Abstract: An increasingly important requirement for certain classes of software-intensive systems is the ability to self-adapt their structure and behavior at run-time when reacting to changes that may occur to the system, its environment, or its goals. A major challenge related to self-adaptive software systems is the ability to provide assurances of their resilience when facing changes. Since in these systems, the components that act as controllers of a target system incorporate highly complex software, there is the need to analyze the impact that controller failures might have on the services delivered by the system. In this paper, we present a novel approach for evaluating the resilience of self-adaptive software systems by applying robustness testing techniques to the controller to uncover failures that can affect system resilience. The approach for evaluating resilience, which is based on probabilistic model checking, quantifies the probability of satisfaction of system properties when the target system is subject to controller failures. The feasibility of the proposed approach is evaluated in the context of an industrial middleware system used to monitor and manage highly populated networks of devices, which was implemented using the Rainbow framework for architecture-based self-adaptation.

Abstract: Cyber-physical systems (CPS) are heterogeneous, because they tightly couple computation, communication and control along with physical dynamics, which are traditionally considered separately. Without a comprehensive modeling formalism, model-based development of CPS involves using a multitude of models in a variety of formalisms that capture various aspects of the system design, such as software design, networking design, physical models, and protocol design. Without a rigorous unifying framework, system integration and integration of the analysis results for various models remains ad hoc. In this paper, we propose a multi-view architecture framework that treats models as views of the underlying system structure and uses structural and semantic mappings to ensure consistency and enable system-level verification from that of the models in a hierarchical and compositional manner. Throughout the paper, the theoretical concepts are illustrated using two examples, an automotive intersection collision avoidance system and a quadrotor.

Abstract: As new market opportunities, technologies, platforms, and frameworks become available, systems require large-scale and systematic architectural restructuring to accommodate them. Today’s architects have few techniques to help them plan this architecture evolution. In particular, they have little assistance in planning alternative evolution paths, trading off various aspects of the different paths, or knowing best practices for particular domains. In this paper we describe an approach for planning and reasoning about architecture evolution. Our approach focuses on providing architects with the means to model prospective evolution paths and supporting analysis to select among these candidate paths. To demonstrate the usefulness of our approach, we show how it can be applied to an actual architecture evolution. In addition, we present some theoretical results about our evolution path constraint specification language.

Abstract: Requirements for high availability in computing systems today demand that systems be self-adaptive to maintain expected qualities-of-service in the presence of system faults, variable environmental conditions, and changing user requirements. Autonomic computing tackles the challenge of automating tasks that humans would otherwise have to perform to achieve this goal. However, existing approaches to autonomic computing lack the ability to capture routine human repair tasks in a way that takes into account the business context that humans use in selecting an appropriate form of adaptation, while dealing with timing delays and uncertainties in outcome of repair actions. In this article, we present Stitch, a language for representing repair strategies within the context of an architecture-based self-adaptation framework. Stitch supports the explicit representation of repair decision trees together with the ability to express business objectives, allowing a self-adaptive system to select a strategy that has optimal utility in a given context, even

Abstract: The Rainbow framework uses software architectures and a reusable infrastructure to support self-adaptation of software systems. The use of external adaptation mechanisms allows the explicit specification of adaptation strategies for multiple system concerns.

Abstract: The software architecture of most systems is usually described informally and diagrammatically by means of boxes and lines. In order for these descriptions to be meaningful, the diagrams are understood by interpreting the boxes and lines in specic, conventionalized ways. The informal, imprecise nature of these interpretations has a number of limitations. In this paper we consider these conventionalized interpretations as architectural styles and provide a formal framework for their uniform denition. In addition to providing a template for precisely dening new architectural styles, this framework allows for analysis within and between dierent architectural styles.

Abstract: In the world of autonomic computing, the ultimate aim is to automate human tasks in system management to achieve high-level stakeholder objectives. One common approach is to capture and represent human expertise in a form executable by a computer. Techniques to capture such expertise in programs, scripts, or rule sets are effective to an extent. However, they are often incapable of expressing the necessary adaptation expertise and emulating the subtleties of trade-offs in high-level decision making. In this paper, we propose a new language of adaptation that is suffi-ciently expressive to capture the subtleties of choice, deriving its ontology from system administration tasks and its underlying formalism from utility theory.

Abstract: Over the past 15 years there has been increasing recognition that careful attention to the design of a system�s software architecture is critical to satisfying its requirements for quality attributes such as performance, security, and dependability. As a consequence, during this period the field of software architecture has matured significantly. However, current practices of software architecture rely on relatively informal methods, limiting the potential for fully exploiting architectural designs to gain insight and improve the quality of the resulting system. In this paper we draw from a variety of research results to illustrate how formal approaches to software architecture can lead to enhancements in software quality, including improved clarity of design, support for analysis, and assurance that implementations conform to their intended architecture.

Abstract: Numerous architectural description languages (ADLs) have been developed, each providing complementary capabilities for architectural development and analysis. Unfortunately, each ADL and supporting toolset operates in isolation, making it difficult to integrate those tools and share architectural descriptions. ACME is being developed as a joint effort of the software architecture research community as a common interchange format for architecture design tools. ACME provides a structural framework for characterizing architectures, together with annotation facilities for additional ADL-specific information. This scheme permits subsets of ADL tools to share architectural information that is jointly understood, while tolerating the presence of information that falls outside their common vocabulary. In this paper we describe ACME's key features, rationale, and technical innovations.