
Domain Modeling-Based Software Engineering
A Formal Approach
Hardcover | 31 August 2000
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372 Pages
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No approach can be said to be perfect if it fails to satisfy the following two criteria. Firstly, a good approach should support the full life cycle of software development. Secondly, a good approach should support the development of large-scale software for real use in many application domains. Such an approach can be referred to as a five-in-one approach.
The authors of this book have, for the past eight years, conducted research in knowledge-based software engineering, of which the final goal is to develop a paradigm for software engineering which not only integrates the three approaches mentioned above, but also fulfils the two criteria on which the five-in-one approach is based. Domain Modeling- Based Software Engineering: A Formal Approach explores the results of this research.
Domain Modeling-Based Software Engineering: A Formal Approach will be useful to researchers of knowledge-based software engineering, students and instructors of computer science, and software engineers who are working on large-scale projects of software development and want to use knowledge-based development methods in their work.
| List of Figures | p. xi |
| List of Tables | p. xiii |
| Foreword | p. xv |
| Acknowledgments | p. xvii |
| Introduction | |
| Challenge of the Era | p. 3 |
| The Requirement Analysis Gap Revisited | p. 3 |
| The Formal Methods | p. 5 |
| The Knowledge Based Approaches | p. 6 |
| The KISSME Approach | p. 8 |
| Introducing the Domain Knowledge | p. 8 |
| The Knowledge based Formal Approach | p. 10 |
| Ontology based Domain Analysis | p. 11 |
| A Three-Layer Structure of Requirement Elicitation | p. 11 |
| Pre-Requirement Analysis | p. 14 |
| Automatic Generation of Software Architecture | p. 16 |
| Automation, Interaction and Evolution | p. 17 |
| The Knowledge Industry | p. 18 |
| The Eagle Projects and the PROMIS Tools | p. 18 |
| The Eagle I Project | p. 18 |
| The Eagle II Project | p. 18 |
| The Eagle III Project | p. 20 |
| The Eagle IV Project | p. 20 |
| Organization of the book | p. 22 |
| Domain Analysis and Domain Modeling | |
| Ontology-Oriented Domain Analysis: The Foundation | p. 25 |
| Domain Analysis and Domain Engineering | p. 25 |
| DADL: Ontology-Oriented External Domain Knowledge Representation | p. 29 |
| The Features of the Domain | p. 30 |
| The Activity Model | p. 30 |
| The Role Model | p. 31 |
| The Data Model | p. 32 |
| The Domain Flow Model | p. 35 |
| Ontology as Formal Knowledge Representation | p. 36 |
| Can Object-Oriented Paradigm Express the Domain Knowledge? | p. 36 |
| Need for Ontology | p. 37 |
| A General Framework of Information Ontology | p. 38 |
| A Mathematical Model for Ontology | p. 41 |
| The Architecture of Knowledge Models | p. 44 |
| The Design Principle of DOKB | p. 44 |
| Family of Knowledge Models | p. 46 |
| ONONET: The Internal Domain Model Representation | p. 51 |
| INFORM: A Framework of Ontologies and Objects for Information System Modeling | p. 53 |
| Basic Object Types in INFORM | p. 53 |
| Organizing the Basic Entities with Relations | p. 55 |
| The Basic Relation Types in INFORM | p. 56 |
| The Basic Ontologies in INFORM | p. 58 |
| An Example in INFORM | p. 62 |
| SHOP: A Domain Model of Shopping Centers | p. 64 |
| Historical Remarks on Ontology like Domain Knowledge Representation | p. 68 |
| Ontology-Oriented Domain Analysis: The Dynamics | p. 73 |
| A Theory of Domain Classification | p. 74 |
| Need for Domain Classification | p. 74 |
| Enterprise Constructs and Repertory Grids | p. 74 |
| Building Up the Repertory Grids | p. 78 |
| Classifying the Enterprises | p. 81 |
| Classifying the Attributes | p. 91 |
| Build Virtual Domain Models: A Genetic Approach | p. 92 |
| SONONET and Well-Formed Domain Models | p. 104 |
| Interactive Operation for Constructing Domain Models | p. 115 |
| Interactive Operation | p. 116 |
| Tools for Constructing Domain Models | p. 117 |
| Knowledge Base Browser | p. 118 |
| The Knowledge based Software Development | |
| Automating The Requirement Analysis | p. 123 |
| The Pseudo-Natural Language BIDL | p. 123 |
| The Motivation of BIDL | p. 123 |
| The Design of BIDL | p. 124 |
| Formalizing the Pseudo-Natural Languages | p. 130 |
| The Relational Grammar | p. 130 |
| Parsing Pseudo-Natural Language Texts based on Relational Grammars | p. 133 |
| Pseudo-Natural Language for Pre-Requirement Analysis | p. 134 |
| Requirement Acquisition from Texts | p. 134 |
| The Pre-Requirement Analysis and its Automation | p. 135 |
| Requirement Acquisition from Pseudo-Natural Language Texts: First Step of OORA | p. 136 |
| IS-net: Transformational Semantics of BIDL | p. 137 |
| Need for a Semantic Network Representation | p. 137 |
| Syntax and Semantics of IS-net | p. 138 |
| Interactive Knowledge Acquirer and Its Automation | p. 142 |
| INKAI: The PROMIS Knowledge Acquirer | p. 142 |
| Automated Construction of Interactive Knowledge Acquisition Interface | p. 151 |
| Historical Remarks on the Pseudo-Natural Language Understanding PNLU | p. 154 |
| Motivation for Introducing Pseudo-Natural Languages | p. 154 |
| The Basic Idea of PNLU | p. 155 |
| First Experiences in PNLU | p. 158 |
| Application of PNLU Techniques to Information Systems Modeling | p. 158 |
| An Assessment of the PNLU Approach | p. 159 |
| Historical Remarks on Semantic Network Representation | p. 160 |
| The Snetl Language | p. 160 |
| The CS-net Language | p. 162 |
| Historical Remarks on Knowledge Acquirers | p. 163 |
| Oora: Ontology Oriented Requirement Analysis | p. 167 |
| On Executable Specification | p. 167 |
| The Object-Oriented Analysis Revisited | p. 168 |
| Ontology Recognition and Clustering | p. 171 |
| The Procedure of Ontology Recognition and Clustering | p. 171 |
| A Detailed Example | p. 175 |
| Semantic Integrity of OORA | p. 178 |
| What do We Mean by Semantic Integrity? | p. 178 |
| The Small and the Grand BIDL | p. 181 |
| Scalability of the Target Information System | p. 182 |
| Completeness of the Target Information System | p. 183 |
| Consistency of the Target Information System | p. 184 |
| Normality of the Target Information System | p. 185 |
| Intelligence of the Target Information System | p. 186 |
| User Independent And User Dependent Models | p. 186 |
| Why User Dependent Models? | p. 186 |
| Strategy Library and User Model | p. 187 |
| Environment Model | p. 189 |
| Strategy Forest | p. 189 |
| The Case based UDM Generator | p. 193 |
| Make Use of Commonsense | p. 195 |
| Planning Software Architecture | p. 201 |
| Issues on Software Architecture and Architecture Description Languages | p. 201 |
| Motivation of Studying Software Architecture | p. 201 |
| Different Software Architecture | p. 203 |
| Architecture Description Languages | p. 207 |
| The Architecture Description Language NEWCOM | p. 209 |
| An Overview of NEWCOM | p. 209 |
| The Components of NEWCOM | p. 210 |
| The Connectors of NEWCOM | p. 213 |
| An NEWCOM Example | p. 215 |
| A Comparison of NEWCOM with Other Architecture Implementation Languages | p. 216 |
| Planning the Client Server Architecture | p. 217 |
| Planning the Intranet | p. 224 |
| The Virtual Enterprise | |
| Intelligent Information Service | p. 229 |
| Motivation and Approaches | p. 229 |
| A Technical Basis: Processing the Fuzzy Information | p. 231 |
| The Architecture of PRINSE Data Warehouses | p. 234 |
| Hierarchical and Typed Model of Data Warehouse | p. 234 |
| Fuzzy Information Retrieval in Pseudo-Natural Language | p. 237 |
| Natural Style Query Language NQL | p. 237 |
| Query Language Interpreters | p. 239 |
| Query Answer Composers | p. 240 |
| Information Reporters | p. 243 |
| Data Warehouse Builder WARDER | p. 243 |
| Acquisition and Application of Temporal Knowledge | p. 244 |
| The TEMPO System | p. 244 |
| TKDL: A Language For Describing the Temporal Knowledge | p. 245 |
| TKCM: A Compiler for Integrating the Temporal Knowledge | p. 248 |
| Tendency Detection from Temporal Data | p. 252 |
| Data Mining and Knowledge Discovery | p. 252 |
| Learning Fuzzy Decision Trees | p. 253 |
| Learning Fuzzy Decision Trees from Sequential and Incomplete Data | p. 256 |
| Other Functional Agents of PRINSE | p. 267 |
| Agents as Tendency Detector | p. 267 |
| Agents as Exception Handlers | p. 268 |
| Agents as Time Monitor | p. 268 |
| Software Reuse and System Evolution | p. 269 |
| Software Evolution versus Software Reuse | p. 269 |
| Software Reuse | p. 269 |
| Component Based and Knowledge Based Software Reuse | p. 270 |
| Software Evolution | p. 271 |
| Horizontal System Evolution | p. 272 |
| A General Schema of Software Reuse and Software Evolution in PROMIS | p. 272 |
| Program Evolution at BIDL Level | p. 274 |
| Program Evolution at NEWCOM Level | p. 280 |
| Vertical Software Evolution | p. 282 |
| Software Process as a Third Dimension of Software Evolution | p. 282 |
| Evolution of Software Process in PROMIS | p. 284 |
| Ontology as Software Process | p. 285 |
| Executable Software Process Ontology | p. 289 |
| Database Transformation | p. 295 |
| Meaning and Goals of Database Transformation | p. 295 |
| Data Warehouse Evolution | p. 297 |
| Evolution of Tools | p. 300 |
| Tool Evolution at BIDL Level | p. 300 |
| Tool Evolution at Semantic Network Representation Level | p. 304 |
| Evolution at Knowledge Base Level | p. 305 |
| A Summary | |
| Summary and Assessment | p. 311 |
| Combining Formal Methods with Knowledge Based Ones | p. 311 |
| Ontology as Unified Representation Paradigm for Different Approaches | p. 313 |
| Data Flow Diagram | p. 313 |
| Data Structure Diagram | p. 314 |
| The Jackson Development Method | p. 314 |
| Entity Relationship Data Models | p. 316 |
| Knowledge Based Fast Prototyping and a New Software Life Cycle | p. 317 |
| Pseudo-Natural Language versus Natural Like Languages | p. 322 |
| Pseudo-Natural Language versus Pseudo Code | p. 324 |
| Pseudo-Natural Language versus Limited Natural Language | p. 326 |
| The Knowledge Industry | p. 329 |
| Knowledge Engineers versus Software Engineers | p. 329 |
| Knowledge Industry versus Software Industry | p. 330 |
| Table of Contents provided by Syndetics. All Rights Reserved. |
ISBN: 9780792378891
ISBN-10: 079237889X
Series: The Kluwer International Series on Asian Studies in Computer and Information Science, 8
Published: 31st August 2000
Format: Hardcover
Language: English
Number of Pages: 372
Audience: General Adult
Publisher: Springer Nature B.V.
Country of Publication: US
Dimensions (cm): 23.5 x 15.88 x 2.54
Weight (kg): 0.69
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