Chapter Overview

Chapter Overview (18)

This chapter refers to the tool section on our book website. The latter provides an evolving source of information on existing tools enabling flexible process support in process-aware information systems. The book's website covers the tools presented in these chapters as well as others not described here.

Sunday, 28 April 2013 09:03

Chapter 16 - Alaska Simulator Toolset

This chapter introduces Alaska Simulator Toolset (AST), an open source tool suite for systematically exploring and investigating the decision deferral patterns introduced in Chapter 11. By providing integrated support for Late Binding, Late Modeling & Composition, and Iterative Refinement, AST fosters systematic testing of factors that impact the suitability of these approaches. Thus, AST promotes research in the context of loosely-specified processes and hence supports the selection of the right degree of pre-planning. The chapter introduces the concepts underlying AST, presents its architecture, and discusses its use.

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Sunday, 28 April 2013 09:03

Chapter 15 - AristaFlow BPM Suite

In dynamic environments, it becomes necessary to quickly implement new business processes, to allow for ad-hoc deviations from pre-specified processes, and to enable controlled process evolution over time. These fundamental features should be provided by any PAISs without affecting the correctness and soundness of the processes it implements. This chapter presents the AristaFlow BPM Suite---an adaptive PAIS that addresses these challenges. It has originated from the ADEPT research projects. Its overall vision is to provide next generation process management technology for the flexible support of dynamic processes along the process lifecycle. Due to its generic services and application programming interfaces, the AristaFlow BPM Suite can be applied to a variety of applications from different domains.

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For large and complex scenarios, the proper coordination of concurrent executions of user- and data-driven processes is crucial. In this context, object-aware processes provide a high degree of abstraction by enabling two levels of process granularity: object behavior and object interactions. Furthermore, object-aware process management supports data-driven process execution, flexible choice of activity granularities, and integrated access to business processes and business data. This chapter introduces the PHILharmonicFlows framework, which enables object-aware process management in the large scale. In particular, the framework allows for a tight integration of processes, functions, data, and users.

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In practice, many business processes are rather unstructured, knowledge-intensive, and driven by user decisions and data. Typically, these processes can not be straight-jacketed into a set of activities with pre-specified precedence relations; i.e., the primary driver for the progress of the process is not the event related to activity completion, but the availability of certain values for data objects. When implementing such user- and data-driven processes in a PAIS, a tight integration of processes, data and users therefore becomes necessary. This chapter presents case handling as an example of such a process support paradigm. Following this, the fundamental characteristics of user- and data-driven processes are elaborated in detail. In particular, it is shown that object-awareness is required; i.e., a PAIS should manage data by means of object types that comprise object attributes and relations to other object types. Picking up this metaphor, pioneering work targeting at a tight integration of processes and data is evaluated. Besides case handling, this includes Proclets, business artifacts, data-driven process coordination, and product-based workflows.

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This chapter introduces constraint-based approaches to process modeling and execution which enable loosely-specified processes. While pre-specified process models define how things have to be done (i.e., in what order and under what conditions activities shall be executed), constraint-based process models focus on what should be done by describing the activities that may be performed and the constraints prohibiting undesired execution behavior. In this chapter we address the modeling, verification, and execution of constraint-based process models. Moreover, we discuss how these models can be adapted and evolved over time. We further present techniques for assisting end-users during process execution. Finally, constraint-based process models and pre-specified ones are systematically compared and ways to integrate both approaches are discussed.

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In many application domains pre-specifying the entire process model is not possible. While parts of the process model are known at build-time, others are uncertain and can only be specified during run-time. To better deal with such uncertainty, decisions regarding the exact specification of selected parts of the process has to be deferred to run-time. Since decision deferral can be realized in many different ways, this chapter first introduces a taxonomy for it. It then introduces different decision deferral patterns like Late Selection, Late Modeling & Composition, Iterative Refinement, and Ad-hoc Composition. Finally, examples of concrete implementations of the different patterns are presented.

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Sunday, 28 April 2013 08:58

Chapter 10 - Business Process Compliance

In the previous chapters, the proper executability of a pre-specified process model has been based on syntactical constraints, correctness of its data flow schema, and behavioral soundness. However, business processes are also subject to semantic constraints that stem from regulations, laws, and guidelines---also known as compliance rules. Process-aware information systems have to ensure that respective compliance rules are obeyed in order to guarantee semantically correct and error-free execution as well as changes of their business processes. This chapter discusses how such compliance rules can be defined and how they can be ensured in the different phases of the process lifecycle.

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Business processes evolve over time due to changes in their legal, technical, or business context, or as a result of organizational learning. As a consequence, pre-specified process models and their technical implementation in a PAIS need to be adapted accordingly. Moreover, pre-specified process models often have to be changed to cope with design errors, technical problems, or poor model quality. This chapter presents techniques to tackle these challenges and to change implemented business processes at a technical level. First, it deals with process model evolution, i.e., the evolution of pre-specified process models over time to accommodate changes of real-world processes. In this context, techniques are introduced for dealing with already running process instances and their on-the-fly migration to the changed process model, without violating any correctness and soundness properties. Second, this chapter introduces process model refactorings to foster internal process model quality and to ensure maintainability of the PAIS over time.

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Accountability and traceability are important requirements any flexible PAIS needs to fulfill. This chapter describes how execution and change logs can be used to restore the structure and state of a process instance for any given point in time. The information recorded in event and change logs, however, can not only be exploited to ensure accountability and traceability, but used for analysis purposes as well. This chapter discusses different process mining techniques for analyzing flexible business processes. In particular, it presents techniques for the mining of execution logs and change logs. Finally, advanced techniques for analyzing process variant collections in the absence of a change log are introduced.

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