Business process integration and automation are among the most significant factors driving the information technology industry today. In addressing the manifold technology challenges of integration and automation, new standardization efforts aim at improving the interoperability of businesses by moving toward a declarative specification of business processes, that is, one which describes what a business process does and not how it is implemented. At the same time, Model Driven Architecturet focuses on improving the software-engineering methods with which business process solutions are implemented by separating the business or application logic from the underlying platform technology and representing this logic with precise semantic models. In this paper, we present an approach to the model-driven generation of programs in the Business Process Execution Language for Web Services (BPEL4WS), which transforms a graphically represented control-flow model into executable code by using techniques that originated in compiler theory. We discuss the underlying algorithms as well as general questions concerning the representation and analysis of model transformations. We study a declarative representation of transformation rules, where preconditions and postconditions are represented in the Object Constraint Language. By adopting a declarative approach, we pave the way for future automatic consistency checking of transformation rules and bidirectional reconciliation of evolving models.Model Driven Architecture** (MDA**) has been proposed by the Object Management Group (OMG) to enhance the efficiency and quality of software development and to reinforce the use of an enterprise architecture strategy. Models can be specified from different views, such as that of a business analyst or an information technology (IT) architect, and can be represented at different levels of abstraction. MDA separates the business or application logic from the underlying platform technology and represents this logic with precise semantic models. In particular, MDA distinguishes between Ó

Abstract-Regression testing techniques are commonly used to validate the correctness of upgrades. When a regression test fails, testers must understand the erroneous behaviors that caused the failure and identify the fault that originated these erroneous behaviors. In many cases, identifying the causes of a failure is difficult and time consuming. The analysis of regression problems provides interesting opportunities to validation and verification techniques. In fact, by comparing the execution of the base version and the upgraded version of the same program it is possible to automatically deduce information about incorrect behavior of the program.In this paper we present RADAR (Regression Analysis with Diff And Recording), a dynamic analysis technique, which analyzes regression problems and automatically identifies the chain of erroneous events that lead to a failure in C/C++ programs. RADAR exploits information about changes and the availability of multiple versions of the same program to automatically distinguish correct and suspicious events. Empirical experience with industrial and open source cases shows that RADAR can effectively support testers in the investigation of regression problems. Thus, RADAR can drive and simplify the debugging process.

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Seamlessly updating software in running systems has recently gained momentum. Dynamically updating the software of real-time embedded systems, however, still poses numerous challenges: such systems must meet hard deadlines, cope with limited resources, and adhere to high safety standards.This paper presents a solution for updating componentbased cyclic embedded systems without violating real-time constraints. In particular, it investigates how to identify points in time at which updates can be performed and how to transfer the state of a component to a new version of the same component. We also present experimental results to validate the proposed solution.

Real-time controllers handle safety-critical environments such as power grids in a continuous way. Controllers are only updated during the same maintenance periods as the plant they control. As a consequence, old software versions are usually used longer than necessary, which can have a negative impact on performance, reliability, or security. This paper presents a solution for updating component-based controllers at runtime in a non-disruptive way -there is no "bump" in the control cycle. This solution allows for simultaneous updates of real-time components with arbitrarily large states.The solution is validated by demonstrating a large-scale dynamic software update on an embedded controller with a 1 kHz control cycle on RT Linux. As a corollary, we show that an arbitrary number of components can be simultaneously updated in a nondisruptive way.

To guarantee high availability, automation systems must be fault-tolerant. To this end, they must provide redundant solutions for the critical parts of the system. Classical fault tolerance patterns such as standby or N-modular redundancy provide system stability in the case of a fault. Fault tolerance is subsequently degraded or, depending on the number of deployed replicas, often even unavailable until the system has been repaired.We introduce a combination of a component-based framework, redundancy patterns, and a runtime manager, which is able to provide fault tolerance, to detect host failures, and to trigger a reconfiguration of the system at runtime. This combined solution maintains system operation in case a fault occurs and automatically restores fault tolerance. The proposed solution is validated using a case study of an industrial distributed automation system. The validation shows how our solution quickly restores fault tolerance without the need for operator intervention or immediate hardware replacement while limiting the impact on other applications.

Precision and consistency are important prerequisites for class models to conform to their intended domain semantics. Precision can be achieved by augmenting models with design constraints and consistency can be achieved by avoiding contradictory constraints. However, there are different views of what constitutes a contradiction for design constraints. Moreover, state-of-the-art analysis approaches for proving constrained models consistent either scale poorly or require the use of interactive theorem proving. In this paper, we present a heuristic approach for efficiently analyzing constraint specifications built from constraint patterns. This analysis is based on precise notions of consistency for constrained class models and exploits the semantic properties of constraint patterns, thereby enabling syntax-based consistency checking in polynomial-time. We introduce a consistency checker implementing these ideas and we report on case studies in applying our approach to analyze industrial-scale models. These studies show that pattern-based constraint development supports the creation Communicated by Dr. Alessandra Cavarra. M. Wahler ( )

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