Related
In one of his videos (concerning Scala's lazy evaluation, namely lazy keyword), Martin Odersky shows the following implementation of cons operation used to construct a Stream:
def cons[T](hd: T, tl: => Stream[T]) = new Stream[T] {
def head = hd
lazy val tail = tl
...
}
So tail operation is written concisely using lazy evaluation feature of the language.
But in reality (in Scala 2.11.7), the implementation of tail is a bit less elegant:
#volatile private[this] var tlVal: Stream[A] = _
#volatile private[this] var tlGen = tl _
def tailDefined: Boolean = tlGen eq null
override def tail: Stream[A] = {
if (!tailDefined)
synchronized {
if (!tailDefined) {
tlVal = tlGen()
tlGen = null
}
}
tlVal
}
Double-checked locking and two volatile fields: that's roughly how you would implement a thread-safe lazy computation in Java.
So the questions are:
Doesn't lazy keyword of Scala provide any 'evaluated maximum once' guarantee in a multi-threaded case?
Is the pattern used in real tail implementation an idiomatic way to do a thread-safe lazy evaluation in Scala?
Doesn't lazy keyword of Scala provide any 'evaluated maximum once'
guarantee in a multi-threaded case?
Yes, it does, as others have stated.
Is the pattern used in real tail implementation an idiomatic way to do
a thread-safe lazy evaluation in Scala?
Edit:
I think I have the actual answer as to why not lazy val. Stream has public facing API methods such as hasDefinitionSize inherited from TraversableOnce. In order to know if a Stream has a finite size not, we need a way of checking without materializing the underlying Stream tail. Since lazy val doesn't actually expose the underlying bit, we can't do that.
This is backed by SI-1220
To strengthen this point, #Jasper-M points out that the new LazyList api in strawman (Scala 2.13 collection makeover) no longer has this issue, since the entire collection hierarchy has been reworked and there are no longer such concerns.
Performance related concerns
I would say "it depends" on which angle you're looking at this problem. From a LOB point of view, I'd say definitely go with lazy val for conciseness and clarity of implementation. But, if you look at it from the point of view of a Scala collections library author, things start to look differently. Think of it this way, you're creating a library which will be potentially be used by many people and ran on many machines across the world. This means that you should be thinking of the memory overhead of each structure, especially if you're creating such an essential data structure yourself.
I say this because when you use lazy val, by design you generate an additional Boolean field which flags if the value has been initialized, and I am assuming this is what the library authors were aiming to avoid. The size of a Boolean on the JVM is of course VM dependent, by even a byte is something to consider, especially when people are generating large Streams of data. Again, this is definitely not something I would usually consider and is definitely a micro optimization towards memory usage.
The reason I think performance is one of the key points here is SI-7266 which fixes a memory leak in Stream. Note how it is of importance to track the byte code to make sure no extra values are retained inside the generated class.
The difference in the implementation is that the definition of tail being initialized or not is a method implementation which checks the generator:
def tailDefined: Boolean = tlGen eq null
Instead of a field on the class.
Scala lazy values are evaluated only once in multi-threaded cases. This is because the evaluation of lazy members is actually wrapped in a synchronized block in the generated code.
Lets take a look at the simple claas,
class LazyTest {
lazy val x = 5
}
Now, lets compile this with scalac,
scalac -Xprint:all LazyTest.scala
This will result in,
package <empty> {
class LazyTest extends Object {
final <synthetic> lazy private[this] var x: Int = _;
#volatile private[this] var bitmap$0: Boolean = _;
private def x$lzycompute(): Int = {
LazyTest.this.synchronized(if (LazyTest.this.bitmap$0.unary_!())
{
LazyTest.this.x = (5: Int);
LazyTest.this.bitmap$0 = true
});
LazyTest.this.x
};
<stable> <accessor> lazy def x(): Int = if (LazyTest.this.bitmap$0.unary_!())
LazyTest.this.x$lzycompute()
else
LazyTest.this.x;
def <init>(): LazyTest = {
LazyTest.super.<init>();
()
}
}
}
You should be able to see... that the lazy evaluation is thread-safe. And you will also see some similarity to that "less elegant" implementation in Scala 2.11.7
You can also experiment with tests similar to following,
import scala.concurrent.Future
import scala.concurrent.ExecutionContext.Implicits.global
case class A(i: Int) {
lazy val j = {
println("calculating j")
i + 1
}
}
def checkLazyInMultiThread(): Unit = {
val a = A(6)
val futuresList = Range(1, 20).toList.map(i => Future{
println(s"Future $i :: ${a.j}")
})
Future.sequence(futuresList).onComplete(_ => println("completed"))
}
checkLazyInMultiThread()
Now, the implementation in standard library avoids using lazy because they are able to provide a more efficient solution than this generic lazy translation.
You are correct, lazy vals use locking precisely to guard against double evaluation when accessed at the same time by two threads. Future developments, furthermore, will give the same guarantees without locking.
What is idiomatic, in my humble opinion, is a highly debatable subject when it comes to a language that, by design, allows for a wide range of different idioms to be adopted. In general, however, application code tends to be considered idiomatic when going more into the direction of pure functional programming, as it gives a series of interesting advantages in terms of ease of testing and reasoning that would make sense to give up only in case of serious concerns. This concern can be one of performance, which is why the current implementation of the Scala Collection API, while exposing in most cases a functional interface, makes heavy use (internally and in restricted scopes) of vars, while loops and established patterns from imperative programming (as the one you highlighted in your question).
Something that comes up a fair amount when dealing with heterogeneous data is the need to partially change simple objects that hold data. For instance, you might want to add, drop, or rename a property, or concatenate two objects. This is easy enough in dynamic languages, but I'm wondering if there are any clever solutions proposed by static languages?
To fix ideas, are there any languages that enable, perhaps through some sort of static mixin syntax, something like this (C#):
var hello = new { Hello = "Hello" };
var world = new { World = "World" };
var helloWorld = hello + world;
Console.WriteLine(helloWorld.ToString());
//outputs {Hello = Hello, World = World}
This certainly seems possible, since no runtime information is used. Are there static languages that have this capability?
Added:
A limited version of what I'm considering is F#'s copy-and-update record expression:
let myRecord3 = { myRecord2 with Y = 100; Z = 2 }
What you're describing is known in programming language research as record concatenation. There has been some work on static type systems for record concatenation, mostly in the context of automatic type inference a la Haskell or ML. To the best of my knowledge it has not yet made an impact on any mainstream programming languages.
In some dynamic languages I have seen this kind of syntax:
myValue = if (this.IsValidObject)
{
UpdateGraph();
UpdateCount();
this.Name;
}
else
{
Debug.Log (Exceptions.UninitializedObject);
3;
}
Basically being able to return the last statement in a branch as the return value for a variable, not necessarily only for method returns, but they could be achieved as well.
What's the name of this feature?
Can this also be achieved in staticly typed languages such as C#? I know C# has ternary operator, but I mean using if statements, switch statements as shown above.
It is called "conditional-branches-are-expressions" or "death to the statement/expression divide".
See Conditional If Expressions:
Many languages support if expressions, which are similar to if statements, but return a value as a result. Thus, they are true expressions (which evaluate to a value), not statements (which just perform an action).
That is, if (expr) { ... } is an expression (could possible be an expression or a statement depending upon context) in the language grammar just as ?: is an expression in languages like C, C# or Java.
This form is common in functional programming languages (which eschew side-effects) -- however, it is not "functional programming" per se and exists in other language that accept/allow a "functional like syntax" while still utilizing heavy side-effects and other paradigms (e.g. Ruby).
Some languages like Perl allow this behavior to be simulated. That is, $x = eval { if (true) { "hello world!" } else { "goodbye" } }; print $x will display "hello world!" because the eval expression evaluates to the last value evaluated inside even though the if grammar production itself is not an expression. ($x = if ... is a syntax error in Perl).
Happy coding.
To answer your other question:
Can this also be achieved in staticly typed languages such as C#?
Is it a thing the language supports? No. Can it be achieved? Kind of.
C# --like C++, Java, and all that ilk-- has expressions and statements. Statements, like if-then and switch-case, don't return values and there fore can't be used as expressions. Also, as a slight aside, your example assigns myValue to either a string or an integer, which C# can't do because it is strongly typed. You'd either have to use object myValue and then accept the casting and boxing costs, use var myValue (which is still static typed, just inferred), or some other bizarre cleverness.
Anyway, so if if-then is a statement, how do you do that in C#? You'd have to build a method to accomplish the goal of if-then-else. You could use a static method as an extension to bools, to model the Smalltalk way of doing it:
public static T IfTrue(this bool value, Action doThen, Action doElse )
{
if(value)
return doThen();
else
return doElse();
}
To use this, you'd do something like
var myVal = (6 < 7).IfTrue(() => return "Less than", () => return "Greater than");
Disclaimer: I tested none of that, so it may not quite work due to typos, but I think the principle is correct.
The new IfTrue() function checks the boolean it is attached to and executes one of two delegates passed into it. They must have the same return type, and neither accepts arguments (use closures, so it won't matter).
Now, should you do that? No, almost certainly not. Its not the proper C# way of doing things so it's confusing, and its much less efficient than using an if-then. You're trading off something like 1 IL instruction for a complex mess of classes and method calls that .NET will build behind the scenes to support that.
It is a ternary conditional.
In C you can use, for example:
printf("Debug? %s\n", debug?"yes":"no");
Edited:
A compound statement list can be evaluated as a expression in C. The last statement should be a expression and the whole compound statement surrounded by braces.
For example:
#include <stdio.h>
int main(void)
{
int a=0, b=1;
a=({
printf("testing compound statement\n");
if(b==a)
printf("equals\n");
b+1;
});
printf("a=%d\n", a);
return 0;
}
So the name of the characteristic you are doing is assigning to a (local) variable a compound statement. Now I think this helps you a little bit more. For more, please visit this source:
http://www.chemie.fu-berlin.de/chemnet/use/info/gcc/gcc_8.html
Take care,
Beco.
PS. This example makes more sense in the context of your question:
a=({
int c;
if(b==a)
c=b+1;
else
c=a-1;
c;
});
In addition to returning the value of the last expression in a branch, it's likely (depending on the language) that myValue is being assigned to an anonymous function -- or in Smalltalk / Ruby, code blocks:
A block of code (an anonymous function) can be expressed as a literal value (which is an object, since all values are objects.)
In this case, since myValue is actually pointing to a function that gets invoked only when myValue is used, the language probably implements them as closures, which are originally a feature of functional languages.
Because closures are first-class functions with free variables, closures exist in C#. However, the implicit return does not occur; in C# they're simply anonymous delegates! Consider:
Func<Object> myValue = delegate()
{
if (this.IsValidObject)
{
UpdateGraph();
UpdateCount();
return this.Name;
}
else
{
Debug.Log (Exceptions.UninitializedObject);
return 3;
}
};
This can also be done in C# using lambda expressions:
Func<Object> myValue = () =>
{
if (this.IsValidObject) { ... }
else { ... }
};
I realize your question is asking about the implicit return value, but I am trying to illustrate that there is more than just "conditional branches are expressions" going on here.
Can this also be achieved in staticly
typed languages?
Sure, the types of the involved expressions can be statically and strictly checked. There seems to be nothing dependent on dynamic typing in the "if-as-expression" approach.
For example, Haskell--a strict statically typed language with a rich system of types:
$ ghci
Prelude> let x = if True then "a" else "b" in x
"a"
(the example expression could be simpler, I just wanted to reflect the assignment from your question, but the expression to demonstrate the feature could be simlpler:
Prelude> if True then "a" else "b"
"a"
.)
I don't know if this is possible, but are there any languages where you can use a dot operator on a function per se. I'll give an example.
function blah returns type2
type 2 looks like this
{
data
number
}
when I call blah are there any languages that support blah.number, so that when it makes the function call and gets the type2, it then grabs number and returns that. I'm sorry if this is an obvious answer, but I couldn't even think of a good way to word it to google it.
I just ran into a situation that would be convienient to have that, rather then make an intermediate variable you just make sure you return the type.
I know that I could add a "get" function that would get the specific number variable from that type, but that's an additional function someone would have to add so I am excluding that as a option (as I can just return the type and access using a variable there isn't really a dire need for a new function).
EDIT: I feel like an idiot.....
EDIT # 2: For some reason I had it in my head that you couldn't do dot operations on functions, (I don't care about the parentheses I was just trying to give an example)
Edit # 3: Is there a name for this or is it still just a dot operation?
Well this works in C if the function returns a struct like this:
struct retval {
char * data;
int number;
};
retval foo() {
// do something and then return an instance of retval
}
// call
int a = foo().number;
I would like to know if there is any language that does not support something like this.
About Edit #3
The name would generally be member access, since all you do is to access a member of the return value. This could differ across languages though.
In most languages you can do Blah().Member ... the typing of a pair of parentheses won't kill you, will it? These languages include C, C++, Java, C# etc.
Yep, to the best of my knowledge, most modern languages (if not most languages in general) support this.
Maybe I misunderstand you, but in most languages, you can already do that.
in java for example, if you have a function get_foo() returning an object of type foo, and foo is defined as
Class Foo{
public int bar;
public double baz;
}
you can do get_foo().bar returning bar
Any language that allows a function to return an object/struct will support that... And languages like Ruby (where the () are optional) will make it exactly like you tiped (blah.number instead of blah().number).
Another way of avoiding the parentheses is using a property or an equivalent idiom... So C#, VB.NET and Python would also allow that.
If you want to make a new function out of an existing one, it's possible with lambda expressions. In C#, for example, it'd be var fooblah = (x => foo(x).blah); Obviously, if there's an overloading available in the language, you can't do it without giving a list of arguments.
Er...you mean, like a returning a class or a struct?
In C#
private class Blah
{
public string Data {get; set;}
public int Number {get; set;}
}
public Blah DoSomething()
{
return new Blah{Data="Data",Number=1};
}
Every so often when programmers are complaining about null errors/exceptions someone asks what we do without null.
I have some basic idea of the coolness of option types, but I don't have the knowledge or languages skill to best express it. What is a great explanation of the following written in a way approachable to the average programmer that we could point that person towards?
The undesirability of having references/pointers be nullable by default
How option types work including strategies to ease checking null cases such as
pattern matching and
monadic comprehensions
Alternative solution such as message eating nil
(other aspects I missed)
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:
the variable is uninitialized. This should, ideally, never happen. A variable shouldn't exist unless it is initialized.
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?
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.
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).
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).
The undesirability of having having references/pointers be nullable by default.
I don't think this is the main issue with nulls, the main issue with nulls is that they can mean two things:
The reference/pointer is uninitialized: the problem here is the same as mutability in general. For one, it makes it more difficult to analyze your code.
The variable being null actually means something: this is the case which Option types actually formalize.
Languages which support Option types typically also forbid or discourage the use of uninitialized variables as well.
How option types work including strategies to ease checking null cases such as pattern matching.
In order to be effective, Option types need to be supported directly in the language. Otherwise it takes a lot of boiler-plate code to simulate them. Pattern-matching and type-inference are two keys language features making Option types easy to work with. For example:
In F#:
//first we create the option list, and then filter out all None Option types and
//map all Some Option types to their values. See how type-inference shines.
let optionList = [Some(1); Some(2); None; Some(3); None]
optionList |> List.choose id //evaluates to [1;2;3]
//here is a simple pattern-matching example
//which prints "1;2;None;3;None;".
//notice how value is extracted from op during the match
optionList
|> List.iter (function Some(value) -> printf "%i;" value | None -> printf "None;")
However, in a language like Java without direct support for Option types, we'd have something like:
//here we perform the same filter/map operation as in the F# example.
List<Option<Integer>> optionList = Arrays.asList(new Some<Integer>(1),new Some<Integer>(2),new None<Integer>(),new Some<Integer>(3),new None<Integer>());
List<Integer> filteredList = new ArrayList<Integer>();
for(Option<Integer> op : list)
if(op instanceof Some)
filteredList.add(((Some<Integer>)op).getValue());
Alternative solution such as message eating nil
Objective-C's "message eating nil" is not so much a solution as an attempt to lighten the head-ache of null checking. Basically, instead of throwing a runtime exception when trying to invoke a method on a null object, the expression instead evaluates to null itself. Suspending disbelief, it's as if each instance method begins with if (this == null) return null;. But then there is information loss: you don't know whether the method returned null because it is valid return value, or because the object is actually null. It's a lot like exception swallowing, and doesn't make any progress addressing the issues with null outlined before.
Assembly brought us addresses also known as untyped pointers. C mapped them directly as typed pointers but introduced Algol's null as a unique pointer value, compatible with all typed pointers. The big issue with null in C is that since every pointer can be null, one never can use a pointer safely without a manual check.
In higher-level languages, having null is awkward since it really conveys two distinct notions:
Telling that something is undefined.
Telling that something is optional.
Having undefined variables is pretty much useless, and yields to undefined behavior whenever they occur. I suppose everybody will agree that having things undefined should be avoided at all costs.
The second case is optionality and is best provided explicitly, for instance with an option type.
Let's say we're in a transport company and we need to create an application to help create a schedule for our drivers. For each driver, we store a few informations such as: the driving licences they have and the phone number to call in case of emergency.
In C we could have:
struct PhoneNumber { ... };
struct MotorbikeLicence { ... };
struct CarLicence { ... };
struct TruckLicence { ... };
struct Driver {
char name[32]; /* Null terminated */
struct PhoneNumber * emergency_phone_number;
struct MotorbikeLicence * motorbike_licence;
struct CarLicence * car_licence;
struct TruckLicence * truck_licence;
};
As you observe, in any processing over our list of drivers we'll have to check for null pointers. The compiler won't help you, the safety of the program relies on your shoulders.
In OCaml, the same code would look like this:
type phone_number = { ... }
type motorbike_licence = { ... }
type car_licence = { ... }
type truck_licence = { ... }
type driver = {
name: string;
emergency_phone_number: phone_number option;
motorbike_licence: motorbike_licence option;
car_licence: car_licence option;
truck_licence: truck_licence option;
}
Let's now say that we want to print the names of all the drivers along with their truck licence numbers.
In C:
#include <stdio.h>
void print_driver_with_truck_licence_number(struct Driver * driver) {
/* Check may be redundant but better be safe than sorry */
if (driver != NULL) {
printf("driver %s has ", driver->name);
if (driver->truck_licence != NULL) {
printf("truck licence %04d-%04d-%08d\n",
driver->truck_licence->area_code
driver->truck_licence->year
driver->truck_licence->num_in_year);
} else {
printf("no truck licence\n");
}
}
}
void print_drivers_with_truck_licence_numbers(struct Driver ** drivers, int nb) {
if (drivers != NULL && nb >= 0) {
int i;
for (i = 0; i < nb; ++i) {
struct Driver * driver = drivers[i];
if (driver) {
print_driver_with_truck_licence_number(driver);
} else {
/* Huh ? We got a null inside the array, meaning it probably got
corrupt somehow, what do we do ? Ignore ? Assert ? */
}
}
} else {
/* Caller provided us with erroneous input, what do we do ?
Ignore ? Assert ? */
}
}
In OCaml that would be:
open Printf
(* Here we are guaranteed to have a driver instance *)
let print_driver_with_truck_licence_number driver =
printf "driver %s has " driver.name;
match driver.truck_licence with
| None ->
printf "no truck licence\n"
| Some licence ->
(* Here we are guaranteed to have a licence *)
printf "truck licence %04d-%04d-%08d\n"
licence.area_code
licence.year
licence.num_in_year
(* Here we are guaranteed to have a valid list of drivers *)
let print_drivers_with_truck_licence_numbers drivers =
List.iter print_driver_with_truck_licence_number drivers
As you can see in this trivial example, there is nothing complicated in the safe version:
It's terser.
You get much better guarantees and no null check is required at all.
The compiler ensured that you correctly dealt with the option
Whereas in C, you could just have forgotten a null check and boom...
Note : these code samples where not compiled, but I hope you got the ideas.
Microsoft Research has a intersting project called
Spec#
It is a C# extension with not-null type and some mechanism to check your objects against not being null, although, IMHO, applying the design by contract principle may be more appropriate and more helpful for many troublesome situations caused by null references.
Robert Nystrom offers a nice article here:
http://journal.stuffwithstuff.com/2010/08/23/void-null-maybe-and-nothing/
describing his thought process when adding support for absence and failure to his Magpie programming language.
Coming from .NET background, I always thought null had a point, its useful. Until I came to know of structs and how easy it was working with them avoiding a lot of boilerplate code. Tony Hoare speaking at QCon London in 2009, apologized for inventing the null reference. To quote him:
I call it my billion-dollar mistake. It was the invention of the null
reference in 1965. At that time, I was designing the first
comprehensive type system for references in an object oriented
language (ALGOL W). My goal was to ensure that all use of references
should be absolutely safe, with checking performed automatically by
the compiler. But I couldn't resist the temptation to put in a null
reference, simply because it was so easy to implement. This has led to
innumerable errors, vulnerabilities, and system crashes, which have
probably caused a billion dollars of pain and damage in the last forty
years. In recent years, a number of program analysers like PREfix and
PREfast in Microsoft have been used to check references, and give
warnings if there is a risk they may be non-null. More recent
programming languages like Spec# have introduced declarations for
non-null references. This is the solution, which I rejected in 1965.
See this question too at programmers
I've always looked at Null (or nil) as being the absence of a value.
Sometimes you want this, sometimes you don't. It depends on the domain you are working with. If the absence is meaningful: no middle name, then your application can act accordingly. On the other hand if the null value should not be there: The first name is null, then the developer gets the proverbial 2 a.m. phone call.
I've also seen code overloaded and over-complicated with checks for null. To me this means one of two things:
a) a bug higher up in the application tree
b) bad/incomplete design
On the positive side - Null is probably one of the more useful notions for checking if something is absent, and languages without the concept of null will endup over-complicating things when it's time to do data validation. In this case, if a new variable is not initialized, said languagues will usually set variables to an empty string, 0, or an empty collection. However, if an empty string or 0 or empty collection are valid values for your application -- then you have a problem.
Sometimes this circumvented by inventing special/weird values for fields to represent an uninitialized state. But then what happens when the special value is entered by a well-intentioned user? And let's not get into the mess this will make of data validation routines.
If the language supported the null concept all the concerns would vanish.
Vector languages can sometimes get away with not having a null.
The empty vector serves as a typed null in this case.