International audienceThe term model-driven engineering (MDE) is typically used to describe software development approaches in which abstract models of software systems are created and systematically transformed to concrete implementations. In this paper we give an overview of current research in MDE and discuss some of the major challenges that must be tackled in order to realize the MDE vision of software development. We argue that full realizations of the MDE vision may not be possible in the near to medium-term primarily because of the wicked problems involved. On the other hand, attempting to realize the vision will provide insights that can be used to significantly reduce the gap between evolving software complexity and the technologies used to manage complexity

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Agile processes focus on the early facilitation and fast production of working code, and are based on software-development process models that support iterative, incremental development of software. Although agile methods have existed for a number of years now, answers to questions concerning the suitability of agile processes to particular software-development environments are still often based on anecdotal accounts of experiences. An appreciation of the (often unstated) assumptions underlying agile processes can lead to a better understanding of the applicability of agile processes to particular situations. Agile processes are less likely to be applicable in situations in which core assumptions do not hold. This article examines the principles and advocated practices of agile processes to identify underlying assumptions. It also identifies limitations that may arise from these assumptions and outlines how the limitations can be addressed by incorporating other software-development techniques and practices into agile development environments.

In the near future, the Internet of Things is expected to penetrate all aspects of the physical world, including homes and urban spaces. In order to handle the massive amount of data that becomes collectible and to offer services on top of this data, the most convincing solution is the federation of the Internet of Things and cloud computing. Yet, the wide adoption of this promising vision, especially for application areas such as pervasive health care, assisted living, and smart cities, is hindered by severe privacy concerns of the individual users. Hence, user acceptance is a critical factor to turn this vision into reality. To address this critical factor and thus realize the cloud-based Internet of Things for a variety of different application areas, we present our comprehensive approach to privacy in this envisioned setting. We allow an individual user to enforce all her privacy requirements before any sensitive data is uploaded to the cloud, enable developers of cloud services to integrate privacy functionality already into the development process of cloud services, and offer users a transparent and adaptable interface for configuring their privacy requirements.