Year

2015

Season

Spring

Paper Type

Master's Thesis

College

College of Computing, Engineering & Construction

Degree Name

Master of Science in Computer and Information Sciences (MS)

Department

Computing

NACO controlled Corporate Body

University of North Florida. School of Computing

First Advisor

Dr. Karthikeyan Umapathy

Second Advisor

Dr. Sherif Elfayoumy

Third Advisor

Dr. Zornitza Genova Prodanoff

Department Chair

Dr. Asai Asaithambi

College Dean

Dr. Mark A. Tumeo

Abstract

In a typical workflow process, exceptions are the norm. Exceptions are defined as deviations from the normal sequence of activities and events. Exceptions can be divided into two broad categories: known exceptions (i.e., expected and predefined deviations) and unknown exceptions (i.e., unexpected and undefined deviations). Business Process Execution Language (BPEL) has become the de facto standard for executing business workflows with the use of web services. BPEL includes exception handling methods that are sufficient for known exception scenarios. Depending on the exception and the specifics of the exception handling tools, processes may either halt or move to completion. Instances of processes that are halted or left incomplete due to unhandled exceptions affect the performance of the workflow process, as they increase resource utilization and process completion time. However, designing efficient process handlers to avoid the issue of unhandled exceptions is not a simple task. This thesis provides a tool that handles unknown exceptions using provisions for exception handling with the involvement of human activities by using the BPEL4PEOPLE specification. BPEL4PEOPLE, an extension of BPEL, offers the ability to specify human activities within BPEL processes. The approach considered in this thesis involves humans in exception handling tools by providing an alternate sub process within a given business process. A prototype application has been developed implementing the tool that handles unknown exceptions. The prototype application monitors the progress of an automated workflow process and permits human involvement to reroute the course of a workflow process when an unknown exception occurs. The utility of the prototype and the tool using the Scenario Walkthrough and Inspection Methods (SWIMs) are demonstrated. We demonstrate the utility of the tool through loan application process scenarios, and offer a walkthrough of the system by using examples of instances with examples of known and unknown exceptions, as well as a claims analysis of process instances results.

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