Best explanation for languages without null

I think the succinct summary of why null is undesirable is that meaningless states should not be representable.

Suppose I'm modeling a door. It can be in one of three states: open, shut but unlocked, and shut and locked. Now I could model it along the lines of

class Door
    private bool isShut
    private bool isLocked

and it is clear how to map my three states into these two boolean variables. But this leaves a fourth, undesired state available: isShut==false && isLocked==true. Because the types I have selected as my representation admit this state, I must expend mental effort to ensure that the class never gets into this state (perhaps by explicitly coding an invariant). In contrast, if I were using a language with algebraic data types or checked enumerations that lets me define

type DoorState =
    | Open | ShutAndUnlocked | ShutAndLocked

then I could define

class Door
    private DoorState state

and there are no more worries. The type system will ensure that there are only three possible states for an instance of class Door to be in. This is what type systems are good at - explicitly ruling out a whole class of errors at compile-time.

The problem with null is that every reference type gets this extra state in its space that is typically undesired. A string variable could be any sequence of characters, or it could be this crazy extra null value that doesn't map into my problem domain. A Triangle object has three Points, which themselves have X and Y values, but unfortunately the Points or the Triangle itself might be this crazy null value that is meaningless to the graphing domain I'm working in. Etc.

When you do intend to model a possibly-non-existent value, then you should opt into it explicitly. If the way I intend to model people is that every Person has a FirstName and a LastName, but only some people have MiddleNames, then I would like to say something like

class Person
    private string FirstName
    private Option<string> MiddleName
    private string LastName

where string here is assumed to be a non-nullable type. Then there are no tricky invariants to establish and no unexpected NullReferenceExceptions when trying to compute the length of someone's name. The type system ensures that any code dealing with the MiddleName accounts for the possibility of it being None, whereas any code dealing with the FirstName can safely assume there is a value there.

So for example, using the type above, we could author this silly function:

let TotalNumCharsInPersonsName(p:Person) =
    let middleLen = match p.MiddleName with
                    | None -> 0
                    | Some(s) -> s.Length
    p.FirstName.Length + middleLen + p.LastName.Length

with no worries. In contrast, in a language with nullable references for types like string, then assuming

class Person
    private string FirstName
    private string MiddleName
    private string LastName

you end up authoring stuff like

let TotalNumCharsInPersonsName(p:Person) =
    p.FirstName.Length + p.MiddleName.Length + p.LastName.Length

which blows up if the incoming Person object does not have the invariant of everything being non-null, or

let TotalNumCharsInPersonsName(p:Person) =
    (if p.FirstName=null then 0 else p.FirstName.Length)
    + (if p.MiddleName=null then 0 else p.MiddleName.Length)
    + (if p.LastName=null then 0 else p.LastName.Length)

or maybe

let TotalNumCharsInPersonsName(p:Person) =
    p.FirstName.Length
    + (if p.MiddleName=null then 0 else p.MiddleName.Length)
    + p.LastName.Length

assuming that p ensures first/last are there but middle can be null, or maybe you do checks that throw different types of exceptions, or who knows what. All these crazy implementation choices and things to think about crop up because there's this stupid representable-value that you don't want or need.

Null typically adds needless complexity. Complexity is the enemy of all software, and you should strive to reduce complexity whenever reasonable.

(Note well that there is more complexity to even these simple examples. Even if a FirstName cannot be null, a string can represent "" (the empty string), which is probably also not a person name that we intend to model. As such, even with non-nullable strings, it still might be the case that we are "representing meaningless values". Again, you could choose to battle this either via invariants and conditional code at runtime, or by using the type system (e.g. to have a NonEmptyString type). The latter is perhaps ill-advised ("good" types are often "closed" over a set of common operations, and e.g. NonEmptyString is not closed over .SubString(0,0)), but it demonstrates more points in the design space. At the end of the day, in any given type system, there is some complexity it will be very good at getting rid of, and other complexity that is just intrinsically harder to get rid of. The key for this topic is that in nearly every type system, the change from "nullable references by default" to "non-nullable references by default" is nearly always a simple change that makes the type system a great deal better at battling complexity and ruling out certain types of errors and meaningless states. So it is pretty crazy that so many languages keep repeating this error again and again.)

The nice thing about option types isn't that they're optional. It is that all other types aren't.

Sometimes, we need to be able to represent a kind of "null" state. Sometimes we have to represent a "no value" option as well as the other possible values a variable may take. So a language that flat out disallows this is going to be a bit crippled.

But often, we don't need it, and allowing such a "null" state only leads to ambiguity and confusion: every time I access a reference type variable in .NET, I have to consider that it might be null.

Often, it will never actually be null, because the programmer structures the code so that it can never happen. But the compiler can't verify that, and every single time you see it, you have to ask yourself "can this be null? Do I need to check for null here?"

Ideally, in the many cases where null doesn't make sense, it shouldn't be allowed.

That's tricky to achieve in .NET, where nearly everything can be null. You have to rely on the author of the code you're calling to be 100% disciplined and consistent and have clearly documented what can and cannot be null, or you have to be paranoid and check everything.

However, if types aren't nullable by default, then you don't need to check whether or not they're null. You know they can never be null, because the compiler/type checker enforces that for you.

And then we just need a back door for the rare cases where we do need to handle a null state. Then an "option" type can be used. Then we allow null in the cases where we've made a conscious decision that we need to be able to represent the "no value" case, and in every other case, we know that the value will never be null.

As others have mentioned, in C# or Java for example, null can mean one of two things:

1. the variable is uninitialized. This should, ideally, never happen. A variable shouldn't exist unless it is initialized.
2. the variable contains some "optional" data: it needs to be able to represent the case where there is no data. This is sometimes necessary. Perhaps you're trying to find an object in a list, and you don't know in advance whether or not it's there. Then we need to be able to represent that "no object was found".

The second meaning has to be preserved, but the first one should be eliminated entirely. And even the second meaning should not be the default. It's something we can opt in to if and when we need it. But when we don't need something to be optional, we want the type checker to guarantee that it will never be null.

All of the answers so far focus on why null is a bad thing, and how it's kinda handy if a language can guarantee that certain values will never be null.

They then go on to suggest that it would be a pretty neat idea if you enforce non-nullability for all values, which can be done if you add a concept like Option or Maybe to represent types that may not always have a defined value. This is the approach taken by Haskell.

It's all good stuff! But it doesn't preclude the use of explicitly nullable / non-null types to achieve the same effect. Why, then, is Option still a good thing? After all, Scala supports nullable values (is has to, so it can work with Java libraries) but supports Options as well.

Q. So what are the benefits beyond being able to remove nulls from a language entirely?

A. Composition

If you make a naive translation from null-aware code

def fullNameLength(p:Person) = {
  val middleLen =
    if (null == p.middleName)
      p.middleName.length
    else
      0
  p.firstName.length + middleLen + p.lastName.length
}

to option-aware code

def fullNameLength(p:Person) = {
  val middleLen = p.middleName match {
    case Some(x) => x.length
    case _ => 0
  }
  p.firstName.length + middleLen + p.lastName.length
}

there's not much difference! But it's also a terrible way to use Options... This approach is much cleaner:

def fullNameLength(p:Person) = {
  val middleLen = p.middleName map {_.length} getOrElse 0
  p.firstName.length + middleLen + p.lastName.length
}

Or even:

def fullNameLength(p:Person) =       
  p.firstName.length +
  p.middleName.map{length}.getOrElse(0) +
  p.lastName.length

When you start dealing with List of Options, it gets even better. Imagine that the List people is itself optional:

people flatMap(_ find (_.firstName == "joe")) map (fullNameLength)

How does this work?

//convert an Option[List[Person]] to an Option[S]
//where the function f takes a List[Person] and returns an S
people map f

//find a person named "Joe" in a List[Person].
//returns Some[Person], or None if "Joe" isn't in the list
validPeopleList find (_.firstName == "joe")

//returns None if people is None
//Some(None) if people is valid but doesn't contain Joe
//Some[Some[Person]] if Joe is found
people map (_ find (_.firstName == "joe")) 

//flatten it to return None if people is None or Joe isn't found
//Some[Person] if Joe is found
people flatMap (_ find (_.firstName == "joe")) 

//return Some(length) if the list isn't None and Joe is found
//otherwise return None
people flatMap (_ find (_.firstName == "joe")) map (fullNameLength)

The corresponding code with null checks (or even elvis ?: operators) would be painfully long. The real trick here is the flatMap operation, which allows for the nested comprehension of Options and collections in a way that nullable values can never achieve.

Since people seem to be missing it: null is ambiguous.

Alice's date-of-birth is null. What does it mean?

Bob's date-of-death is null. What does that mean?

A "reasonable" interpretation might be that Alice's date-of-birth exists but is unknown, whereas Bob's date-of-death does not exist (Bob is still alive). But why did we get to different answers?

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Another problem: null is an edge case.

• Is null = null?
• Is nan = nan?
• Is inf = inf?
• Is +0 = -0?
• Is +0/0 = -0/0?

The answers are usually "yes", "no", "yes", "yes", "no", "yes" respectively. Crazy "mathematicians" call NaN "nullity" and say it compares equal to itself. SQL treats nulls as not equal to anything (so they behave like NaNs). One wonders what happens when you try to store ±∞, ±0, and NaNs into the same database column (there are 2⁵³ NaNs, half of which are "negative").

To make matters worse, databases differ in how they treat NULL, and most of them aren't consistent (see NULL Handling in SQLite for an overview). It's pretty horrible.

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And now for the obligatory story:

I recently designed a (sqlite3) database table with five columns a NOT NULL, b, id_a, id_b NOT NULL, timestamp. Because it's a generic schema designed to solve a generic problem for fairly arbitrary apps, there are two uniqueness constraints:

UNIQUE(a, b, id_a)
UNIQUE(a, b, id_b)

id_a only exists for compatibility with an existing app design (partly because I haven't come up with a better solution), and is not used in the new app. Because of the way NULL works in SQL, I can insert (1, 2, NULL, 3, t) and (1, 2, NULL, 4, t) and not violate the first uniqueness constraint (because (1, 2, NULL) != (1, 2, NULL)).

This works specifically because of how NULL works in a uniqueness constraint on most databases (presumably so it's easier to model "real-world" situations, e.g. no two people can have the same Social Security Number, but not all people have one).

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FWIW, without first invoking undefined behaviour, C++ references cannot "point to" null, and it's not possible to construct a class with uninitialized reference member variables (if an exception is thrown, construction fails).

Sidenote: Occasionally you might want mutually-exclusive pointers (i.e. only one of them can be non-NULL), e.g. in a hypothetical iOS type DialogState = NotShown | ShowingActionSheet UIActionSheet | ShowingAlertView UIAlertView | Dismissed. Instead, I'm forced to do stuff like assert((bool)actionSheet + (bool)alertView == 1).