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What is the Scala hierarchy?


What is the difference between by-name and by-value parameters?

A by-value parameter is evaluated before the method is invoked e.g. (x: Int) while a by-name parameter is not evaluated before the method is invoked, but each time the parameter is referenced inside the method e.g. (x: => Int)

What are the differences between def val var lazy?

  • def defines a method
  • val defines a fixed value, it is immmutable and eagerly initialized
  • var defines a variable reference, it is mutable and it should be avoided
  • lazy only initialised when required and as late as possible (deferred evaluation), default is strict and is not recomputed like by-name parameters

What are Nothing Nil None Empty Null null Unit?

  • Nothing is a trait that is the bottom subtype of every subtype of Any
  • Nil is an empty list that is defined as a List[Nothing]
  • None is an empty option that is defined as a Option[Nothing]
  • Null is a trait and is the bottom type similiar to Nothing but only for AnyRef not AnyVal
  • null is an instance of the Null trait
  • Unit is a subtype of AnyVal, it's only value is () and it is not represented by any object in the underlying runtime system. A method with return type Unit is analogous to a Java method which is declared void

What is the uniform access principal?

The uniform access principle states that variables, precomputed properties and parameterless functions should be accessed using the same syntax. Therefore not betraying whether they are implemented through storage or through computation. Scala supports this principle by not allowing parentheses to be placed at call sites of parameterless functions. A parameterless function definition def can be changed to a val or vice versa, without affecting client code

What referentially transparent means?

An expression e is referentially transparent if, for all programs p, all occurrences of e in p can be replaced by the result of evaluating e without affecting the meaning of p

What is a pure function?

A function f is pure if the expression f(x) is referentially transparent for all referentially transparent x. Hence a pure function is modular and composable

What is a higher-order function?

A higher-order function is a function that takes other functions as arguments or returns a function as result

What is recursive function?

A recursive function is a function which calls itself. With head recursion, the recursive call is not the last instruction in the function.

A tail recursive function is a special case of recursion in which the last instruction executed in the method is the recursive call. As long as the recursive call is in tail position, Scala detects and compiles it to the same sort of bytecode as would be emitted for a while loop

def factorial(n: Int): Int = {
  def loop(index: Int, result: Int): Int = index match {
    case i if i == 0 => loop(1, 1 * result)
    case i if i < n => loop(i + 1, i * result)
    case i => i * result
  loop(0, 1)

What is a function literal?

Function literal is a synonyms for anonymous function. Because functions are just ordinary Scala objects, we say that they are first-class values. A function literal is syntactic sugar for an object with a method called apply

val lessThan0 = (a: Int, b: Int) => a < b
val lessThan1 = (a, b) => a < b
val lessThan2 = new Function2[Int, Int, Boolean] {
  override def apply(a: Int, b: Int): Boolean = a < b

What is a variadic function?

A variadic function accepts zero or more arguments. It provides a little syntactic sugar for creating and passing a Seq of elements explicitly. The special _* type annotation allows to pass a Seq to a variadic method

sealed trait MyList[+A]
case object MyNil extends MyList[Nothing]
case class MyCons[+A](head: A, tail: MyList[A]) extends MyList[A]

object MyList {
  def apply[A](list: A*): MyList[A] =
    if (list.isEmpty) MyNil
    else MyCons(list.head, apply(list.tail: _*))

// usage
MyList(1, 2, 3, 4, 5)

What is a value class?

The AnyVal class can be used to define a value class, which is optimized at compile time to avoid the allocation of an instance

final case class Price(value: BigDecimal) extends AnyVal {
  def lowerThan(p: Price): Boolean = this.value < p.value

What is autoboxing?

The JVM defines primitive types (boolean, byte, char, float, int, long, short and double) that are stack-allocated rather than heap-allocated. When a generic type is introduced, for example, scala.collection.immutable.List, the JVM references an object equivalent, instead of a primitive type. For example, an instantiated list of integers would be heap-allocated objects rather than integer primitives. The process of converting a primitive to its object equivalent is called boxing, and the reverse process is called unboxing. Boxing is a relevant concern for performance-sensitive programming because boxing involves heap allocation. In performance-sensitive code that performs numerical computations, the cost of boxing and unboxing can can create significant performance slowdowns

What is the specialized annotation?

Specialization with @specialized annotation, refers to the compile-time process of generating duplicate versions of a generic trait or class that refer directly to a primitive type instead of the associated object wrapper. At runtime, the compiler-generated version of the generic class (or, as it is commonly referred to, the specialized version of the class) is instantiated. This process eliminates the runtime cost of boxing primitives, which means that you can define generic abstractions while retaining the performance of a handwritten, specialized implementation although it has some quirks

What is the switch annotation?

In scenarios involving simple pattern match statements that directly match a value, using @switch annotation provides a warning at compile time if the switch can't be compiled to a tableswitch or lookupswitch which procides better performance, because it results in a branch table rather than a decision tree

What is an Algebraic Data Type?

In type theory, regular data structures can be described in terms of sums, products and recursive types. This leads to an algebra for describing data structures (and so-called algebraic data types). Such data types are common in statically typed functional languages

An algebraic data type (ADT) is just a data type defined by one or more data constructors, each of which may contain zero or more arguments. We say that the data type is the sum or union of its data constructors, and each data constructor is the product of its arguments, hence the name algebraic data type


  • these types represent a SUM type because Shape is a Circle OR a Rectangle
  • Circle is a PRODUCT type because it has a radius
  • Rectangle is a PRODUCT type because it has a width AND a height
sealed trait Shape
final case class Circle(radius: Double) extends Shape
final case class Rectangle(width: Double, height: Double) extends Shape

How for-comprehensions is desugared? (docs)

// (1) works because "foreach" is defined
scala> for (i <- List(1, 2, 3)) println(i)

// (2) "yield" works because "map" is defined
scala> for (i <- List(1, 2, 3)) yield i*2
res2: List[Int] = List(2, 4, 6)

// (3) "if" works because "withFilter" is defined
scala> for (i <- List(1, 2, 3, 4); if i%2 == 0) yield i*2
res3: List[Int] = List(4, 8)

// (4) works because "flatMap" is defined
scala> for (i <- List(1, 2, 3, 4); j <- List(3, 4, 5, 6); if i == j) yield i
res4: List[Int] = List(3, 4)

What is a Typeclass?

A Typeclass is a programming pattern that allow to extend existing libraries with new functionality, without using traditional inheritance and without altering the original library source code using a combination of ad-hoc polymorphism, parametric polymorphism (type parameters) and implicits

What is a Monoid?

A Monoid is an algebraic type with 2 laws, a binary operation over that type, satisfying associativity and an identity element

  • associative e.g a + (b + c) == (a + b) + c
  • identity e.g. for sum is 0, for product is 1, for string is ""
trait Monoid[A] {
  // associativity
  // op(op(x, y), z) == op(x, op(y, z))
  def op(x: A, y: A): A

  // identity
  // op(x, zero) == op(zero, x) == x
  def zero: A

// example
val stringMonoid = new Monoid[String] {
  override def op(x: String, y: String): String = x + y
  override def zero: String = ""

Monoids have an intimate connection with lists and arguments of the same type, it doesn't matter if we choose foldLeft or foldRight when folding with a monoid because the laws of associativity and identity hold, hence this allows parallel computation

The real power of monoids comes from the fact that they compose, this means, for example, that if types A and B are monoids, then the tuple type (A, B) is also a monoid (called their product)

scala> List("first", "second", "third").foldLeft(
scala> List("first", "second", "third").foldRight(
res: String = firstsecondthird

What is a Semigroup?

A Semigroup is just the combine part of a Monoid. While many semigroups are also monoids, there are some data types for which we cannot define an empty element e.g. non-empty sequences and positive integers

trait Semigroup[A] {
  // or op
  def combine(x: A, y: A): A

trait Monoid[A] extends Semigroup[A] {
  // or zero
  def empty: A

What is a Functor?

Informally, a Functor is anything with a map method

// F is a higher-order type constructor or a higher-kinded type
trait Functor[F[_]] {
  def map[A, B](fa: F[A])(f: A => B): F[B]

What is a Monad?

Informally, a Monad is anything with a constructor and a flatMap method. A Monad is a mechanism for sequencing computations, all monads are functors but the opposite is not true.

A Monad is an implementation of one of the minimal sets of monadic combinators, satisfying the laws of associativity and identity

  • unit and flatMap
  • unit and compose
  • unit, map and join

where the above are defined

def unit[A](a: => A): F[A]
def map[A, B](ma: F[A])(f: A => B): F[B]
def flatMap[A, B](ma: F[A])(f: A => F[B]): F[B]
def compose[A, B, C](f: A => F[B], g: B => F[C]): A => F[C]
def join[A](mma: F[F[A]]): F[A]

// Identity: compose(unit, f) = f = compose(f, unit)
// Associativity: compose(compose(f, g), h) = compose(f, compose(g, h))

A Monad provide a context for introducing and binding variables and performing variable substitution

object Monad {
  case class Id[A](value: A) {
    def map[B](f: A => B): Id[B] =
    def flatMap[B](f: A => Id[B]): Id[B] =

  val idMonad: Monad[Id] = new Monad[Id] {
    override def unit[A](a: => A): Id[A] =

    override def flatMap[A, B](ma: Id[A])(f: A => Id[B]): Id[B] =

Monad.Id("hello ").flatMap(a => Monad.Id("world").flatMap(b => Monad.Id(a + b)))

for {
  a <- Monad.Id("hello ")
  b <- Monad.Id("world")
} yield a + b

res: Monad.Id[String] = Id(hello world)

What is a Semigroupal?

A Semigroupal is a type class that allows to combine contexts. In contrast to flatMap, which imposes a strict order, Semigroupal parameters are independent of one another, which gives more freedom with respect to monads

trait Semigroupal[F[_]] {
  def product[A, B](fa: F[A], fb: F[B]): F[(A, B)]

What is an Applicative?

  • all applicatives are functors
  • all applicatives are a semigroupal
  • all monads are applicative functors, viceversa is not true
// cats definition
trait Apply[F[_]] extends Semigroupal[F] with Functor[F] {
  def ap[A, B](ff: F[A => B])(fa: F[A]): F[B]
  def product[A, B](fa: F[A], fb: F[B]): F[(A, B)] =
    ap(map(fa)(a => (b: B) => (a, b)))(fb)

trait Applicative[F[_]] extends Apply[F] {
  def pure[A](a: A): F[A]

// red book definition
trait Applicative[F[_]] extends Functor[F] {
  // primitive combinators
  def map2[A, B, C](fa: F[A], fb: F[B])(f: (A, B) => C): F[C]
  def unit[A](a: => A): F[A]

  // derived combinators
  def map[A, B](fa: F[A])(f: A => B): F[B] =
    map2(fa, unit(()))((a, _) => f(a))
  def traverse[A, B](as: List[A])(f: A => F[B]): F[List[B]] =
    as.foldRight(unit(List[B]()))((a, fbs) => map2(f(a), fbs)(_ :: _))