Despite the popularity of BPEL engines to orchestrate complex and executable processes, there are still only few approaches available to help find the most appropriate engine for individual requirements.
One of the more crucial factors for such a middleware product in industry are the performance characteristics of a BPEL engine.
There exist multiple studies in industry and academia testing the performance of BPEL engines, which differ in focus and method.
We aim to compare the methods used in these approaches and provide guidance for further research in this area.
Based on the related work in the field of performance testing, we created a process engine specific comparison framework, which we used to evaluate and classify nine different approaches that were found using the method of a systematical literature survey.
With the results of the status quo analysis in mind, we derived directions for further research in this area.
Correct and standard compliant serializations of BPMN process models are crucial for model exchange between tools, automatic application of academic verification approaches and executability on BPMN engines. The official standard document does not provide an extensive set of all constraints regarding the correctness of model serializations. This technical reports fills this gap by presenting a categorized list of generic, technology independent constraints stated by the standard. Furthermore it is analyzed which rules are already covered when the standardized XSD-based serialization format is used.
More than five years have passed since the final release of the long-desired OASIS standard of a process language for web service orchestration, the Web Services Business Process Execution Language (BPEL). The aim of this standard is to establish a universally accepted orchestration language that forms a core part of current service-oriented architectures and, because of standardisation, avoids vendor lock-in. High expectations, in academia and practice alike, have been set on it. By now, several fully conformant and highly scalable engines should have arrived in the market. The perception of many however, is that standard conformance in current engines is far from given. It is our aim to shed light on this situation. In this study, we present the tool betsy, a BPEL Engine Test System that allows for a fully-automatic assessment of the standard conformance of a given BPEL engine. We use it to examine the five most important open source BPEL engines available today. Betsy comes with a large set of engineindependent conformance test cases for assessing BPEL standard conformance. This enables us to give a view of the state of the art in BPEL support.
In the post-proceedings of the Workshop "Visibility in Information Spaces and in Geographic Environments" a selection of research papers is presented where the topic of visibility is addressed in different contexts. Visibility governs information selection in geographic environments as well as in information spaces and in cognition. The users of social media navigate in information spaces and at the same time, as embodied agents, they move in geographic environments. Both activities follow a similar type of information economy in which decisions by individuals or groups require a highly selective filtering to avoid information overload. In this context, visibility refers to the fact that in social processes some actors, topics or places are more salient than others. Formal notions of visibility include the centrality measures from social network analysis or the plethora of web page ranking methods. Recently, comparable approaches have been proposed to analyse activities in geographic environments: Place Rank, for instance, describes the social visibility of urban places based on the temporal sequence of tourist visit patterns. The workshop aimed to bring together researchers from AI, Geographic Information Science, Cognitive Science, and other disciplines who are interested in understanding how the different forms of visibility in information spaces and geographic environments relate to one another and how the results from basic research can be used to improve spatial search engines, geo-recommender systems or location-based social networks.
Orchestration languages are of paramount importance for building composite services in service-oriented architectures. Pattern-based analysis is a method that allows to determine the expressiveness of existing process languages and serves as a means of comparison between different languages. The aim of this study is the analysis and comparison of important languages for building Web Services-based orchestrations, as well as the improvement of the method of pattern-based analysis. The predominant orchestration language today is the Web Services Business Process Execution Language (WS-BPEL) 2.0. This language is a standard that has been implemented by several companies and projects, such as the OpenESB BPEL Service Engine. An additional language is Windows Workflow 4 that is shipped by Microsoft as part of the .NET framework. There are various aspects, represented by pattern catalogs, for which existing languages can be analyzed. This study suggests a methodology for ordering existing pattern catalogs according to their importance for a selected problem domain which is Business-to-Business Integration. It furthermore presents an extensive evaluation of the languages at hand and assesses the degree of support they provide for several of the most important pattern catalogs. These catalogs are the workflow control-flow patterns, the service interaction patterns, the change patterns and the time patterns.
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.
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.