As applications grow in size and complexity, and computing infrastructure continues to evolve, it becomes increasingly difficult to build a system that satisfies all requirements and constraints that might arise during its lifetime. As a result, there is an increasing need for software to adapt in response to new requirements and environmental conditions after it has been deployed. Due to their high complexity, adaptive programs are generally difficult to specify, design, verify, and validate. In addition, the current lack of reusable design expertise that can be leveraged from one adaptive system to another further exacerbates the problem. To address this problem, we studied over thirty adaptation-related research and project implementations available from the literature and open sources to harvest adaptation-oriented design patterns that support the development of adaptive systems. These patterns facilitate the separate development of the functional logic and the adaptive logic. We present these design patterns within the context of a modeling-based development process for dynamically adaptive systems. In order to address the assurance of these adaptive systems, the patterns also include templates for formally specifying invariant properties of adaptive systems.

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a b s t r a c tInordertobeabletoflexiblyadjustacompany'sbusinessprocesses(BPs)thereisanincreasing interest in flexible process-aware information systems (PAISs). This increasing flexibility, however, typically implies decreased user guidance by the PAIS and thus poses significant challenges to its users. As a major contribution of this work, we propose a recommendation system which assists users during process execution to optimize performance goals of the processes. The recommendation system is based on a constraint-based approach for planning and scheduling the BP activities and considers both the control-flow and the resource perspective. To evaluate the proposed constraint-based approach different algorithms are applied to a range of test models of varyingcomplexity. The results indicate that, although the optimization of process execution is a highly constrained problem, the proposed approach produces a satisfactory number of suitable solutions.

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