Formalization of Design Patterns by Means of Ontologies

Table of Contents

1 Introduction

2 Related Work

2.1 Classification of Design Patterns

2.2 Ontological and Other Formal Approaches

3 Design Patterns

3.1 The GOF Pattern Catalogue

3.1.1 Abstract Factory

3.1.2 Builder

3.1.3 Factory Method

3.1.4 Prototype

3.1.5 Singleton

3.1.6 Adapter

3.1.7 Bridge

3.1.8 Composite

3.1.9 Decorator

3.1.10 Facade

3.1.11 Flyweight

3.1.12 Proxy

3.1.13 Chain of Responsibility

3.1.14 Command

3.1.15 Interpreter

3.1.16 Iterator

3.1.17 Mediator

3.1.18 Memento

3.1.19 Observer

3.1.20 State

3.1.21 Strategy

3.1.22 Template Method

3.1.23 Visitor

4 Ontologies

4.1 The Web Ontology Language OWL

4.1.1 Classes

4.1.2 Properties

4.1.3 Individuals

4.1.4 The Manchester OWL Syntax

4.2 Other Ontology Languages

4.2.1 RDF and XML

4.2.2 RDFS

4.2.3 DAML+OIL

4.3 Conclusions

5 Ontology Engineering Tools

5.1 Protégé

5.2 Querying and Inference Approaches

5.2.1 SPARQL and the Jena Framework

5.2.2 The Pellet DIG Reasoner

5.2.3 RacerPro

5.2.4 The nRQL Query Language

5.3 Conclusions

6 Developing the DPIO

6.1 Knowledge-Engineering Methodology

6.2 Domain and Scope of the Ontology

6.3 Competency Questions

6.3.1 Meta Questions

6.3.2 Questions in the Domain of Design Patterns

6.4 Initial Vocabulary

6.4.1 Intent Classification

6.5 Modeling the Ontology

6.5.1 Classes

6.5.2 Properties

6.5.3 Instances

6.5.4 Examples of Modeled Design Problems

6.6 Completeness of the Ontology

6.7 Conclusions

7 Evaluation

7.1 Formalization of Competency Questions

7.1.1 Meta Questions

7.1.2 Questions in the Domain of Design Patterns

7.2 Test of the Ontology

7.3 Conclusions

8 The Design Pattern Wizard

8.1 Requirements

8.2 Architecture

8.3 The Wizard User Interface

8.4 Conclusions

9 Conclusions and Future Work

Objectives and Topics

This thesis aims to address the challenge of selecting appropriate design patterns from an ever-growing catalog by formalizing their intent using an ontology. The primary research goal is to develop the Design Pattern Intent Ontology (DPIO) and a supportive tool that assists developers in identifying the most suitable design pattern for a given software design problem.

• Formal classification of the 23 GoF design patterns based on their intent.
• Development of the Design Pattern Intent Ontology (DPIO) using the Web Ontology Language (OWL).
• Creation of the Design Pattern Wizard, a prototype tool that leverages the ontology to suggest design patterns.
• Implementation of a knowledge-based approach to visual problem definition and automated pattern recommendation.

Excerpt from the Book

Summary of Chapters

1 Introduction: Discusses the motivation behind formalizing design pattern intents to assist in the complex selection process, highlighting the limitations of narrative text in traditional pattern catalogs.

2 Related Work: Provides a comprehensive overview of existing classification schemes for design patterns and formal approaches to pattern representation.

3 Design Patterns: Summarizes the intent and applicability of the 23 classic GoF design patterns, which serve as the foundation for the developed ontology.

4 Ontologies: Introduces ontology concepts, emphasizing the role of OWL in making domain knowledge machine-understandable.

5 Ontology Engineering Tools: Reviews development environments and query languages, specifically focusing on Protégé, SPARQL, and nRQL for ontology manipulation and inference.

6 Developing the DPIO: Describes the systematic engineering process for building the Design Pattern Intent Ontology, covering methodology, vocabulary, and modeling decisions.

7 Evaluation: Details the formal evaluation of the DPIO by testing it against defined competency questions using the nRQL query language.

8 The Design Pattern Wizard: Presents the architecture and user interface of the prototypical tool that utilizes the DPIO to provide visual pattern suggestions to developers.

9 Conclusions and Future Work: Reflects on the effectiveness of the proposed ontological approach and outlines potential enhancements for future iterations.

Keywords

Design Patterns, Ontology, OWL, DPIO, Design Pattern Wizard, Software Engineering, Knowledge Representation, SPARQL, nRQL, Pattern Selection, Intent Formalization, GoF, Protégé, Ontology Engineering, Reuse

Frequently Asked Questions

What is the core problem addressed in this work?

The thesis addresses the difficulty developers face in selecting the right design pattern from an increasing number of options, as traditional catalogs are optimized for human reading rather than tool-based support.

What are the central thematic fields?

The central fields include software design patterns, ontology engineering, formal knowledge representation, and intelligent tool development for software architecture.

What is the primary research goal?

The goal is to build a "Design Pattern Intent Ontology" (DPIO) that formally describes the intent of design patterns and to develop a wizard tool that helps users select patterns based on their specific design problems.

Which scientific method is employed?

The author uses a knowledge-engineering methodology to build the ontology, incorporating concepts from description logic, OWL, and formal query languages to test the ontology's completeness via competency questions.

What is covered in the main section?

The main sections cover the formalization of pattern intents, the development of the DPIO hierarchy, the evaluation of the ontology, and the architectural implementation of the Design Pattern Wizard.

Which keywords best characterize the work?

Design patterns, ontology, formal representation, pattern selection, and software engineering tools are the central pillars of the research.

How does the ontology handle the n:m relationship between problems and patterns?

The ontology models design problems as separate "containers" of constraints, which are linked to design patterns via the object property "isSolutionTo", allowing a many-to-many mapping.

How is the Design Pattern Wizard integrated into a development workflow?

The wizard acts as a visual front-end that translates user-defined constraints into SPARQL queries, suggesting relevant patterns without requiring the user to have deep knowledge of the underlying ontology query language.