Change Support in Process-Aware Information Systems - A Pattern-Based Analysis

In today's dynamic business world the economic success of an enterprise increasingly depends on its ability to react to changes in its environment in a quick and flexible way. Process-aware information systems (PAIS) offer promising perspectives in this respect and are increasingly employed for operationally supporting business processes. To provide effective business process support, flexible PAIS are needed which do not freeze existing business processes, but allow for loosely specified processes, which can be detailed during run-time. In addition, PAIS should enable authorized users to flexibly deviate from the predefined processes if required (e.g., by allowing them to dynamically add, delete, or move process activities) and to evolve business processes over time. At the same time PAIS must ensure consistency and robustness. The emergence of different process support paradigms and the lack of methods for comparing existing change approaches have made it difficult for PAIS engineers to choose the adequate technology. In this paper we suggest a set of changes patterns and change support features to foster the systematic comparison of existing process management technology with respect to process change support. Based on these change patterns and features, we provide a detailed analysis and evaluation of selected systems from both academia and industry. The identified change patterns and change support features facilitate the comparison of change support frameworks, and consequently will support PAIS engineers in selecting the right technology for realizing flexible PAIS. In addition, this work can be used as a reference for implementing more flexible PAIS

Orchestrating the Dynamic Adaptation of Distributed Software with Process Technology

Software systems are becoming increasingly complex to develop, understand, analyze, validate, deploy, configure, manage and maintain. Much of that complexity is related to ensuring adequate quality levels to services provided by software systems after they are deployed in the field, in particular when those systems are built from and operated as a mix of proprietary and non-proprietary components. That translates to increasing costs and difficulties when trying to operate large-scale distributed software ensembles in a way that continuously guarantees satisfactory levels of service. A solution can be to exert some form of dynamic adaptation upon running software systems: dynamic adaptation can be defined as a set of automated and coordinated actions that aim at modifying the structure, behavior and performance of a target software system, at run time and without service interruption, typically in response to the occurrence of some condition(s). To achieve dynamic adaptation upon a given target software system, a set of capabilities, including monitoring, diagnostics, decision, actuation and coordination, must be put in place. This research addresses the automation of decision and coordination in the context of an end-to-end and externalized approach to dynamic adaptation, which allows to address as its targets legacy and component-based systems, as well as new systems developed from scratch. In this approach, adaptation provisions are superimposed by a separate software platform, which operates from the outside of and orthogonally to the target application as a whole; furthermore, a single adaptation possibly spans concerted interventions on a multiplicity of target components. To properly orchestrate those interventions, decentralized process technology is employed for describing, activating and coordinating the work of a cohort of software actuators, towards the intended end-to-end dynamic adaptation. The approach outlined above, has been implemented in a prototype, code-named Workflakes, within the Kinesthetics eXtreme project investigating externalized dynamic adaptation, carried out by the Programming Systems Laboratory of Columbia University, and has been employed in a set of diverse case studies. This dissertation discusses and evaluates the concept of process-based orchestration of dynamic adaptation and the Workflakes prototype on the basis of the results of those case studies

Weaving of Aspects in Business Process Management

Separation of cross-cutting concerns is an important issue in business process management, where Aspect-Oriented Business Process Modeling (AO-BPM) aims to support this separation through a new form of encapsulation technique. Although different researchers have investigated how these models can be designed to support separation of non-retroactive cross-cutting concerns, there is no study that defines the separation of retroactive ones. The lack of a unified definition of the syntax and the operational semantics for these models hinders their enactment in practice as well. As a result, the perceived usefulness and usability of these approaches have not yet been investigated so far. Thus, this article fills this gap by formalizing an AO-BPM language and the semantics that can support enactment of such models. The semantics is validated through the state-space analysis technique, and the feasibility of the implementation is also demonstrated. The perceived usefulness and easy to use of the AO-BPM is evaluated by applying the Technology Acceptance Model during a workshop session. The result shows that participants perceived the approach usable and easy to use

Context-aware workflow management in eHealth applications

Workflows are a technology to structure work in functional, non-overlapping steps. They define not only the order of execution of the steps, and describe whether steps are executed in parallel, they also specify who or what tool has to fulfill which step. Workflows offer the possibility to automate work, to increase the understandability of processes, and they ease the control of process execution. The tools to manage workflows, so called workflow management systems (WfMSs), are traditionally rigid as they separate workflow definition done at build time from workflow execution done at run time. This makes them ill-suited for managing flexible and unstructured workflows. In this thesis, we focus on the support of flexible processes in eHealth, which are affected by more foreseen than unforeseen events. To bridge the gap between rigid WfMSs and flexible workflows, we developed a concept for dynamic and context-aware workflow management called Flexwoman. Although our focus lies on flexible eHealth processes, Flexwoman is a generic approach that can be applied to several different application domains. Flexwoman supports the usage of context information to adapt processes automatically at run time to foreseen events. Processes can also be manually adapted to handle unforeseen events. To achieve this flexibility, context information from different sensors is unified and thus can be analyzed in the same way. The analysis and adaptation of workflows is executed with a rule engine. A rule engine can store, reason about and apply knowledge automatically and efficiently. Rules and application logic are separated, thus, rules can be changed during run time without affecting application logic or process description. Workflows are internally described by Hierarchical Colored Petri nets (HCPNs) and executed by a HCPN execution engine. HCPNs allow for a deterministic execution of workflows and can represent workflows on different levels of detail. In summary, in Flexwoman, significant context changes (events) trigger automated adaptations that replace parts of the workflow by sub workflows, which can in turn be adapted. The adaptations and the rules for context-aware adaptation are saved in the organizational memory for later reuse. Flexwoman’s event based behavior facilitates proactive adaptations instead of only allowing for adaptations while entering or leaving a task. Replacements are not bound to special places defined at build time but each part of the workflow, which has not been executed yet, can be replaced at run time. We implemented and evaluated the concept. The evaluations show i) that all required functionality is available, ii) that the system scales with a growing number of rules, and iii) that the system correctly handles failure situations