location awareness, which is considered instrumental for the realization of IoT, but also faces reliability and dependability issues due to node mobility and resource constraints. This paper focuses on the latter, and surveys the state of the art concerning dependa...
Abstract: One way to improve the performance of embedded systems is through heterogeneous platforms, i.e., using hardware containing more than one type of processor, like CPU + GPU or CPU + FPGA. This approach has shown improved performance, particularly in the domain of artificial intelligence, in which computationally demanding models must be trained and executed. However, these computational environments...
Abstract: A wide variety of tools to monitor and track software systems, such as websites or smartphone applications, during runtime already exists. However, their aggregated results are often not sufficient to answer questions on a product management level since these questions address several levels of complexity and abstractions, and tend to be formulated on a rather high level, for instance concerning t...
Abstract: In recent years in the software industry, the use of safety-critical software is increasing at a rapid rate. However, little is known about the relationship between safety-critical regulations and the management of technical debt. The research is based on interviews with 19 practitioners working in different safety-critical domains implementing software according to different safety regulation sta...
Abstract: Linux source-code automated maintenance (by analyzing 35 semantic patches applied to 19 versions of Linux) and (ii) fixing energy anti-patterns existing in Android applications available on GitHub (by analyzing 22 anti-patterns rewriting rules on 19 Android applications). In ‘‘Variability management in safety-critical systems design & dependability analysis,...
Abstract: Much has been investigated about software reuse since the software crisis. The development of software reuse methods, implementation techniques, and cost models has resulted in a significant amount of research over years. Nevertheless, the increasing adoption of reuse techniques, many of them subsumed under higher level software engineering processes, and advanced programming techniques that ease ...
Abstract: Accurately learning what delivers value to customers is difficult. Online Controlled Experiments (OCEs), aka A/B tests, are becoming a standard operating procedure in software companies to address this challenge as they can detect small causal changes in user behavior due to product modifications (e.g. new features). However, like any data analysis method, OCEs are sensitive to trustworthiness and...
Abstract: Digitalization and servitization are impacting many domains, including the mining industry. As the equipment becomes connected and technical infrastructure evolves, business models and risk management need to adapt. In this paper, we present a study on how changes in asset and risk distribution are evolving for the actors in a software ecosystem (SECO) and system-of-systems (SoS) around a mining o...
Abstract: Although Model-Based Software Engineering (MBE) is a widely accepted Software Engineering (SE) discipline, no agreed-upon core set of concepts and practices (i.e., a Body of Knowledge) has been defined for it yet. With the goals of characterizing the contents of the MBE discipline, promoting a global consistent view of it, clarifying its scope with regard to other SE disciplines, and defining a fo...
Abstract: It has become widely accepted that the Internet of Things (IoT) devices and technologies are the key enablers for many emerging applications including remote health monitoring. Various physiological sensing devices have been designed and equipped with different radio technologies. The choice of radio hardware plays an important role on the overall performance of the system since it imposes some li...
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