Generative Analysis: The Power of Generative AI for Object-Oriented Software Engineering with UML (Early Release)

✍ Scribed by Jim Arlow; Ila Neustadt

• Publisher: Addison-Wesley
• Year: 2024
• Tongue: English
• Leaves: 512
• Category: Library

✦ Synopsis

Learn a new method of object-oriented analysis called generative analysis and keep your skill-set on pace with how generative AI is transforming the face of software engineering
Generative AI is revolutionizing many industries, including software engineering. Many aspects of manual coding are becoming automated, and the skills needed by software engineers, developers, and analysts are evolving. Anyone who writes or works with code will need to produce precise analysis artifacts to feed the AI code generation process. Enter generative analysis: a precise, structured way to for software engineers, programmers, and analysts to transition to this new, AI-enhanced, software engineering world.

In Generative Analysis, experts Jim Arlow and Ila Neustadt leverage literate modeling, M++, and multivalent logic to lay out a precise and structured, step-by-step approach to object-oriented analysis that produces clear and unambiguous results suitable for further processing into code by generative AI systems such as Copilot, ChatGPT, and Gemini.

Generative analysis artifacts feed generative AIs to generate code and UML models

Techniques feed into and refine each other until a precise analysis definition of a software system is achieved

Well-defined process has definite milestones and end points to eliminate "analysis paralysis"

This guide teaches advanced, precise, and sophisticated analysis techniques that will allow you to thrive in the new world of software engineering with generative AI.

✦ 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