No abstract

Autonomous systems are gaining momentum in various application domains, such as autonomous vehicles, autonomous transport robotics and self-adaptation in smart homes. Product liability regulations impose high standards on manufacturers of such systems with respect to dependability (safety, security and privacy). Today's conventional engineering methods are not adequate for providing guarantees with respect to dependability requirements in a costefficient manner, e.g. road tests in the automotive industry sum up millions of miles before a system can be considered sufficiently safe. System engineers will no longer be able to test and respectively formally verify autonomous systems during development time in order to guarantee the dependability requirements in advance. In this vision paper, we introduce a new holistic software systems engineering approach for autonomous systems, which integrates development time methods as well as operation time techniques. With this approach, we aim to give the users a transparent view of the confidence level of the autonomous system under use with respect to the dependability requirements. We present already obtained results and point out research goals to be addressed in the future.

No abstract

The Internet of Things (IoT) is maturing and more and more IoT platforms that give access to things are emerging. However, the real potential of the IoT lies in growing IoT cross-domain ecosystems on top of these platforms that will deliver new, unanticipated value added applications and services. We identified two crucial aspects that are important to grow an IoT ecosystem: (i) interoperability to enable cross-platform and even cross-domain application developments on top of IoT platforms as well as (ii) marketplaces to share and monetize IoT resources. Having these two crucial pillars of an IoT ecosystem in mind, we present in this article the BIG IoT architecture as the foundation to establish IoT ecosystems. The architecture fulfills essential requirements that have been assessed among industry and research organizations as part of the BIG IoT project. We demonstrate a first proof-of-concept implementation in the context of an exemplary smart cities scenario.

There is an increasing necessity to deploy autonomous systems in highly heterogeneous, dynamic environments, e.g. service robots in hospitals or autonomous cars on highways. Due to the uncertainty in these environments, the verification results obtained with respect to the system and environment models at design-time might not be transferable to the system behavior at run time. For autonomous systems operating in dynamic environments, safety of motion and collision avoidance are critical requirements. With regard to these requirements, Maček et al. [6] define the passive safety property, which requires that no collision can occur while the autonomous system is moving. To verify this property, we adopt a two phase process which combines static verification methods, used at design time, with dynamic ones, used at run time. In the design phase, we exploit UPPAAL to formalize the autonomous system and its environment as timed automata and the safety property as TCTL formula and to verify the correctness of these models with respect to this property. For the runtime phase, we build a monitor to check whether the assumptions made at design time are also correct at run time. If the current system observations of the environment do not correspond to the initial system assumptions, the monitor sends feedback to the system and the system enters a passive safe state.

Abstract-In practice, more and more software development projects are distributed, ranging from partly distributed teams to global projects with each stakeholder located differently. Teaching actual practice in software engineering at university needs a proper mixture of theory and practice. But setting up practical exercises for global software engineering is hard, because students have to cooperate across different locations and situations reflecting the teaching intentions have to be provoked explicitly.This paper presents the concepts behind our common teaching environment for global software engineering -the GloSELab. It describes the experiences on setting up a distributed course and reports our teaching intentions based on each universities main focus: project management, requirements engineering & quality assurance, architecture, and implementation. Furthermore, we discuss our setup -a stage-gate process, where each location takes care of a different phase -and report occurred problems and how they supported or interfered with our teaching intentions.

Global software engineering has become a fact in many companies due to real necessity in practice. In contrast to co-located projects global projects face a number of additional software engineering challenges. Among them quality management has become much more difficult and schedule and budget overruns can be observed more often. Compared to co-located projects global software engineering is even more challenging due to the need for integration of different cultures, different languages, and different time zonesacross companies, and across countries. The diversity of development locations on several levels seriously endangers an effective and goal-oriented progress of projects. In this position paper we discuss reasons for global development, sketch settings for distribution and views of orchestration of dislocated companies in a global project that can be seen as a "virtual project environment". We also present a collection of questions, which we consider relevant for global software engineering. The questions motivate further discussion to derive a research agenda in global software engineering.

In the digital Economy 'Data is the new oil. In the last decade technology has disrupted every filed imaginable. One such booming technology is Blockchain. A blockchain is essentially a distributed database of records or public ledger of all transactions or digital events that have been executed and shared among participating parties. And once entered, the information is immutable. Ongoing projects and prior work in the fields of big data, data mining and data science has revealed how relevant data can be used to enhance products and services. There are uncountable applications and advantages of relevant data. The most valuable companies of today treat data as a commodity, which they trade and earn revenues. But use of relevant data has also drawn attention by the other nonconventional organizations and domains. To facilitate such trading, data marketplaces have emerged. In this paper we present a global data marketplace for users to easily buy and share data. The main focus of this research is to have a central data sharing platform for the recycling industry. This paper is a part of the research project "Recycling 4.0" which is focusing on sustainably improving the recycling process through exchange of information. We identify providing secure platform, data integrity and data quality as some major challenges for a data marketplace. In this paper we also explore how global data marketplace could be implemented using blockchain and similar technologies. CCS Concepts • Information systems → World Wide Web → Web applications → Electronic commerce → Electronic data interchange • Security and privacy → Systems security → Distributed systems security • Computer systems organization → Architectures → Distributed architectures