Introduction to monoids for object-oriented programmers.

This article is part of a larger series about monoids, semigroups, and related concepts. In this article, you'll learn what a monoid is, and what distinguishes it from a semigroup.

Monoids are a subset of semigroups.

Monoids form a subset of semigroups. The rules that govern monoids are stricter than those for semigroups, so you'd be forgiven for thinking that it would make sense to start with semigroups, and then build upon that definition to learn about monoids. From a strictly hierarchical perspective, that would make sense, but I think that monoids are more intuitive. When you see the most obvious monoid example, you'll see that they cover operations from everyday life. It's easy to think of examples of monoids, while you have to think harder to find some good semigroup examples. That's the reason I think that you should start with monoids.

Monoid laws

What do addition (40 + 2) and multiplication (6 * 7) have in common?

They're both

  • associative
  • binary operations
  • with a neutral element.
That's all it takes to form a monoid. Associativity and the existence of a neutral element is sometimes referred to as the monoid laws. It's worth noting that a monoid is a combination of a data type (or set) and an operation. It's not a data type in itself, but rather a function (or method) that operates on that data type. For example, addition and multiplication are two different monoids that both work on numbers.

Binary operation

Let's start with the most basic property. That an operation is binary means that it works on two values. Perhaps you mostly associate the word binary with binary numbers, such as 101010, but the word originates from Latin and means something like of two. Astronomers talk about binary stars, but the word is dominantly used in computing context: apart from binary numbers, you may also have heard about binary trees. When talking about binary operations, it's implied that both input values are of the same type, and that the return type is the same as the input type. In other words, a C# method like this is a proper binary operation:

public static Foo Op(Foo x, Foo y)

Sometimes, if Op is an instance method on the Foo class, it can also look like this:

public Foo Op (Foo foo)

On the other hand, this isn't a binary operation:

public static Baz Op(Foo f, Bar b)

Although it takes two input arguments, they're of different types, and the return type is a third type.

Since all involved arguments and return values are of the same type, a binary operation exhibits what Eric Evans in Domain-Driven Design calls Closure of Operations.


In order to form a monoid, the binary operation must be associative. This simply means that the order of evaluation doesn't matter. For example, for addition, it means that

(2 + 3) + 4 = 2 + (3 + 4) = 2 + 3 + 4 = 9

Likewise, for multiplication

(2 * 3) * 4 = 2 * (3 * 4) = 2 * 3 * 4 = 24

Expressed as the above Op instance method, associativity would require that areEqual is true in the following code:

var areEqual = foo1.Op(foo2).Op(foo3) == foo1.Op(foo2.Op(foo3));

On the left-hand side, foo1.Op(foo2) is evaluated first, and the result then evaluated with foo3. On the right-hand side, foo2.Op(foo3) is evaluated first, and then used as an input argument to foo1.Op. Since the left-hand side and the right-hand side are compared with the == operator, associativity requires that areEqual is true.

In C#, if you have a custom monoid like Foo, you'll have to override Equals and implement the == operator in order to make all of this work.

Neutral element

The third rule for monoids is that there must exist a neutral value. In the normal jargon, this is called the identity element, and this is what I'm going to be calling it from now on. I only wanted to introduce the concept using a friendlier name.

The identity element is a value that doesn't 'do' anything. For addition, for example, it's zero, because adding zero to a value doesn't change the value:

0 + 42 = 42 + 0 = 42

As an easy exercise, see if you can figure out the identity value for multiplication.

As implied by the above sum, the identity element must act neutrally both when applied to the left-hand side and the right-hand side of another value. For our Foo objects, it could look like this:

var hasIdentity =
    Foo.Identity.Op(foo) == foo.Op(Foo.Identity) &&
    foo.Op(Foo.Identity) == foo;

Here, Foo.Identity is a static read-only field of the type Foo.


There are plenty of examples of monoids. The most obvious examples are addition and multiplication, but there are more. Depending on your perspective, you could even say that there's more than one addition monoid, because there's one for integers, one for real numbers, and so on. The same can be said for multiplication.

There are also two monoids over boolean values called all and any. If you have a binary operation over boolean values called all, how do you think it works? What would be the identity value? What about any?

I'll leave you to ponder (or look up) all and any, and instead, in the next articles, show you some slightly more interesting monoids.

In essence, if you have a data type that 'behaves like a number', you can probably make it a monoid. Addition is often the best candidate, because it doesn't mess with the dimensions of what you're keeping track of. As an example, the .NET Base Class Library defines a TimeSpan structure with an Add method. It also comes with a == operator. On the other hand, there's no Multiply method for TimeSpan, because what does it mean to multiply two durations? What would the dimension be? Time squared?


A monoid (not to be confused with a monad) is a binary operation that satisfies the two monoid laws: that the operation is associative, and that an identity element exists. Addition and multiplication are prime examples, but several others exist.

(By the way, the identity element for multiplication is one (1), all is boolean and, and any is boolean or.)

Next: Strings, lists, and sequences as a monoid.


Great series! I'm a big fan of intuitive abstractions and composition. Can't wait for the remaining parts.

I first heard of the closure property in SICP, where it's mentioned that:

In general, an operation for combining data objects satisfies the closure property if the results of combining things with that operation can themselves be combined using the same operation.
Also, a reference to the algebraic origin of this concept is made in the foot note for this sentence:
The use of the word "closure" here comes from abstract algebra, where a set of elements is said to be closed under an operation if applying the operation to elements in the set produces an element that is again an element of the set.

It's interesting to see this concept come up over and over, although it hasn't been widely socialized as a formal construct to software composition.

2017-10-06 15:38 UTC

This looks like it's going to be a fantastic series - I'm really looking forwards to reading the rest!

So, as we are talking about forming a vocabulary and reducing ambiguity, I have a question about the use of the word closure, which I think has more than one common meaning in this context.

In Eric Evans' "Closure of Operations", closure refers to the fact that the operation is "closed" over it's set of possible values - in other words, the set is closed under the operation.

Closure is also used to describe a function with a bound value (as in the poor man's object").

These are two separate concepts as far as I am aware. Also, I suspect that the latter meaning is likely more well known to C# devs reading this series, especially ReSharper users who have come across it's "implicitly captured closure" detection. So, if I am correct, do you think it is worth making this distinction clear to avoid potential confusion?

2017-10-18 07:30 UTC

Sean, thank you for writing. That's a great observation, and one that I frankly admit that I hadn't made myself. In an ideal world, one of those concepts would have a different name, so that we'd be able to distinguish them from each other.

In my experience, I find that the context in which I'm using those words tend to make the usage unambiguous, but I think that you have a good point that some readers may be more familiar with closure as a captured outer value, rather than the concept of an operation where the domain and the codomain is the same. I'll see if I can make this clearer when I revisit Evans' example.

2017-10-18 12:02 UTC

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Friday, 06 October 2017 07:38:00 UTC


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