Runnable Specifications
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Table of Contents
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Introduction
Objectives
- Discover what you will learn in this book.
- Learn whether this book is for you.
- Understand how to use this book.
Chapter 1: Data Lens Part 1
Capture information and its relationships in a data model
Objectives
- Learn to analyze the structure of a domain and encode it in your language.
- Learn to evaluate data models based on fit.
- Understand how domain models are constructed by abstraction, encoding, and feedback.
This chapter presents a challenge to me as an author: I've got to reteach something most programmers already do intuitively without making it obvious and boring.
You probably have an intuitive sense of how to model the data of a domain. You likely do it every day. But sometimes we need to relearn the skills we rely on at a deeper level so we can build on top of the new understanding.
The data lens is all about encoding the relationships we find in our domain using features of our language with the same structure.
Chapter 2: Data Lens Part 2
Further explorations of encoding relationships in data
Objectives
- Understand the important distinction between component and peer relationships.
- Discover when and how to reify a relationship into its own encoding.
- Learn the various ways we can enforce the structure of our encoding.
In Chapter 1, we began our exploration of encoding the relationships among values in a domain. This chapter continues that exploration, diving deeper into the structure of more complex relationships. We get into some theory. And we end it by learning different ways to encode and enforce structure.
Data Lens Supplement
Chapter 3: Operation Lens
Operations are the heart of a domain model
Objectives
- Understand how function signatures concisely encode the intent of a use case.
- Discover how total functions make your domain model more robust.
- Learn to specify requirements with functions you can't define.
Once you know how to data model, you should forget about it. Start with modeling the operations. The operations will give you so much information about how to encode your data, and since you're good at data modeling, you can do it later.
In this chapter, we're going to learn how to reason about operations without knowing how they are implemented or how the values they operate on are encoded.
Chapter 4: Composition Lens
Capture how operations work together
Objectives
- Learn to align the model with the relationships between operations in a domain.
- Understand how to encode the relationships as tests.
The operations play a vital role in the domain model, and until now, we've considered them in isolation. But the operations also have relationships between themselves. We can extract quite a lot of information from those relationships to make better design decisions.
Chapter 5: Domain Lens
Define the problem to model the right thing
Objectives
- Discover ways to look past our biases to clearly see the problem your software is solving.
- Learn to use that clarity to model the domain more simply and directly.
Chapter 6: Volatility Lens
Look at how things change over time
Objectives
- Learn to look at change over time to improve our design decisions
- Learn to look at change across users to improve our design decisions
Chapter 7: Layers Lens
Take a lateral approach to solving difficult problems
Objectives
- Learn to defer decisions to a higher layer when it makes the layer cleaner.
- Learn to wrangle tough domains by going down to a lower layer.
We have to make difficult decisions when designing. And sometimes any path we take will make a mess. But we often don't have to face the decision head on. We can take advantage of the layer structure and make a clean decision in a higher or lower layer.
Chapter 8: Time Lens
Model changes over time explicitly
Objectives
- Learn to model time explicitly in a domain.
- Understand when modeling time is useful.
- Discover how an explicit model of time makes implementing undo easy.
Chapter 9: Architecture Lens
Build mini-models of architectural features to isolate complexity
Objectives
- Learn to create models to isolate architectural complexity.