Stefanie Rinderle

Correctness criteria for dynamic changes in workflow systems: a survey

The capability to dynamically adapt in-progress workflows (WF) is an essential requirement for any workflow management system (WfMS). This fact has been recognized by the WF community for a long time and different approaches in the area of adaptive workflows have been developed so far. This survey systematically classifies these approaches and discusses their strengths and limitations along typical problems related to dynamic WF change. Along this classification we present important criteria for the correct adaptation of running workflows and analyze how actual approaches satisfy them. Furthermore, we provide a detailed comparison of these approaches and sketch important further issues related to dynamic change.

Flexible Support of Team Processes by Adaptive Workflow Systems

Process-oriented support of collaborative work is an important challenge today. At first glance, Workflow Management Systems (WfMS) seem to be very suitable tools for realizing team-work processes. However, such processes have to be frequently adapted, e.g., due to process optimizations or when process goals change. Unfortunately, runtime adaptability still seems to be an unsolvable problem for almost all existing WfMS. Usually, process changes can be accomplished by modifying a corresponding (graphical) workflow (WF) schema. Especially for long-running processes, however, it is extremely important that such changes can be propagated to already running WF instances as well, but without causing inconsistencies and errors. The paper presents a general and comprehensive correctness criterion for ensuring compliance of in-progress WF instances with a modified WF schema. For different kinds of WF schema changes, it is precisely stated, which rules and which information are needed at mininum for satisfying this criterion.

Adaptive process management with ADEPT2

In the ADEPT project we have been working on the design and implementation of next generation process management software. Based on a conceptual framework for dynamic process changes, on novel process support functions, and on advanced implementation concepts, the developed system enables the realization of adaptive, process-aware information systems (PAIS). Basically, process changes can take place at the type as well as the instance level: changes of single process instances may have to be carried out in an ad-hoc manner and must not affect system robustness and consistency. Process type changes, in turn, must be quickly accomplished in order to adapt the PAIS to business process changes. ADEPT2 offers powerful concepts for modeling, analyzing, and verifying process schemes. Particularly, it ensures schema correctness, like the absence of deadlock-causing cycles or erroneous data flows. This, in turn, constitutes an important prerequisite for dynamic process changes as well. ADEPT2 supports both ad-hoc changes of single process instances and the propagation of process type changes to running instances.

Integration and verification of semantic constraints in adaptive process management systems

Adaptivity in process management systems is key to their successful applicability in practice. Approaches have been already developed to ensure system correctness after arbitrary process changes at the syntactical level (e.g., avoiding inconsistencies such as deadlocks or missing input parameters after a process change). However, errors may be still caused at the semantical level (e.g., violation of business rules). Therefore, the integration and verification of domain knowledge will flag a milestone in the development of adaptive 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 domain knowledge on the one hand and are still manageable concerning the effort for maintenance and semantic process verification on the other hand. This can be used to detect semantic conflicts (e.g., drug incompatibilities) when modeling process templates, applying ad hoc changes at process instance level, and propagating process template modifications to already running process instances, even if they have been already individually modified themselves; i.e., we present techniques to ensure semantic correctness for single and concurrent changes which are, in addition, minimal regarding the set of semantic constraints to be checked. Together with further optimizations of the semantic checks based on certain process meta model properties this allows for efficiently verifying processes. Altogether, the framework presented in this paper provides the basis for process management systems which are adaptive and semantic-aware at the same time.

Integrating process learning and process evolution – a semantics based approach

Companies are developing a growing interest in aligning their information systems in a process-oriented way. However, current process-aware information systems (PAIS) fail to meet process flexibility requirements, which reduces the applicability of such systems. To overcome this limitation PAIS should capture the whole process life cycle and all kinds of changes in an integrated way. In this paper we present such a holistic approach providing full process life cycle support by combining the ADEPT framework for dynamic process changes with the concepts and methods provided by case-based reasoning (CBR) technology. This allows expressing the semantics of process changes, their memorization and their reuse to perform similar changes in the future. If the same or similar process instance changes occur frequently, potential process type changes are suggested to the process engineer. The process engineer can then perform a schema evolution and migrate running instances to the new schema version by using the ADEPT framework. Finally, the case–base related to the old schema version is migrated as well.

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.

Mining staff assignment rules from event-based data

Process mining offers methods and techniques for capturing process behaviour from log data of past process executions. Although many promising approaches on mining the control flow have been published, no attempt has been made to mine the staff assignment situation of business processes. In this paper, we introduce the problem of mining staff assignment rules using history data and organisational information (e.g., an organisational model) as input. We show that this task can be considered an inductive learning problem and adapt a decision tree learning approach to derive staff assignment rules. In contrast to rules acquired by traditional techniques (e.g., questionnaires) the thus derived rules are objective and show the staff assignment situation at hand. Therefore, they can help to better understand the process. Moreover, the rules can be used as input for further analysis, e.g., workload balance analysis or delta analysis. This paper presents the current state of our work and points out some challenges for future research.

Evolution of process choreographies in DYCHOR

Process-aware information systems have to be frequently adapted due to business process changes One important challenge not adequately addressed so far concerns the evolution of process choreographies, i.e., the change of interactions between partner processes in a cross-organizational setting If respective modifications are applied in an uncontrolled manner, inconsistencies or errors might occur in the sequel In particular, modifications of private processes performed by a single party may affect the implementation of the private processes of partners as well In this paper we present the DYCHOR (DYnamic CHOReographies) framework which allows process engineers to detect how changes of private processes may affect related public views and – if so – how they can be propagated to the public and private processes of partners In particular, DYCHOR exploits the semantics of the applied changes in order to automatically determine the adaptations necessary for the partner processes Altogether our framework provides an important contribution towards the realization of adaptive, cross-organizational processes.

On Dealing with Structural Conflicts between Process Type and Instance Changes

Adaptive process management systems must be able to support changes of single process instances as well as 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 manner. However, especially for long-running processes, it must be possible to handle the interplay between process type and instance changes as well, but without running into trouble at runtime. This paper presents an extended criterion for correctly propagating process type changes to both, instances which are still running according to their original schema and instances which have been individually modified. In this context, we discuss and categorize structural conflicts potentially occuring between concurrent process changes. We show that our considerations are applicable to different process meta models and present tests for quickly detecting such structural conflicts.

Balancing flexibility and security in adaptive process management systems

Process–aware information systems (PAIS) must provide sufficient flexibility to their users to support a broad spectrum of application scenarios. As a response to this need adaptive process management systems (PMS) have emerged, supporting both ad-hoc deviations from the predefined process schema and the quick adaptation of the PAIS to business process changes. This newly gained runtime flexibility, however, imposes challenging security issues as the PMS becomes more vulnerable to misuse. Process changes must be restricted to authorized users, but without nullifying the advantages of a flexible system by handling authorizations in a too rigid way. This paper discusses requirements relevant in this context and proposes a comprehensive access control (AC) model with special focus on adaptive PMS. On the one hand, our approach allows the compact definition of user dependent access rights restricting process changes to authorized users only. On the other hand, the definition of process type dependent access rights is supported to only allow for those change commands which are applicable within a particular process context. Respective AC mechanisms will be key ingredients in future adaptive PMS.