Monitoring and analysis of Workflow applications: a domain-specific language approach

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Autor(es)
Oscar González

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Libro impreso ISBN 9789586955959 $ 72.100 Cantidad:

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Impreso

Estado de la publicación:

Activo

Año de edición:

2011

ISBN-13:

Páginas:

304

Tamaño(cm):

17 x 24

Peso (kg):

0.5200 kg

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Descripción

The increased focus of companies on improving their operational efficiency has raised a demand for advanced systems to support the continuous monitoring and measurement of business activities. These business activities are typically automated into workflow applications. The monitoring and measurement solutions aim at giving organizations the opportunity to focus on process improvement by detecting problematic properties during the execution of workf1ow applications. The focus of this research is to raise the level of abstraction for workflow developers for monitoring and measuring workflow applications.

Colaboradores

Oscar González

Tabla de contenido

Acknow ledgements
Abstract
Resumen Samenvatting

I. Problem Statement and Background

1. Introduction
1.1. Research Context

1.2. Problem Statement
1.2.1. A Trouble Ticket Workflow Scenario
1.2.2. The Need for Higher-Level Mechanisms
1.2.3. An Overview of the Problem

1.3. Research and Assessment Goals
1.4. Approach
1.5. Contributions
1.6. Outline of the Dissertation

2. Background: Workflow Monitoring and Analysis

2.1. Workflow Management Systems
2.1.1. Perspectives on Workflow Application
2.1.2. Process Models Specifications
2.1.3. Workflow Implementation and Enactment
2.1.4. Workflow M&A

2.2. M&A of Workflow Applications
2.2.1. Workflow M&A Taxonomy
2.2.2. Workflow M&A Views
2.2.3. Workflow M&A Dimensions
2.2.4. Workflow M&A Technologies

2.3. Summary

II. Specifying M&A Concerns in Workflow Applications

3. Rationale and Background

3.1. Domain-Specific Languages (DSL)
3.1.1. Development Process
3.1.2. Design Principles

3.2. Requirements for the MonitA DSL
3.2.1. Monitoring and Analysis Desiderata.
3.2.2. MonitA DSL Properties

3.3. Design Rationale of the MonitA DSL
3.3.1. Object Constraint Language (OCL)
3.3.2. Aspect-Oriented Programming (AOP)

3.4. Summary

4. MonitA: The M&A Language

4.1. Monitoring and Analysis Specification
4.1.1. Data Types Specification
4.1.2. Workflow Data Specification
4.1.3. M&A Concerns Specification

4.2. Measurement Data Segment
4.2.1. Measurement Variable Declaration
4.2.2. Measurement Variables Initialization
4.2.3. Navigation of Measurement Information

4.3. Monitoring Events Segment
4.3.1. Workflow Events Monitoring
4.3.2. Analysis Functions Invocation

4.3.3. Execution Context Passing

4.4. Analysis Functions Segment
4.4.1. Measurement Actions
4.4.2. Control Actions

4.5. Discussion
4.6. Summary

5. Evaluation of the MonitA Language

5.1. Evaluation of Design Principles
5.1.1. Representation
5.1.2. Absorption
5.1.3. Standardization
5.1.4. Abstraction
5.1.5. Compression
5.1.6. Generalization
5.1.7. Optimization.

5.2. Evaluation of Expressiveness and Learnability
5.2.1. Basic Study
5.2.2. Results

5.3. Data Modeling Characteristics
5.3.1. Relation to Workflow Data Patterns

5.4. Summary

III. Implementing M&A Concerns Using Generative Approaches

6. Rationale and Background

6.1. Requirements for the MonitA Implementation Strategy
6.2. Design Rationale for the MonitA Implementation Strategy

6.3. Model-Driven Engineering
6.3.1. Metamodels, Models, and Transformation
6.3.2. MDE and DSL
6.3.3. Traceability Models

6.4. Aspect-Oriented Software Development
6.4.1. Aspect-Oriented Programming Languages
6.4.2. Aspect-Oriented Workflow Languages

6.5. Summary

7. MonitA: The Generative Implementation Strategy

7.1. M&A Concerns Execution

7.2. Architecture for Creating a MonitA Generative Infrastructure
7.2.1. Functional Decomposition Viewpoint
7.2.2. Generative Strategy

7.3. Controlling the Workflow Generation Process
7.3.1. Transforming BPMN Models into Executable Workflows
7.3.2. Managing Traceability
7.3.3. Accessing Workflow Data

7.4. Generating the M&A Code
7.4.1. Transforming MonitA Specifications into AOP Code
7.4.2. Transforming MonitA Specifications into Workflow Code
7.4.3. Managing Measurement Data and Control Actions
7.4.4. Transforming Measurement Data

7.5. Composing the MonitA Code with Workflow Applications
7.5.1. Selecting the Level of Abstraction

7.6. Summary

8. MonitA: Implementation and Execution Infrastructure

8.1. Selected Technology

8.2. MonitA-JPDL Generative Infrastructure
8.2.1. JPDL Workflow Code Generator
8.2.2. MonitA Code Generator into JPDL
8.2.3. Composing MonitA Code with JPDL Applications

8.3. MonitA-BPEL Generative Infrastructure
8.3.1. BPEL Workfl.ow Code Generator
8.3.2. MonitA Code Generator into BPEL
8.3.3. Composing MonitA Code with BPEL Applications

8.4. Infrastructure for Enacting MonitA Specifications
8.4.1. Specification Environment
8.4.2. Measurement Data Store System
8.4.3. Workflow Monitoring and Analysis Dashboard

8.5. Summary

IV. Validation and Conclusion

9. Validation

9.1. Scenario 1: Trouble Ticket Workflow Application
9.1.1. Monitoring and Analysis Requirements
9.1.2. Generative Implementation and Composition

9.2. Scenario 2: Loan Approval Workflow Application
9.2.1. Data Association Model
9.2.2. Monitoring and Analysis Requirements
9.2.3. Generative Implementation and Composition

9.3. Scenario 3: Trip Expenses Workflow Application
9.3.1. Data Association Model
9.3.2. Monitoring and Analysis Requirements
9.3.3. Generative Implementation and Composition

9.4. Study 1: Measuring Development Costs by using MonitA
9.4.1. The Exploratory Study
9.4.2. Quantitative Results
9.4.3. Discussion

9.5. Study 2: Evaluating Maintainability and Understandability
9.5.1. Evaluation Results
9.5.2. Discussion

9.6. Study 3: Evaluating DSL Success Factors in MonitA
9.6.1. Basic Study
9.6.2. Results and Discussion

9.7. Summary

10. Comparing MonitA with Related Work
10.1. M&A Characterization
10.1.1. Execution Environment Capabilities
10.1.2. Monitoring and Analysis Capabilities

10.2. Workflow Monitoring and Analysis at Runtime
10.2.1. Architectures for Business Activity Monitoring
10.2.2. Model-Driven Approaches

10.3. Workflow Monitoring and Analysis A Posteriori
10.3.1. Architectures for Workflow Applications
10.3.2. Business Process Intelligence
10.3.3. Semantic Business Process Management
10.3.4. Process Analysis based on Event logs
10.3.5. Tool Support

10.4. Dynamic and Static Program Analysis

10.5. Process Data Models
10.5.1. Data Modeling in Workflow Applications
10.5.2. Data Modeling on Other Domains

10.6. Domain-Specific Aspect Languages
10.6.1. Business Rules on Business Processes

10.7. Service-Oriented Computing
10.7.1. Web Services Specification
10.7.2. Web Services Composition

10.8. Discussion: Positioning our Approach
10.9. Summary

11. Conclusion

11.1. Conclusions

11.2. Limitations and Future Work
11.2.1. Composing M&A Concerns at the Conceptual Level
11.2.2. Co-evolution of Process and MonitA Models
11.2.3. Managing Concerns Interactions
11.2.4. Expressiveness of the MonitA Language
11.2.5. Specification at a Higher-Level of Abstraction
11.2.6. Performance Evaluations

Appendix A. Formal Grammar of the MonitA Language
Appendix B. Semantics of MonitA Constructs
Appendix C. Formal Grammar of the Data Association Language
Appendix D. Model Transformations

References
Index