Since their invention as lightweight integration technology about a decade ago, Web Services have matured significantly. Today, major middleware solution vendors as well as industry communities like RosettaNet are propagating Web services even for exchanging business-critical data and implementing inter-organizational business processes. Core enablers for using Web services in this domain are stateful interactions using the Web Services Business Process Execution Language (WS-BPEL) as well as advanced communication features like security and reliability using the WS-Security and WS-ReliableMessaging standard specifications. However, advanced communication features come at the price of complexity which challenges interoperability across different Web services stack implementations. Interoperability, in turn, is a predominant requirement for an integration technology such as Web services, in particular if inter-organizational business processes are supposed to be implemented on top of that technology. This paper approaches the problem of testing the interoperability of the so-called WS-* standards, advanced Web services communication features that are typically defined as SOAP extensions and configured using WS-Policy. Being essential to business process integration, WS-Security and WS-ReliableMessaging are selected as representatives of this group and the two major Java-based Web services stack implementations Metro and Axis2 are tested for interoperability. We operationalize the notion of interoperability for testing WS-* standards, suppose an approach for deriving test cases from WS-* specifications as well as a method for performing the test cases, and we provide a comprehensive interoperability review of the two selected Web services stack implementations.
Im Servicegeschäft werden Eventkorrelationssysteme verwendet, um bevorstehende Systemzustände vorherzusagen und damit Anlagenausfälle zu vermeiden. Aus strategischer Sicht kann dies zu höherer Anlagenverfügbarkeit und bessere Planbarkeit beitragen. Unternehmen, die von diesem Wettbewerbsvorteil profitieren wollen, begegnen dabei häufig zwei grundlegenden Problemen: die Komplexität im Service steigt mit der Anzahl der Korrelationen. Gleichzeitig geht die Kostentransparenz für den Gesamtprozess verloren. Die vorliegende Arbeit zeigt, warum diese beiden Probleme entstehen und wie sie weitgehend vermieden werden können.
Current software model checkers quickly reach their limit when being applied to verifying pointer safety properties in source code that includes function pointers and inlined assembly. This paper introduces an alternative technique for checking pointer safety violations, called Symbolic Object Code Analysis (SOCA), which is based on bounded symbolic execution, incorporates path-sensitive slicing, and employs the SMT solver Yices as its execution and verification engine. Extensive experimental results of a prototypic SOCA Verifier, using the Verisec suite and almost 10,000 Linux device driver functions as benchmarks, show that SOCA performs competitively to current source-code model checkers and that it also scales well when applied to real operating systems code and pointer safety issues. SOCA effectively explores semantic niches of software that current software verifiers do not reach.
By using the remote functions of a modern IT service management system infrastructure, it is possible to analyze huge amounts of logfile data from complex technical equipment. This enables a service provider to predict failures of connected equipment before they happen. The problem most providers face in this context is finding a needle in a haystack - the obtained amount of data turns out to be too large to be analyzed manually. This report describes a process to find suitable predictive patterns in log files for the detection of upcoming critical situations. The identification process may serve as a hands-on guide. It describes how to connect statistical means, data mining algorithms and expert domain knowledge in the domain of service management. The process was developed in a research project which is currently being carried out within the Siemens Healthcare service organization. The project deals with two main aspects: First, the identification of predictive patterns in existing service data and second, the architecture of an autonomous agent which is able to correlate such patterns. This paper summarizes the results of the first project challenge. The identification process was tested successfully in a proof of concept for several Siemens Healthcare products.
Ever fiercer competition has forced enterprises not only to optimize their own operations but also to cooperate with their suppliers and customers along their supply chains. Thus, competition today usually takes place between supply chains and not between individual enterprises. Business-To-Business integration (B2Bi) is a major task of supply chain management (SCM), and although it already has been researched for years, B2Bi is still an area of active research with a plethora of research questions and according approaches. Hence, management of B2Bi projects necessitates the identification of relevant requirements which is a far from trivial task. This paper identifies a core set of B2Bi challenges and deduces a comprehensive set of B2Bi requirements that are particularly useful for tackling the challenges identified. The derivation of B2Bi requirements follows an inductive approach that is based on the analysis of integration standards, reference architectures and related literature. In order to operationalize the B2Bi requirements for further analysis and concrete B2Bi projects, the requirements are classified according to the abstraction layers of a B2Bi schema. Thus, this report not only offers a requirements check list for B2Bi projects but also helps in deciding when to address which requirements during the course of a B2Bi project.
The KI ´09 workshop on Complex Cognition was a joint venture of the Cognition group of the Special Interest Group Artificial Intelligence of the German Computer Science Society (Gesellschaft für Informatik) and the German Cognitive Science Association. Dealing with complexity has become one of the great challenges for modern information societies. To reason and decide, plan and act in complex domains is no longer limited to highly specialized professionals in restricted areas such as medical diagnosis, controlling technical processes, or serious game playing. Complexity has reached everyday life and affects people in such mundane activities as buying a train ticket, investing money, or connecting a home desktop to the internet. Research in cognitive AI can contribute to supporting people navigating through the jungle of everyday reasoning, decision making, planning and acting by providing intelligent support technology. Lessons learned from expert systems research of the nineteen-eighties show that the aim should not be to provide for fully automated systems which can solve specialized tasks autonomously but instead to develop interactive assistant systems where user and system work together by taking advantage of the respective strengths of human and machine. To accomplish a smooth collaboration between humans and intelligent systems, basic research in cognition is a necessary precondition. Insights into cognitive structures and processes underlying successful human reasoning and planning can provide suggestions for algorithm design. Even more important, insights into restrictions and typical errors and misconceptions of the cognitive systems provide information about those parts of a complex task from which the human should be relieved. For successful human-computer interaction in complex domains it has, furthermore, to be decided which information should be presented when, in what way, to the user. We strongly believe that symbolic approaches of AI and psychological research of higher cognition are at the core of success for the endeavor to create intelligent assistant system for complex domains. While insight into the neurological processes of the brain and into the realization of basic processes of perception, attention and senso-motoric coordination are important for the basic understanding of the principles of human intelligence, these processes have a much too fine granularity for the design and realization of interactive systems which must communicate with the user on knowledge level. If human system users are not to be incapacitated by a system, system decisions must be transparent for the user and the system must be able to provide explanations for the reasons of its proposals and recommendations. Therefore, even when some of the underlying algorithms are based on statistical or neuronal approaches, the top-level of such systems must be symbolical and rule-based. The papers presented at this workshop on complex cognition give an inspiring and promising overview of current work in the field which can provide first building stones for our endeavor to create knowledge level intelligent assistant systems for complex domains. The topics cover modelling basic cognitive processes, interfacing subsymbolic and symbolic representations, dealing with continuous time, Bayesian identification of problem solving strategies, linguistically inspired methods for assessing complex cognitive processes and complex domains such as recognition of sketches, predicting changes in stocks, spatial information processing, and coping with critical situations.
Inductive programming is concerned with the automated construction of declarative, often functional, recursive programs from incomplete specifications such as input/output examples. The inferred program must be correct with respect to the provided examples in a generalising sense: it should be neither equivalent to them, nor inconsistent. Inductive programming algorithms are guided explicitly or implicitly by a language bias (the class of programs that can be induced) and a search bias (determining which generalised program is constructed first). Induction strategies are either generate-and-test or example-driven. In generate-and-test approaches, hypotheses about candidate programs are generated independently from the given specifications. Program candidates are tested against the given specification and one or more of the best evaluated candidates are developed further. In analytical approaches, candidate programs are constructed in an example-driven way. While generate-and-test approaches can -- in principle -- construct any kind of program, analytical approaches have a more limited scope. On the other hand, efficiency of induction is much higher in analytical approaches. Inductive programming is still mainly a topic of basic research, exploring how the intellectual ability of humans to infer generalised recursive procedures from incomplete evidence can be captured in the form of synthesis methods. Intended applications are mainly in the domain of programming assistance -- either to relieve professional programmers from routine tasks or to enable non-programmers to some limited form of end-user programming. Furthermore, in the future, inductive programming techniques might be applied to further areas such as supporting the inference of lemmata in theorem proving or learning grammar rules. Inductive automated program construction has been originally addressed by researchers in artificial intelligence and machine learning. During the last years, some work on exploiting induction techniques has been started also in the functional programming community. Therefore, the third workshop on |Approaches and Applications of Inductive Programming| took place for the first time in conjunction with the ACM SIGPLAN International Conference on Functional Programming (ICFP 2009). The first and second workshop were associated with the International Conference on Machine Learning (ICML 2005) and the European Conference on Machine Learning (ECML 2007). AAIP´09 aimed to bring together researchers from the functional programming and the artificial intelligence communities, working in the field of inductive functional programming, and advance fruitful interactions between these communities with respect to programming techniques for inductive programming algorithms, the identification of challenge problems and potential applications. For everybody interested in inductive programming we recommend to visit the website: www.inductive-programming.org.
Business-To-Business Integration (B2Bi) is a key mechanism for enterprises to gain competitive advantage. However, developing B2Bi applications is far from trivial. Inter alia, agreement among integration partners about the business documents and the control flow of business document exchanges as well as applying suitable communication technologies for overcoming heterogeneous IT landscapes are major challenges. At the same time, choreography languages such as ebXML BPSS (ebBP), orchestration languages such as WS-BPEL and Web Services are promising to provide the foundations for seamless interactions among business partners. Automatically translating choreography agreements of integration partners into partner-specific orchestrations is an obvious idea for ensuring conformance of orchestration models to choreography models. Moreover, the application of such model-driven development methods facilitates productivity and cost-effectiveness whereas applying a service oriented architecture (SOA) based on WS-BPEL and Web Services leverages standardization and decoupling. By now, the realization of QoS attributes has not yet received the necessary attention that makes such approaches suitable for B2Bi. In this report, we describe a proof-of-concept implementation of the translation of ebBP choreographies into WS-BPEL orchestrations that respects B2Bi-relevant QoS attributes.
Offering services anonymously on the Internet using so-called location-hidden services requires complex protocols with many different nodes involved. These properties result in performance problems, e.g. a simple website request taking tens of seconds. This work describes a setup to measure the performance of hidden services using the worldwide Tor network. It analyzes the results and proposes changes to the protocol to improve the performance without losing anonymity.
Recently, service orientation has strongly influenced the way enterprise applications are built. Service ecosystems, which provide means to trade services between companies like goods, are an evaluation of service orientation. To allow service ordering, discovering, selection, and consumption, a common way to describe services is a necessity. This paper discusses existing approaches to describe certain service aspects. Finally, a Service Description Framework for service ecosystems is proposed and exemplified.