Dataflow Analysis and Workflow Design in Business Process Management

Workflow technology has become a standard solution for managing increasingly complex business processes. Successful business process management depends on effective workflow modeling, which has been limited mainly to modeling the control and coordination of activities, i.e. the control flow perspect...

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Main Author: Sun, Xiaoyun
Other Authors: Zhao, J. Leon
Language:EN
Published: The University of Arizona. 2007
Subjects:
Online Access:http://hdl.handle.net/10150/194901
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spelling ndltd-arizona.edu-oai-arizona.openrepository.com-10150-1949012015-10-23T04:41:45Z Dataflow Analysis and Workflow Design in Business Process Management Sun, Xiaoyun Zhao, J. Leon Zhao, J. Leon Nunamaker, Jr., Jay F. Zeng, Daniel Fricke, Martin workflow modeling dataflow specification dataflow anomalies dataflow verification dependency analysis workflow design Workflow technology has become a standard solution for managing increasingly complex business processes. Successful business process management depends on effective workflow modeling, which has been limited mainly to modeling the control and coordination of activities, i.e. the control flow perspective. However, given a workflow specification that is flawless from the control flow perspective, errors can still occur due to incorrect dataflow specification, which is referred to as dataflow anomalies.Currently, there are no sufficient formalisms for discovering and preventing dataflow anomalies in a workflow specification. Therefore, the goal of this dissertation is to develop formal methods for automatically detecting dataflow anomalies from a given workflow model and a rigorous approach for workflow design, which can help avoid dataflow anomalies during the design stage.In this dissertation, we first propose a formal approach for dataflow verification, which can detect dataflow anomalies such as missing data, redundant data, and potential data conflicts. In addition, we propose to use the dataflow matrix, a two-dimension table showing the operations each activity has on each data item, as a way to specify dataflow in workflows. We believe that our dataflow verification framework has added more analytical rigor to business process management by enabling systematic elimination of dataflow errors.We then propose a formal dependency-analysis-based approach for workflow design. A new concept called "activity relations" and a matrix-based analytical procedure are developed to enable the derivation of workflow models in a precise and rigorous manner. Moreover, we decouple the correctness issue from the efficiency issue as a way to reduce the complexity of workflow design and apply the concept of inline blocks to further simplify the procedure. These novel techniques make it easier to handle complex and unstructured workflow models, including overlapping patterns.In addition to proving the core theorems underlying the formal approaches and illustrating the validity of our approaches by applying them to real world cases, we provide detailed algorithms and system architectures as a roadmap for the implementation of dataflow verification and workflow design procedures. 2007 text Electronic Dissertation http://hdl.handle.net/10150/194901 659747192 2084 EN Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. The University of Arizona.
collection NDLTD
language EN
sources NDLTD
topic workflow modeling
dataflow specification
dataflow anomalies
dataflow verification
dependency analysis
workflow design
spellingShingle workflow modeling
dataflow specification
dataflow anomalies
dataflow verification
dependency analysis
workflow design
Sun, Xiaoyun
Dataflow Analysis and Workflow Design in Business Process Management
description Workflow technology has become a standard solution for managing increasingly complex business processes. Successful business process management depends on effective workflow modeling, which has been limited mainly to modeling the control and coordination of activities, i.e. the control flow perspective. However, given a workflow specification that is flawless from the control flow perspective, errors can still occur due to incorrect dataflow specification, which is referred to as dataflow anomalies.Currently, there are no sufficient formalisms for discovering and preventing dataflow anomalies in a workflow specification. Therefore, the goal of this dissertation is to develop formal methods for automatically detecting dataflow anomalies from a given workflow model and a rigorous approach for workflow design, which can help avoid dataflow anomalies during the design stage.In this dissertation, we first propose a formal approach for dataflow verification, which can detect dataflow anomalies such as missing data, redundant data, and potential data conflicts. In addition, we propose to use the dataflow matrix, a two-dimension table showing the operations each activity has on each data item, as a way to specify dataflow in workflows. We believe that our dataflow verification framework has added more analytical rigor to business process management by enabling systematic elimination of dataflow errors.We then propose a formal dependency-analysis-based approach for workflow design. A new concept called "activity relations" and a matrix-based analytical procedure are developed to enable the derivation of workflow models in a precise and rigorous manner. Moreover, we decouple the correctness issue from the efficiency issue as a way to reduce the complexity of workflow design and apply the concept of inline blocks to further simplify the procedure. These novel techniques make it easier to handle complex and unstructured workflow models, including overlapping patterns.In addition to proving the core theorems underlying the formal approaches and illustrating the validity of our approaches by applying them to real world cases, we provide detailed algorithms and system architectures as a roadmap for the implementation of dataflow verification and workflow design procedures.
author2 Zhao, J. Leon
author_facet Zhao, J. Leon
Sun, Xiaoyun
author Sun, Xiaoyun
author_sort Sun, Xiaoyun
title Dataflow Analysis and Workflow Design in Business Process Management
title_short Dataflow Analysis and Workflow Design in Business Process Management
title_full Dataflow Analysis and Workflow Design in Business Process Management
title_fullStr Dataflow Analysis and Workflow Design in Business Process Management
title_full_unstemmed Dataflow Analysis and Workflow Design in Business Process Management
title_sort dataflow analysis and workflow design in business process management
publisher The University of Arizona.
publishDate 2007
url http://hdl.handle.net/10150/194901
work_keys_str_mv AT sunxiaoyun dataflowanalysisandworkflowdesigninbusinessprocessmanagement
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