Abstract. The goal of this roadmap paper is to summarize the stateof-the-art and identify research challenges when developing, deploying and managing self-adaptive software systems. Instead of dealing with a wide range of topics associated with the field, we focus on four essential topics of self-adaptation: design space for self-adaptive solutions, software engineering processes for self-adaptive systems, from centralized to decentralized control, and practical run-time verification & validation for self-adaptive systems. For each topic, we present an overview, suggest future directions, and focus on selected challenges. This paper complements and extends a previous roadmap on software engineering for self-adaptive systems published in 2009 covering a different set of topics, and reflecting in part on the previous paper. This roadmap is one of the many results of the Dagstuhl Seminar 10431 on Software Engineering for Self-Adaptive Systems, which took place in October 2010.

The intrinsic flexibility and dynamism of service-centric applications preclude their pre-release validation and demand for suitable probes to monitor their behavior at run-time. Probes must be suitably activated and deactivated ac- cording to the context in which the application is executed, but also according to the confidence we get on its quality. The paper supports the idea that significant data may come from very different sources and probes must be able to accommodate all of them. The paper presents: (1) an approach to specify monitoring directives, called monitoring rules, and weave them dynamically into the process they belong to; (2) a proxy-based solution to support the dynamic selection and execution of monitoring rules at run-time; (3) a user-oriented language to integrate data acquisition and analysis into monitoring rules

Self-adaptation is imposing as a key characteristic of many modern software systems to tackle their complexity and cope with the many environments in which they can operate. Self-adaptation is a requirement per-se, but it also impacts the other (conventional) requirements of the system; all these new and old requirements must be elicited and represented in a coherent and homogenous way. This paper presents FLAGS, an innovative goal model that generalizes the KAOS model, adds adaptive goals to embed adaptation countermeasures, and fosters self-adaptation by considering requirements as live, runtime entities. FLAGS also distinguishes between crisp goals, whose satisfaction is boolean, and fuzzy goals, whose satisfaction is represented through fuzzy constraints. Adaptation countermeasures are triggered by violated goals and the goal model is modified accordingly to maintain a coherent view of the system and enforce adaptation directives on the running system. The main elements of the approach are demonstrated through an example application.

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Service-based approaches are widely used to integrate heterogenous systems. Web services allow for the definition of highly dynamic systems where components (services) can be discovered and QoS parameters negotiated at run-time. This justifies the need for monitoring service compositions at run-time. Research on this issue, however, is still in its infancy. We investigate how to monitor dynamic service compositions with respect to contracts expressed via assertions on services. Dynamic compositions are represented as BPEL processes which can be monitored at run-time to check whether individual services comply with their contracts. Monitors can be automatically defined as additional services and linked to the service composition. We present two alternative implementations of our monitoring approach: one based on late-binding and reflection and the other based on a standard assertion system. The two implementations are exemplified on a case study.