Holger Giese

Engineering Self-Adaptive Systems through Feedback Loops

To deal with the increasing complexity of software systems and uncertainty of their environments, software engineers have turned to self-adaptivity. Self-adaptive systems are capable of dealing with a continuously changing environment and emerging requirements that may be unknown at design-time. However, building such systems cost-effectively and in a predictable manner is a major engineering challenge. In this paper, we explore the state-of-the-art in engineering self-adaptive systems and identify potential improvements in the design process. Our most important finding is that in designing self-adaptive systems, the feedback loops that control self-adaptation must become first-class entities. We explore feedback loops from the perspective of control engineering and within existing self-adaptive systems in nature and biology. Finally, we identify the critical challenges our community must address to enable systematic and well-organized engineering of self-adaptive and self-managing software systems.

Software Engineering for Self-Adaptive Systems: A Second Research Roadmap

The goal of this roadmap paper is to summarize the state-of-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.

Towards the compositional verification of real-time UML designs

Current techniques for the verification of software as e.g. model checking are limited when it comes to the verification of complex distributed embedded real-time systems. Our approach addresses this problem and in particular the state explosion problem for the software controlling mechatronic systems, as we provide a domain specific formal semantic definition for a subset of the UML 2.0 component model and an integrated sequence of design steps. These steps prescribe how to compose complex software systems from domain-specific patterns which model a particular part of the system behavior in a well-defined context. The correctness of these patterns can be verified individually because they have only simple communication behavior and have only a fixed number of participating roles. The composition of these patterns to describe the complete component behavior and the overall system behavior is prescribed by a rigorous syntactic definition which guarantees that the verification of component and system behavior can exploit the results of the verification of individual patterns.

From model transformation to incremental bidirectional model synchronization

The model-driven software development paradigm requires that appropriate model transformations are applicable in different stages of the development process. The transformations have to consistently propagate changes between the different involved models and thus ensure a proper model synchronization. However, most approaches today do not fully support the requirements for model synchronization and focus only on classical one-way batch-oriented transformations. In this paper, we present our approach for an incremental model transformation which supports model synchronization. Our approach employs the visual, formal, and bidirectional transformation technique of triple graph grammars. Using this declarative specification formalism, we focus on the efficient execution of the transformation rules and how to achieve an incremental model transformation for synchronization purposes. We present an evaluation of our approach and demonstrate that due to the speedup for the incremental processing in the average case even larger models can be tackled.

On Patterns for Decentralized Control in Self-Adaptive Systems

Self-adaptation is typically realized using a control loop. One prominent approach for organizing a control loop in self-adaptive systems is by means of four components that are responsible for the primary functions of self-adaptation: Monitor, Analyze, Plan, and Execute, together forming a MAPE loop. When systems are large, complex, and heterogeneous, a single MAPE loop may not be sufficient for managing all adaptation in a system, so multiple MAPE loops may be introduced. In self-adaptive systems with multiple MAPE loops, decisions about how to decentralize each of the MAPE functions must be made. These decisions involve how and whether the corresponding functions from multiple loops are to be coordinated (e.g., planning components coordinating to prepare a plan for an adaptation). To foster comprehension of self-adaptive systems with multiple MAPE loops and support reuse of known solutions, it is crucial that we document common design approaches for engineers. As such systematic knowledge is currently lacking, it is timely to reflect on these systems to: (a) consolidate the knowledge in this area, and (b) to develop a systematic approach for describing different types of control in self-adaptive systems. We contribute with a simple notation for describing interacting MAPE loops, which we believe helps in achieving (b), and we use this notation to describe a number of existing patterns of interacting MAPE loops, to begin to fulfill (a). From our study, we outline numerous remaining research challenges in this area.

Incremental model synchronization with triple graph grammars

The advent of model-driven software development has put model transformations into focus. In practice, model transformations are expected to be applicable in different stages of a development process and help to consistently propagate changes between the different involved models which we refer to as model synchronization. However, most approaches do not fully support the requirements for model synchronization today and focus only on classical one-way batch-oriented transformations. In this paper, we present our approach for an incremental model transformation which supports model synchronization. Our approach employs the visual, formal, and bidirectional transformation technique of triple graph grammars. Using this declarative specification formalism, we focus on the efficient execution of the transformation rules and present our approach to achieve an incremental model transformation for synchronization purposes. We present an evaluation of our approach and demonstrate that due to the speedup for the incremental processing in the average case even larger models can be tackled.

Symbolic invariant verification for systems with dynamic structural adaptation

The next generation of networked mechatronic systems will be characterized by complex coordination and structural adaptation at run-time. Crucial safety properties have to be guaranteed for all potential structural configurations. Testing cannot provide safety guarantees, while current model checking and theorem proving techniques do not scale for such systems. We present a verification technique for arbitrarily large multi-agent systems from the mechatronic domain, featuring complex coordination and structural adaptation. We overcome the limitations of existing techniques by exploiting the local character of structural safety properties. The system state is modeled as a graph, system transitions are modeled as rule applications in a graph transformation system, and safety properties of the system are encoded as inductive invariants (permitting the verification of infinite state systems). We developed a symbolic verification procedure that allows us to perform the computation on an efficient BDD-based graph manipulation engine, and we report performance results for several examples.

Modular design and verification of component-based mechatronic systems with online-reconfiguration

The development of complex mechatronic systems requires a careful and ideally verifiable design. In addition, engineers from different disciplines, namely mechanical, electrical and software engineering, have to cooperate. The current technology is to use block diagrams including discrete blocks with statecharts for the design and verification of such systems. This does not adequately support the verification of large systems which improve the system behavior at run-time by means of online reconfiguration of its controllers because the system as whole has to be verified. It also does not support cooperative interdisciplinary work because a white-box view on all blocks involved in the online reconfiguration is required. This paper proposes a rigorous component concept based on the notion of UML component diagrams which enables modular composition and decomposition of complex systems with online reconfiguration given by hierarchical hybrid component specifications. The approach enables compatibility checks between components that are often independently developed (across the different disciplines) and supports compositional model checking based on a rigorously defined semantics.

Tool integration at the meta-model level: the Fujaba approach

Today’s development processes employ a variety of notations and tools, e.g., the Unified Modeling Language UML, the Standard Description Language SDL, requirements databases, design tools, code generators, model checkers, etc. For better process support, the employed tools may be organized within a tool suite or integration platform, e.g., Rational Rose or Eclipse. While these tool-integration platforms usually provide GUI adaption mechanisms and functional adaption via application programming interfaces, they frequently do not provide appropriate means for data integration at the meta-model level. Thus, overlapping and redundant data from different “integrated” tools may easily become inconsistent and unusable. We propose two design patterns that provide a flexible basis for the integration of different tool data at the meta-model level. To achieve consistency between meta-models, we describe rule-based mechanisms providing generic solutions for managing overlapping and redundant data. The proposed mechanisms are widely used within the Fujaba Tool Suite. We report about our implementation and application experiences .

Model-Driven Engineering of Self-Adaptive Software with EUREMA

The development of self-adaptive software requires the engineering of an adaptation engine that controls the underlying adaptable software by feedback loops. The engine often describes the adaptation by runtime models representing the adaptable software and by activities such as analysis and planning that use these models. To systematically address the interplay between runtime models and adaptation activities, runtime megamodels have been proposed. A runtime megamodel is a specific model capturing runtime models and adaptation activities. In this article, we go one step further and present an executable modeling language for ExecUtable RuntimE MegAmodels (EUREMA) that eases the development of adaptation engines by following a model-driven engineering approach. We provide a domain-specific modeling language and a runtime interpreter for adaptation engines, in particular feedback loops. Megamodels are kept alive at runtime and by interpreting them, they are directly executed to run feedback loops. Additionally, they can be dynamically adjusted to adapt feedback loops. Thus, EUREMA supports development by making feedback loops explicit at a higher level of abstraction and it enables solutions where multiple feedback loops interact or operate on top of each other and self-adaptation co-exists with offline adaptation for evolution.