I am trying to get a class, which combines list, set and map in Kotlin. I wished to write isScalar function, which should return true if object contains only one element and wrote
import it.unimi.dsi.fastutil.objects.Reference2ReferenceOpenHashMap
import it.unimi.dsi.fastutil.objects.ReferenceArrayList
import it.unimi.dsi.fastutil.objects.ReferenceOpenHashSet
class Args {
var list : ReferenceArrayList<M>? = null
var set : ReferenceOpenHashSet<M>? = null
var map : Reference2ReferenceOpenHashMap<M, M>? = null
fun isEmpty() : Boolean {
return list === null && set === null && map === null
}
fun isScalar() : Boolean {
if(list !== null && list.size == 1) {
return true
}
}
}
Unfortunately it gave me error in comparison
list !== null && list.size == 1
saying
Smart cast to 'ReferenceArrayList<M>' is impossible, because 'list' is a mutable property that could have been changed by this time
As far as I understood, this is related with multithreaded assumption. In Java I would make function synchronized if would expect multithreding. Also, I would be able to disregard this at all, if I am not writing thread-safe.
How should I write in Kotlin?
I saw this solution https://stackoverflow.com/a/44596284/258483 but it expects MT, which I don't want to. How to avoid smart casting if it can't do it?
UPDATE
The question is how to do this in the same "procedural" form. How not to use smart casting?
UPDATE 2
Summarizing, as far as I understood, it is not possible/reasonable to explicitly compare variable with null in Kotlin at all. Because once you compare it, next time yous hould compare it with null again implicitly with such operations like .? and you can't avoid this.
If you take advantage of the fact that null cannot equal 1 (or anything else, really), you can make this check very concise:
fun isScalar() : Boolean =
list?.size == 1
When a null-safe call to list.size returns null, we get false because 1 != null. Otherwise, a comparison of whatever value size returns is made, and that works as you would expect.
By using the null safe operator (?.) you are avoiding a smart cast entirely. Kotlin gives us smart casts to make code cleaner, and this is one of the ways it protects us from misuses of that feature. Kotlin isn't going to protect us from everything (division by zero, the example you use in comments, for example). Your code is getting caught up in a legitimate case of where smart casting can go wrong, so Kotlin jumps in to help.
However, if you are absolutely sure there are no other threads working, then yes, this check is "wrong". You wouldn't need the warning in that case. Judging by this thread on kotlinlang.org, you aren't the only one!
You can perform the null check, and if it succeeds, access a read-only copy of your variable with let:
fun isScalar() : Boolean {
return list?.let { it.size == 1 } ?: false
}
If list is null, the entire let expression will evaluate to null, and the right side of the Elvis operator (false) will be returned.
If list is not null, then the let function is called, and result of the it.size == 1 expression is returned - it refers to the object that let was called on (list in this case). Since it's used with a safe call, this it will have a non-nullable type and size can be called on it.
I had the same problem in the given lines
sliderView.setSliderAdapter(adapter!!)
sliderView.setIndicatorAnimation(IndicatorAnimationType.WORM)
Finally, error resolved by adding !!
sliderView!!.setSliderAdapter(adapter!!)
sliderView!!.setIndicatorAnimation(IndicatorAnimationType.WORM)
int lua_isstring (lua_State *L, int index);
This function returns 1 if the value at the given acceptable index is
a string or a number (which is always convertible to a string), and 0
otherwise. (Source)
Is there a (more elegant) way to really proof if the given string really is a string and not a number in Lua? This function makes absolutely no sense to me!
My first idea is to additionally examine the string-length with
`if(string.len(String) > 1) {/* this must be a string */}`
... but that does not feel so good.
You can replace
lua_isstring(L, i)
which returns true for either a string or a number by
lua_type(L, i) == LUA_TSTRING
which yields true only for an actual string.
Similarly,
lua_isnumber(L, i)
returns true either for a number or for a string that can be converted to a number; if you want more strict checking, you can replace this with
lua_type(L, i) == LUA_TNUMBER
(I've written wrapper functions, lua_isstring_strict() and lua_isnumber_strict().)
This function makes absolutely no sense to me!
It makes sense in light of Lua's coercion rules. Any function that accepts a string should also accept a number, converting that number to a string. That's just how the language semantics are defined. The way lua_isstring and lua_tostring work allow you automatically implement those semantics in your C bindings with no additional effort.
If you don't like those semantics and want to disable automation conversion between string and number, you can define LUA_NOCVTS2N and/or LUA_NOCVTN2S in your build. In particular, if you define LUA_NOCVTN2S, lua_isstring will return false for numbers.
I have a question about using the new Objects.compare(o1, o2, Comparator) method - from my own testing of it, if both o1 and o2 are null then it returns 0, however, if one of them is null then it still throws a null pointer exception. I have found a lot of material on Objects.equals and some of the other Objects utility methods but not much at all on Objects.compare and when we are expected to use it / replace old code with it.
So here I could do this:
String s1 = "hi";
String s2 = "hi";
int x = Objects.compare(s1, s2, Comparator.naturalOrder());
System.out.println("x = " + x);
That works fine, returns 0, now this:
String s1 = null;
String s2 = null;
Also works fine and returns 0. However, this:
String s1 = "hi";
Strng s2 = null;
Throws a NullPointerException. I'm guessing the benefit of Objects.compare(o1,o2,Comparator) vs o1.compareTo(o2) is that it at least handles circumstances where both objects are null and when one of them is null it allows you to design a Comparator to handle it. I'm supposing, e.g.
int x = Objects.compare(s1, s2, Comparator.nullsFirst(Comparator.naturalOrder()));
Whereas with x.compareTo(y) there's no way to handle null unless you do so beforehand? So do the Java library developers now intend us to replace all calls to compareTo with Objects.compare, when we're concerned about nulls? e.g. would we do this in our Comparable implementations?
Side query 1: With regards to using nullsFirst if you use it then pass in a Comparator, which is chained using comparing, thenComparing, etc, does it apply to all of the inner comparators? e.g.
Comparator.nullsFirst(Comparator.comparing(Song::getTitle)
.thenComparing(Song::getArtist)
.thenComparing(Song::getDuration)
)
Would that apply nullsFirst to everything inside or do you need to use nullsFirst individually on each of them? I think from testing that it only applies to the actual Song objects being null, not for the fields of title or artist being null, i.e. if they are null then a NullPointerException is still thrown. Anyway around that?
Side query 2: final question is that because I like the Comparator.comparing syntax, I'm proposing to start to write my compareTo implementions using it - I was struggling to think how to replace this traditional approach, e.g.
public int compareTo(Song other) {
int result = this.title.compareTo(other.title);
if (result == 0) {
result = this.artist.compareTo(other.artist);
if (result == 0) {
result = Integer.compare(this.duration, other.duration);
}
}
return result;
}
then I thought I could use Objects.compare(...) as follows:
public int compareTo(Song other) {
return Objects.compare(this, other, Comparator.nullsFirst(
Comparator.comparing(Song::getTitle)
.thenComparing(Song::getArtist)
.thenComparingInt(Song::getDuration)
));
}
I thought this version was more elegant - I am assuming it is working as I think it is, e.g. by passing this and other as the first 2 arguments then the comparator, it has the same effect as the traditional compareTo approach with if statements? Whilst I can see that the benefit of Objects.compare catching two nulls would never occur as if this was null then the compareTo method call would never be reached (either by handling the exception or it being thrown). But by using nullsFirst I suppose if the argument passed in, i.e. other, was null, then this would handle this safely?
Many thanks in advance for any help.
Objects.compare is not meant to provide a null safe comparison, since there is no default behavior that could be implemented. It just implements a shortcut of not invoking the Comparator’s method when both objects are identical. In other words, it does a==b? 0: c.compare(a, b), nothing more. So not breaking when both objects are null is just a side-effect. The encapsulated code might look trivial but the other methods in this class are of a similar category. Using small utility methods a lot might still result in a notable win.
By the way, it’s not a Java 8 method at all. It exists since Java 7.
Regarding your second question, Comparator.nullsFirst(…) decorates an existing Comparator and will enforce the rule for null values before delegating to the provided comparator as it is the purpose of this comparator to shield the existing one from ever seeing null values. It doesn’t matter whether the decorated comparator is a chained one or not. As long as it is what you called the “inner comparator”, as
you must not invoke thenComparing on the result of nullsFirst as that would imply calling the next comparator when both values are null.
Comparator.nullsFirst(Comparator.comparing(a).thenComparing(b)) // perfect
Comparator.nullsFirst(Comparator.comparing(a)).thenComparing(b) // ouch
Now to your third question, implementing a compareTo method using a nullsFirst comparator is violating the interface specification:
The implementor must ensure sgn(x.compareTo(y)) == -sgn(y.compareTo(x)) for all x and y. (This implies that x.compareTo(y) must throw an exception iff y.compareTo(x) throws an exception.)
This implies that passing null as argument should always result in a NullPointerException as swapping argument and receiver would throw as well, unconditionally.
Orders including a null policy should always be provided as separate Comparators.
Note that it would also be quite inefficient as you would create a new Comparator (multiple Comparators, to be precise) for every compareTo call. Now image sorting a rather large list of these objects…
What I normally do for your final question is to first create a static comparator reference within the class:
public static final Comparator<Song> COMP_DEFAULT
= nullsFirst(comparing(Song::getTitle, nullsFirst(naturalOrder()))
.thenComparing(Song::getArtist, nullsFirst(naturalOrder()))
.thenComparingInt(Song::getDuration));
And then refer to this comparator in compareTo
public int compareTo(Song other) {
return COMP_DEFAULT.compare(this, other);
}
This way you're not recreating your comparator for each compareTo call, null safety of Song is guaranteed as is the result of a.comparetTo(b) == b.compareTo(a).
We also ensure null safety of each property by using nullsFirst(naturalOrder()) for the passed in key comparator (second argument).
As the Comparator returned is immutable it can be made public which can be handy for bundling some alternate Comparators with the class that consumers may use.
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.