You are previewing Functional Programming in C#: Classic Programming Techniques for Modern Projects.

Functional Programming in C#: Classic Programming Techniques for Modern Projects

  1. Cover
  2. Title
  3. Copyright
  4. About the Author
  5. Credits
  6. Contents
  7. Introduction
  8. Part I : Introduction to Functional Programming
    1. Chapter 1 : A Look at Functional Programming History
      1. What Is Functional Programming?
      2. Functional Languages
      3. The Relationship to Object Oriented Programming
      4. Summary
    2. Chapter 2 : Putting Functional Programming into a Modern Context
      1. Managing Side Effects
      2. Agile Programming Methodologies
      3. Declarative Programming
      4. Functional Programming Is a Mindset
      5. Is Functional Programming in C# a Good Idea?
      6. Summary
  9. Part II : C# Foundations of Functional Programming
    1. Chapter 3 : Functions, Delegates, and Lambda Expressions
      1. Functions and Methods
      2. Reusing Functions
      3. Anonymous Functions and Lambda Expressions
      4. Extension Methods
      5. Referential Transparency
      6. Summary
    2. Chapter 4 : Flexible Typing with Generics
      1. Generic Functions
      2. Generic Classes
      3. Constraining Types
      4. Other Generic Types
      5. Covariance and Contravariance
      6. Summary
    3. Chapter 5 : Lazy Listing with Iterators
      1. The Meaning of Laziness
      2. Enumerating Things with .NET
      3. Implementing Iterator Functions
      4. Chaining Iterators
      5. Summary
    4. Chapter 6 : Encapsulating Data in Closures
      1. Constructing Functions Dynamically
      2. The Problem with Scope
      3. How Closures Work
      4. Summary
    5. Chapter 7 : Code Is Data
      1. Expression Trees in .NET
      2. Analyzing Expressions
      3. Generating Expressions
      4. .NET 4.0 Specifics
      5. Summary
  10. Part III : Implementing Well-known Functional Techniques in C#
    1. Chapter 8 : Currying and Partial Application
      1. Decoupling Parameters
      2. Calling Parts of Functions
      3. Why Parameter Order Matters
      4. Summary
    2. Chapter 9 : Lazy Evaluation
      1. What’s Good about Being Lazy?
      2. Passing Functions
      3. Explicit Lazy Evaluation
      4. Comparing the Lazy Evaluation Techniques
      5. How Lazy Can You Be?
      6. Summary
    3. Chapter 10 : Caching Techniques
      1. The Need to Remember
      2. Precomputation
      3. Memoization
      4. Summary
    4. Chapter 11 : Calling Yourself
      1. Recursion in C#
      2. Tail Recursion
      3. Accumulator Passing Style
      4. Continuation Passing Style
      5. Indirect Recursion
      6. Summary
    5. Chapter 12 : Standard Higher Order Functions
      1. Applying Operations: Map
      2. Map, Filter, and Fold in LINQ
      3. Standard Higher Order Functions
      4. Summary
    6. Chapter 13 : Sequences
      1. Understanding List Comprehensions
      2. A Functional Approach to Iterators
      3. Ranges
      4. Restrictions
      5. Summary
    7. Chapter 14 : Constructing Functions from Functions
      1. Composing Functions
      2. Advanced Partial Application
      3. Combining Approaches
      4. Summary
    8. Chapter 15 : Optional Values
      1. The Meaning of Nothing
      2. Implementing Option(al) Values
      3. Summary
    9. Chapter 16 : Keeping Data from Changing
      1. Change Is Good — not!
      2. False Assumptions
      3. Implementing Immutable Container Data Structures
      4. Alternatives to Persistent Data Types
      5. Summary
    10. Chapter 17 : Monads
      1. What’s in a Typeclass?
      2. What’s in a Monad?
      3. Why Do a Whole Abstraction?
      4. A Second Monad: Logging
      5. Syntactic Sugar
      6. Binding with SelectMany?
      7. Summary
  11. Part IV : Putting Functional Programming into Action
    1. Chapter 18 : Integrating Functional Programming Approaches
      1. Refactoring
      2. Writing New Code
      3. Finding Likely Candidates for Functional Programming
      4. Summary
    2. Chapter 19 : The MapReduce Pattern
      1. Implementing MapReduce
      2. Abstracting the Problem
      3. Summary
    3. Chapter 20 : Applied Functional Modularization
      1. Executing SQL Code from an Application
      2. Rewriting the Function with Partial Application and Precomputation in Mind
      3. Summary
    4. Chapter 21 : Existing Projects Using Functional Techniques
      1. The .NET Framework
      2. LINQ
      3. Google MapReduce and Its Implementations
      4. NUnit
      5. Summary
  12. Index
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FALSE ASSUMPTIONS

The interesting thing about the test in this example is that an assumption is made: “while the process of calculating the MutableOrderLine value is in progress, the values of MutableProduct.Price and MutableOrderLine.Count are not going to change.” Within the context of this simple test, the assumption is correct, but outside such an artificial context, this cannot easily be guaranteed. The data structures are declared in such a way that the data contained within them could change at any time. Of course this can only happen in reality if the data is shared across threads running in parallel. In Microsoft’s documentation of .NET Framework data types, there is a section that states whether each data type is to be regarded thread safe or not. The data structures that are marked thread safe usually use locking or other access protection/coordination mechanisms to prevent conflicting access.

In the example scenario, the data that is assumed to be consistent throughout the unit of work represented by the GetValue function lives in two different objects. The objects themselves could theoretically implement locking on their individual properties, but that wouldn’t be sufficient. This algorithm would need locking on the function level, acquiring two separate locks before going about its business of calculating the result. Or perhaps it wouldn’t matter whether the old or the new value of a simple field like Count is being used. The scenario certainly shows the issues that ...

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