Table of contents : Cover Page Title Page Contents Table of Contents Preface About this book Who this book is for About the Authors Chapter 1: Generative Analysis for Generative AI 1.1 Introduction 1.2 Chapter contents 1.3 Communication and Neuro Linguistic Programming (nlp) 1.4 Abstraction 1.5 Finding the right level of abstraction for Generative AI 1.6 Choice of Generative AI 1.7 Applying Generative AI to an example problem domain 1.8 Modeling in Generative Analysis 1.9 Chapter Summary Chapter 2: Launching OLAS, the example project 2.1 Introduction 2.2 Chapter contents 2.3 OLAS - the problem domain 2.4 Software engineering processes 2.5 The Unified Process (UP) 2.6 P structure 2.7 UP workflows 2.8 UP phases 2.9 The UP Phases in the world of Generative AI 2.10 The OLAS inception phase 2.11 The OLAS Vision Statement 2.12 Keep all documents as concise as possible 2.13 Chapter summary Chapter 3: Capturing information in Generative Analysis 3.1 Introduction 3.2 Chapter contents 3.3 Capturing informal, unstructured information 3.4 Mind Mapping 3.5 Concept Mapping 3.6 Dialog Mapping 3.7 Antipatterns in Mapping meetings 3.8 Generative AI and Mapping meetings 3.9 Structured writing 3.10 Structured Documents 3.11 Principles for structuring information 3.12 Structured Writing example 3.13 Complexity vs. profundity? 3.14 Chapter Summary Chapter 4: OLAS Elaboration Phase 4.1 Introduction 4.2 Chapter contents 4.3 Concept Mapping OLAS 4.4 Creating a first-cut logical architecture 4.5 Using Generative AI to kick-start the OLAS Logical Architecture 4.6 How to validate the First-Cut Logical Architecture 4.7 Chapter Summary Chapter 5: Communication 5.1 Introduction 5.2 Chapter contents 5.3 Communication in Generative Analysis 5.4 Flexibility is the key to excellent communication 5.5 Semiotics and the structure of meaning 5.6 Ontology 5.7 Metaphor 5.8 Constructing the Generative Analysis model of human communication 5.9 The Generative Analysis communication model 5.10 Chapter summary Chapter 6: M++ 6.1 Introduction 6.2 Chapter contents 6.3 The nlp Meta Model and M++ 6.4 The M++ pattern template 6.5 Deletion 6.6 Generalization 6.7 Distortion 6.8 More about propositional functions 6.9 Using M++ in Generative Analysis 6.10 Key points for applying M++ 6.11 Summary Chapter 7: Literate Modeling 7.1 Introduction 7.2 Chapter contents 7.3 Limitations of visual models as conveyors of meaning 7.4 The solution—Literate Modeling 7.5 Creating a Business Context Document (BCD) 7.6 Structure of the BCD 7.7 Learn Literate Modeling by example 7.8 Leveraging Generative AI for Literate Modeling 7.9 Integrating engineered prompts with BCDs 7.10 Chapter summary Chapter 8: Information in Generative Analysis 8.1 Introduction 8.2 Chapter contents 8.3 Conversations with Generative AI 8.4 The Generative Analysis Information Model 8.5 Classifying information 8.6 Information 8.7 Resource 8.8 Question 8.9 Proposition 8.10 Idea 8.11 Requirement 8.12 Term 8.13 Chapter summary Chapter 9: Generative Analysis by Example 9.1 Introduction 9.2 Chapter contents 9.3 How to perform Generative Analysis 9.4 Identifying the Information types 9.5 Semantic highlighting 9.6 Finding Resources using Generative AI 9.7 Finding Terms 9.8 Key Statement analysis 9.9 Line-by-line Generative Analysis of the OLAS Vision Statement 9.10 Publishing your Generative Analysis results 9.11 Controlling the GA activity 9.12 Chapter summary Chapter 10: Use case modeling OLAS 10.1 Chapter contents 10.2 The first-cut use case model 10.3 Avoiding analysis paralysis in use case modeling 10.4 How to produce the first-cut use case model 10.5 Use case modelling OLAS 10.6 Using Generative AI in use case modelling 10.7 Patterns in use case modelling - CRUD 10.8 Structuring the use case model 10.9 The homonym problem 10.10 Common mistakes in use case modeling 10.11 Next steps in Generative Analysis of OLAS 10.12 Chapter summary Chapter 11: The Administration Subsystem 11.1 Introduction 11.2 Chapter contents 11.3 Elaborating the Administration subsystem 11.4 Writing CRUD use cases 11.5 Administration: Create 11.6 Administration: Read 11.7 Administration: Update 11.8 Administration: Delete 11.9 Administration use cases wrap up 11.10 Use case realization for the Administration use cases 11.11 Creating a class diagram 11.12 Administration wrap-up 11.13 Generating a behavioural prototype 11.14 Chapter Summary Chapter 12: The Security subsystem 12.1 Introduction 12.2 Chapter contents 12.3 The Security subsystem 12.4 OLAS security policy 12.5 LogOn use case specification 12.6 UnfreezeAccount use case specification 12.7 LogOff use case specification 12.8 Use case realization for the Security subsystem 12.9 Creating sequence diagrams 12.10 Chapter summary Chapter 13: The Catalog subsystem 13.1 Introduction 13.2 Chapter contents 13.3 The Normal and Restricted Collections 13.4 Modeling the Normal and Restricted Catalogs 13.5 The Type/Instance pattern 13.6 Type/Instance: Elements Similar for the OLAS catalogs 13.7 Creating a class model for the catalogs 13.8 The NormalCatalog subsystem use case model 13.9 Reuse with modification strategy for the RestrictedCatalog subsystem 13.10 The RestrictedCatalog subsystem use case model 13.11 Generative AI for use case realization 13.12 Catalog subsystem wrap-up 13.13 Chapter Summary Chapter 14: The Loan subsystem 14.1 Introduction 14.2 Chapter contents 14.3 The Loan subsystem CRUD analysis 14.4 What is a loan? 14.5 Loan subsystem: Create 14.6 State machines for the Loan subsystem 14.7 Loan subsystem: Read 14.8 Fines 14.9 OLASUser class state machine 14.10 Loan subsystem: Update 14.11 Loan subsystem: Delete 14.12 Library vacations 14.13 LibraryVacation: Use case model 14.14 Trust no one 14.15 Loan subsystem wrap-up 14.16 Chapter Summary Chapter 15: The Innsmouth interface 15.1 Introduction 15.2 Chapter contents 15.3 Exchanging catalog information 15.4 How should the catalog sharing be handled in OLAS? 15.5 Updating the InnsmouthInterface use case model 15.6 Getting the Gilman Catalog 15.7 Generating the OLAS export mechanism for the restrictedCatalog 15.8 The Innsmouth Interface wrap-up 15.9 Chapter summary Chapter 16: Milton++ 16.1 Introduction 16.2 Chapter contents 16.3 Communication trances 16.4 Rapport 16.5 Your unconscious mind 16.6 Trance and Generative AI 16.7 The Milton Model and Milton++ 16.8 Distortion, deletion, and generalization in Milton++ 16.9 Distortion 16.10 Deletion 16.11 Generalization 16.12 Chapter summary Summary Bibliography