Related papers: Towards Model-Driven Dashboard Generation for Syst…

In this work, we reflect on the data-driven modeling paradigm that is gaining ground in AI-driven automation of patient care. We argue that the repurposing of existing real-world patient datasets for machine learning may not always…

Autonomous driving progress relies on large-scale annotated datasets. In this work, we explore the potential of generative models to produce vast quantities of freely-labeled data for autonomous driving applications and present…

Deep Neural Networks trained in a fully supervised fashion are the dominant technology in perception-based autonomous driving systems. While collecting large amounts of unlabeled data is already a major undertaking, only a subset of it can…

Traditional methods for performance appraisal are not suitable for agile fast-paced software companies. This has been a realization in the software industry since the early adoption of agile methodologies. Nonetheless, software companies…

Software Cockpits, also known as Software Project Control Centers, support the management and controlling of software and system development projects and provide means for quantitative measurement-based project control. Currently, many…

Context: The systems comprising a system of systems (SoS) are inde- pendently acquired, operated, and managed. Frequently, the architecture documentation of these existing systems addresses only a stand-alone perspective, and must be…

More and more enterprises recently intend to deploy data management systems in the cloud. Due to the professionalism of software development, it has still been difficult for non-programmers to develop this kind of systems, even a small one.…

The Internet of Things (IoT) envisions the integration of physical objects into software systems for automating crucial aspects of our lives, such as healthcare, security, agriculture, and city management. Although the vision is promising,…

Growing scale of recommender systems require extensive tuning to respond to market dynamics and system changes. We address the challenge of tuning a large-scale ads recommendation platform with multiple continuous parameters influencing key…

We contribute a deep-learning-based method that assists in designing analytical dashboards for analyzing a data table. Given a data table, data workers usually need to experience a tedious and time-consuming process to select meaningful…

The growing complexity of software systems as well as changing conditions in their operating environment demand systems that are more flexible, adaptive and dependable. The service-oriented computing paradigm is in widespread use to support…

Accountability is an often called for property of technical systems. It is a requirement for algorithmic decision systems, autonomous cyber-physical systems, and for software systems in general. As a concept, accountability goes back to the…

Component-Based Development (CBD) is a popular approach to mitigating the costs of creating software systems. However, it is not clear to what extent the core component selection and adaptation activities of CBD can be implemented to…

Gaining profound insights from collected data of today's application domains like IoT, cyber-physical systems, health care, or the financial sector is business-critical and can create the next multi-billion dollar market. However, analyzing…

In the automotive industry, platform configuration and software integration are mostly manual tasks performed during the development phase, requiring consideration of various safety and non-safety requirements. This manual process often…

Building models from data is an integral part of the majority of data science workflows. While data scientists are often forced to spend the majority of the time available for a given project on data cleaning and exploratory analysis, the…

The global availability of communication services makes it possible to interconnect independently developed systems, called constituent systems, to provide new synergistic services and more efficient economic processes. The characteristics…

Service Oriented Architecture is a loosely coupled architecture designed to tackle the problem of Business Infrastructure alignment to meet the needs of an organization. A SOA based platform enables the enterprises to develop applications…

In the age of the Cloud and so-called Big Data systems must be increasingly flexible, reconfigurable and adaptable to change in addition to being developed rapidly. As a consequence, designing systems to cater for evolution is becoming…

We propose a novel model- and feature-based approach to development of vehicle software systems, where the end architecture is not explicitly defined. Instead, it emerges from an iterative process of search and optimization given certain…