Computing systems form the backbone of many areas in our society, from manufacturing to traffic control, healthcare, and financial systems. When software plays a vital role in the design, construction, and operation, these systems are referred to as software-intensive systems. Self-adaptation equips a software-intensive system with a feedback loop that either automates tasks that otherwise need to be performed by human operators or deals with uncertain conditions. Such feedback loops have found their way to a variety of practical applications; typical examples are an elastic cloud to adapt computing resources and automated server management to respond quickly to business needs. To gain insight into the motivations for applying self-adaptation in practice, the problems solved using self-adaptation and how these problems are solved, and the difficulties and risks that industry faces in adopting self-adaptation, we performed a large-scale survey. We received 184 valid responses from practitioners spread over 21 countries. Based on the analysis of the survey data, we provide an empirically grounded overview the of state of the practice in the application of self-adaptation. From that, we derive insights for researchers to check their current research with industrial needs, and for practitioners to compare their current practice in applying self-adaptation. These insights also provide opportunities for applying self-adaptation in practice and pave the way for future industry-research collaborations.

Reference architectures (RAs) are successfully used to represent families of concrete software architectures in several domains such as automotive, banking, and the Internet of Things. RAs inspire architects when designing concrete architectures, and they help to guarantee compliance with architectural decisions, regulatory requirements, as well as architectural qualities. Despite their importance, reference architectures still suffer from a number of open technical issues, including (i) the lack of a common interpretation, a precise notation for their representation and documentation, and (ii) the lack of conformance mechanisms for checking the compliance of concrete architectures to their related reference architecture, architectural decisions, regulatory requirements, etc. This paper addresses these two issues by introducing a model-driven approach that leverages (i) a domain-independent metamodel for the representation of reference architectures and (ii) the combination of model transformation and weaving techniques for the automatic conformance checking of concrete architectures. We evaluate the applicability, effectiveness, and generalizability of our approach using illustrative examples from the web browsers and automotive domains, including an assessment from an independent practitioner.

The Android OS market is experiencing a growing share globally. It is becoming the mobile platform of choice for an increasing number of users. People rely on Android mobile devices for surfing the web, purchasing products, or to be part of a social network. The large amount of personal information that is exchanged makes privacy an important concern. As a result, the trustability of mobile apps is a fundamental aspect to be considered, particularly with regard to meeting the expectations of end users. The rigidities of the Android permission model confine end users into a secondary role, offering the only option of choosing between either privacy or functionalities. In this paper, we aim at improving the trustability of Android apps by proposing a user-centric approach to the flexible management of Android permissions.The proposed approach empowers end users to selectively grant permission by specifying (i) the desired level of permissions granularity and (ii) the specific features of the app in which the chosen permission levels are granted. Four experiments have been designed, conducted, and reported for evaluating it. The experiments consider performance, usability, and acceptance from both the end users and developers perspective. Results confirm confidence on the approach.