Abstract

This paper <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> proposes a workflow intelligence and quality improvement framework maximizing the workflow trace- ability and rediscoverability by analyzing the total sequences of the control-path perspective of a workflow model and by rediscovering their runtime enactment history from the workflow log information. The framework needs two kinds of algorithms - One is for generating the total sequences of the control-paths from a workflow model, and the other is for rediscovering the runtime enactment history of each control-path out of the total sequences from the corresponding workflow's execution logs. Eventually, these rediscovered knowledge and history of a workflow model make up a control-path oriented intelligence of the workflow model, which ought to be an essential ingredient for improving the quality of the workflow model. Based upon the workflow intelligence, it is possible for the workflow model to be gradually refined and finally maximize its quality by repeatedly redesigning, reengineering and/or refining during its whole life-long time period.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.