Basil Becker

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.

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.

Towards Practical Runtime Verification and Validation of Self-Adaptive Software Systems

Software validation and verification (VV and (ii) present a proposal for including V&V operations explicitly in feedback loops for ensuring the achievement of software self-adaptation goals. Both of these contributions provide valuable starting points for V&V researchers to help advance this field.

Making control loops explicit when architecting self-adaptive systems

Many self-adaptive systems include control loops between the core system and specific control elements which realize the self-adaptation capabilities. This is also true albeit at a higher level of abstraction for decentralized architectures. However, the available techniques to describe the software architecture of such systems do not support to make the control loops explicit. Therefore, architecting self-adaptive systems and their self-adaptation logic is today not well supported. In this paper, we present a UML profile for control loops that extends UML modeling concepts such that control loops become first class elements of the architecture. This enables that the architecture reflects control loops as crucial elements of the software architecture of these systems. Furthermore, it supports to design control loops as well as the interplay of multiple control loops at the architectural level. In addition, warning signals and related analysis activities are presented that can be used to analyze whether a given architectural UML model using the profile includes potentially problematic occurrences of control loops.

Incremental model synchronization for efficient run-time monitoring

The model-driven engineering community has developed expressive model transformation techniques based on metamodels, which ease the specification of translations between different model types. Thus, it is attractive to also apply these techniques for autonomic and self-adaptive systems at run-time to enable a comprehensive monitoring of their architectures while reducing development efforts. This requires special solutions for model transformation techniques as they are applied at run-time instead of their traditional usage at development time. In this paper we present an approach to ease the development of architectural monitoring based on incremental model synchronization with triple graph grammars. We show that the provided incremental synchronization between a running system and models for different self-management capabilities provides a significantly better compromise between performance and development costs than manually developed solutions.

Model-driven architectural monitoring and adaptation for autonomic systems

Architectural monitoring and adaptation allows self-management capabilities of autonomic systems to realize more powerful adaptation steps, which observe and adjust not only parameters but also the software architecture. However, monitoring as well as adaptation of the architecture of a running system in addition to the parameters are considerably more complex and only rather limited and costly solutions are available today. In this paper we propose a model-driven approach to ease the development of architectural monitoring and adaptation for autonomic systems. Using meta models and model transformation techniques, we were able to realize an incremental synchronization between the run-time system and models for different self-management activities. The synchronization might be triggered when needed and therefore the activities can operate concurrently.

Model-Based extension of AUTOSAR for architectural online reconfiguration

In the last few years innovations in the automotive domain have been realized by software, leading to a dramatically increased complexity of such systems. Additionally, automotive systems have to be flexible and robust, e.g., to be able to deal with failures of sensors, actuators or other constituents of an automotive system. One possibility to achieve robustness and flexibility in automotive systems is the usage of reconfiguration capabilities. However, adding such capabilities introduces an even higher degree of complexity. To avoid this drawback we propose to integrate reconfiguration capabilities into AUTOSAR, an existing framework supporting the management of such a complex system at the architectural level. Elaborated and expensive tools and toolchains assist during the development of automotive systems. Hence, we present how our reconfiguration solution has been seamlessly integrated into such a toolchain.

Modeling of correct self-adaptive systems: a graph transformation system based approach

Software is always embedded in a social and technical context which change over time and therefore also the software has to be adjusted over time to preserve its value. Self-adaptive systems provide a vision how the systems can become capable of doing a large fraction of the required adaptations autonomously. In this paper we first discuss what is required to model correct self-adaptive systems. We then present the formal model of graph transformation systems which serves most of the identified needs. Based on this findings we outline how UML class and object diagrams as well as extensions for the modeling of behavior based upon graph transformation systems can be employed to model correct self-adaptive system. An application example is used to present how the approach can be employed to model self-adaptive systems at a high level of abstraction and means to ensure its correctness are discussed.

Iterative development of consistency-preserving rule-based refactorings

A model refactoring does not only need to ensure behavior preservation. First of all, it needs to ensure that specific well-formedness constraints of the modeling language under consideration are preserved (consistency preservation). The consistency of model refactorings can be ensured by runtime checks. However, this means that not the developer of the refactorings but the user is confronted with the problem.

On Safe Service-Oriented Real-Time Coordination for Autonomous Vehicles

The performance of autonomous vehicles could be drastically improved if ad-hoc networking and suitable real-time coordination is employed to optimize and improve the joint behavior of multiple autonomous units. However, due to ad-hoc connections and the real-time interaction the correctness and safety of such coordinated autonomous units is very hard to ensure. In this paper we present how service- oriented real-time coordination can be employed to achieve this goal. Based on the proper real-time coordination between two or more vehicles captured by a service contract, we focus on structural changes and the instantiation and termination of service contracts which is a crucial prerequisite for a safe system operation. We present how the structural changes and the service contract creation/deletion can be modeled by a well-defined UML subset consisting of class and object diagrams with collaborations as well as well-defined behavioral rules can be verified taking the dynamic structural changes due to the ad-hoc networking as well as the real-time coordination into account. The new verification technique is outlined and the application of the technique for an application example is presented.