Refactoring Process Models in Large Process Repositories.

With the increasing adoption of process-aware information systems (PAIS), large process model repositories have emerged. Over time respective models have to be re-aligned to the real-world business processes through customization or adaptation. This bears the risk that model redundancies are introduced and complexity is increased. If no continuous investment is made in keeping models simple, changes are becoming increasingly costly and error-prone. Though refactoring techniques are widely used in software engineering to address related problems, this does not yet constitute state-of-the art in business process management. Process designers either have to refactor process models by hand or cannot apply respective techniques at all. This paper proposes a set of behaviour-preserving techniques for refactoring large process repositories. This enables process designers to eectively deal with model complexity by making process models better understandable and easier to maintain

Change Mining in Adaptive Process Management Systems

The wide-spread adoption of process-aware information systems has resulted in a bulk of computerized information about real-world processes. This data can be utilized for process performance analysis as well as for process improvement. In this context process mining offers promising perspectives. So far, existing mining techniques have been applied to operational processes, i.e., knowledge is extracted from execution logs (process discovery), or execution logs are compared with some a-priori process model (conformance checking). However, execution logs only constitute one kind of data gathered during process enactment. In particular, adaptive processes provide additional information about process changes (e.g., ad-hoc changes of single process instances) which can be used to enable organizational learning. In this paper we present an approach for mining change logs in adaptive process management systems. The change process discovered through process mining provides an aggregated overview of all changes that happened so far. This, in turn, can serve as basis for all kinds of process improvement actions, e.g., it may trigger process redesign or better control mechanisms

AIOCJ: A Choreographic Framework for Safe Adaptive Distributed Applications

We present AIOCJ, a framework for programming distributed adaptive applications. Applications are programmed using AIOC, a choreographic language suited for expressing patterns of interaction from a global point of view. AIOC allows the programmer to specify which parts of the application can be adapted. Adaptation takes place at runtime by means of rules, which can change during the execution to tackle possibly unforeseen adaptation needs. AIOCJ relies on a solid theory that ensures applications to be deadlock-free by construction also after adaptation. We describe the architecture of AIOCJ, the design of the AIOC language, and an empirical validation of the framework.Comment: Technical Repor

How Advanced Change Patterns Impact the Process of Process Modeling

Process model quality has been an area of considerable research efforts. In this context, correctness-by-construction as enabled by change patterns provides promising perspectives. While the process of process modeling (PPM) based on change primitives has been thoroughly investigated, only little is known about the PPM based on change patterns. In particular, it is unclear what set of change patterns should be provided and how the available change pattern set impacts the PPM. To obtain a better understanding of the latter as well as the (subjective) perceptions of process modelers, the arising challenges, and the pros and cons of different change pattern sets we conduct a controlled experiment. Our results indicate that process modelers face similar challenges irrespective of the used change pattern set (core pattern set versus extended pattern set, which adds two advanced change patterns to the core patterns set). An extended change pattern set, however, is perceived as more difficult to use, yielding a higher mental effort. Moreover, our results indicate that more advanced patterns were only used to a limited extent and frequently applied incorrectly, thus, lowering the potential benefits of an extended pattern set

Glycotope structures and intramolecular affinity factors of plant lectins for Tn/T antigens

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Comprehensive Life Cycle Support for Access Rules in Information Systems: The CEOSIS Project

The definition and management of access rules (e.g., to control access to business documents and business functions) is a fundamental task in any enterprise information system (EIS). While there exists considerable work on how to specify and represent access rules, only little research has been spent on access rule changes. Examples include the evolution of organizational models with need for subsequent adaptation of related access rules as well as direct access rule modifications (e.g., to state a previously defined rule more precisely). This paper presents a comprehensive change framework for the controlled evolution of role-based access rules in EIS. First, we consider changes of organizational models and elaborate how they affect existing access rules. Second, we define change operations which enable direct adaptations of access rules. In the latter context, we define the formal semantics of access rule changes based on operator trees. Particularly, this enables their unambiguous application; i.e., we can precisely determine which effects are caused by respective rule changes. This is important, for example, to be able to efficiently and correctly adapt user worklists in process-aware information systems. Altogether this paper contributes to comprehensive life cycle support for access rules in (adaptive) EIS

Semantic Correctness in Adaptive Process Management Systems

Abstract. Adaptivity in Process Management Systems (PMS) is key to their successful applicability in pratice. Approaches have already been de-veloped to ensure the system correctness after arbitrary process changes at the syntactical level. However, still errors may be caused at the se-mantical level. Therefore, the integration of application knowledge will flag a milestone in the development of process management technology. In this paper, we introduce a framework for defining semantic constraints over processes in such a way that they can express real-world applica-tion knowledge. On the other hand, these constraints are still manageable concerning the effort for maintenance and semantic process verification. This can be used, for example, to detect semantic conflicts when ap-plying process changes (e.g., drug incompatibilities). In order to enable the PMS to deal with such semantic conflicts we also introduce a notion of semantic correctness and discuss how to (efficiently) verify semantic correctness in the context of process changes

Resilience Analysis of Service Oriented Collaboration Process Management systems

Collaborative business process management allows for the automated coordination of processes involving human and computer actors. In modern economies it is increasingly needed for this coordination to be not only within organizations but also to cross organizational boundaries. The dependence on the performance of other organizations should however be limited, and the control over the own processes is required from a competitiveness perspective. The main objective of this work is to propose an evaluation model for measuring a resilience of a Service Oriented Architecture (SOA) collaborative process management system. In this paper, we have proposed resilience analysis perspectives of SOA collaborative process systems, i.e. overall system perspective, individual process model perspective, individual process instance perspective, service perspective, and resource perspective. A collaborative incident and maintenance notification process system is reviewed for illustrating our resilience analysis. This research contributes to extend SOA collaborative business process management systems with resilience support, not only looking at quantification and identification of resilience factors, but also considering ways of improving the resilience of SOA collaborative process systems through measures at design and run-time

Disjoint and Overlapping Process Changes: Challenges, Solutions, Applications

Adaptive process–aware information systems must be able to support ad–hoc changes of single process instances as well as schema modifications at the process type level and their propagation to a collection of related process instances. So far these two kinds of (dynamic) process changes have been mainly considered in an isolated fashion. Especially for long-running processes, however, it must be possible to adequately handle the interplay between type and instance changes as well. One challenge in this context is to determine whether concurrent process type and process instance changes have the same or overlapping effects on the original process schema or not. Information about the degree of overlap is needed, for example, to determine whether and – if yes – how a process type change can be propagated to individually modified process instances as well. This paper provides a formal framework for dealing with overlapping and disjoint process changes and presents adequate migration strategies depending on the particular degree of overlap. In order to obtain a canonical representation of changes an algorithm is introduced which purges change logs from noisy information. Finally, a powerful proof-of-concept prototype exists

Towards a Framework for the Agile Mining of Business Processes

In order to support business processes effectively, their implementation by a process management systems (PMS) must be as close to the real world's processes as possible. Generally, it is not suffcient to analyze and model a business process only once, and then to handle respective business cases according to the defined model for a long period of time. Instead, process implementations must be quickly adaptable to changing needs. A PMS should enable process instance changes and provide facilities for analyzing these instance-specific changes in order to derive optimized process models. In this paper we introduce a framework for the agile mining of business processes which supports the whole process life cycle in an integrated way. Our framework is based on process mining techniques, adaptive process management, and conversational case-based reasoning. On the one hand, it allows annotating execution and change logs with semantical information to gather information about the reasons for ad-hoc deviations, which can then be analyzed by the process engineer (with support from the PMS). On the other hand, it enables the process engineer to adapt process models based on the outcome of these analyses and to migrate related process instances to the new model