Functional Program Design in Scala 2: Advanced Concepts

We'll start by revisiting some concepts that we have learned from Principles of Functional Programming in Scala; collections, pattern matching, and functions. We'll then touch on for-comprehensions, a powerful way in Scala to traverse a list, process it, and return a new list. We'll see how to do queries with for-comprehensions as well as how the for-comprehension is "desugared" into calls to higher-order functions by the Scala compiler. Finally, we'll discuss what monads are, and how to verify that the monad laws are satisfied for a number of examples.

This week we'll revisit performance issues caused by combinatorial search, and we'll discover an important concept in functional programming that can address these issues: laziness. We'll also learn a little bit about proofs on trees; in particular, we'll see how to extend structural induction to trees.

This week, we'll learn how to make the compiler write programs for us! We'll see how the compiler can summon program fragments based on their type and how this mechanism can be used to implement a new form of polymorphism (type classes).

This week, we'll learn about state and side-effects. Through a rich example, we'll learn programming patterns for managing state in larger programs. We'll also learn about for-loops and while-loops in Scala.

This week we'll learn a number of important programming patterns via examples, starting with the observer pattern, and then going on to functional reactive programming.