Is recursion a feature in and of itself? - recursion

...or is it just a practice?
I'm asking this because of an argument with my professor: I lost credit for calling a function recursively on the basis that we did not cover recursion in class, and my argument is that we learned it implicitly by learning return and methods.
I'm asking here because I suspect someone has a definitive answer.
For example, what is the difference between the following two methods:
public static void a() {
return a();
}
public static void b() {
return a();
}
Other than "a continues forever" (in the actual program it is used correctly to prompt a user again when provided with invalid input), is there any fundamental difference between a and b? To an un-optimized compiler, how are they handled differently?
Ultimately it comes down to whether by learning to return a() from b that we therefor also learned to return a() from a. Did we?

To answer your specific question: No, from the standpoint of learning a language, recursion isn't a feature. If your professor really docked you marks for using a "feature" he hadn't taught yet, that was wrong.
Reading between the lines, one possibility is that by using recursion, you avoided ever using a feature that was supposed to be a learning outcome for his course. For example, maybe you didn't use iteration at all, or maybe you only used for loops instead of using both for and while. It's common that an assignment aims to test your ability to do certain things, and if you avoid doing them, your professor simply can't grant you the marks set aside for that feature. However, if that really was the cause of your lost marks, the professor should take this as a learning experience of his or her own- if demonstrating certain learning outcomes is one of the criteria for an assignment, that should be clearly explained to the students.
Having said that, I agree with most of the other comments and answers that iteration is a better choice than recursion here. There are a couple of reasons, and while other people have touched on them to some extent, I'm not sure they've fully explained the thought behind them.
Stack Overflows
The more obvious one is that you risk getting a stack overflow error. Realistically, the method you wrote is very unlikely to actually lead to one, since a user would have to give incorrect input many many times to actually trigger a stack overflow.
However, one thing to keep in mind is that not just the method itself, but other methods higher or lower in the call chain will be on the stack. Because of this, casually gobbling up available stack space is a pretty impolite thing for any method to do. Nobody wants to have to constantly worry about free stack space whenever they write code because of the risk that other code might have needlessly used a lot of it up.
This is part of a more general principle in software design called abstraction. Essentially, when you call DoThing(), all you should need to care about is that Thing is done. You shouldn't have to worry about the implementation details of how it's done. But greedy use of the stack breaks this principle, because every bit of code has to worry about how much stack it can safely assume it has left to it by code elsewhere in the call chain.
Readability
The other reason is readability. The ideal that code should aspire to is to be a human-readable document, where each line describes simply what it's doing. Take these two approaches:
private int getInput() {
int input;
do {
input = promptForInput();
} while (!inputIsValid(input))
return input;
}
versus
private int getInput() {
int input = promptForInput();
if(inputIsValid(input)) {
return input;
}
return getInput();
}
Yes, these both work, and yes they're both pretty easy to understand. But how might the two approaches be described in English? I think it'd be something like:
I will prompt for input until the input is valid, and then return it
versus
I will prompt for input, then if the input is valid I will return it, otherwise I get the input and return the result of that instead
Perhaps you can think of slightly less clunky wording for the latter, but I think you'll always find that the first one is going to be a more accurate description, conceptually, of what you are actually trying to do. This isn't to say recursion is always less readable. For situations where it shines, like tree traversal, you could do the same kind of side by side analysis between recursion and another approach and you'd almost certainly find recursion gives code which is more clearly self-describing, line by line.
In isolation, both of these are small points. It's very unlikely this would ever really lead to a stack overflow, and the gain in readability is minor. But any program is going to be a collection of many of these small decisions, so even if in isolation they don't matter much, it's important to learn the principles behind getting them right.

To answer the literal question, rather than the meta-question: recursion is a feature, in the sense that not all compilers and/or languages necessarily permit it. In practice, it is expected of all (ordinary) modern compilers - and certainly all Java compilers! - but it is not universally true.
As a contrived example of why recursion might not be supported, consider a compiler that stores the return address for a function in a static location; this might be the case, for example, for a compiler for a microprocessor that does not have a stack.
For such a compiler, when you call a function like this
a();
it is implemented as
move the address of label 1 to variable return_from_a
jump to label function_a
label 1
and the definition of a(),
function a()
{
var1 = 5;
return;
}
is implemented as
label function_a
move 5 to variable var1
jump to the address stored in variable return_from_a
Hopefully the problem when you try to call a() recursively in such a compiler is obvious; the compiler no longer knows how to return from the outer call, because the return address has been overwritten.
For the compiler I actually used (late 70s or early 80s, I think) with no support for recursion the problem was slightly more subtle than that: the return address would be stored on the stack, just like in modern compilers, but local variables weren't. (Theoretically this should mean that recursion was possible for functions with no non-static local variables, but I don't remember whether the compiler explicitly supported that or not. It may have needed implicit local variables for some reason.)
Looking forwards, I can imagine specialized scenarios - heavily parallel systems, perhaps - where not having to provide a stack for every thread could be advantageous, and where therefore recursion is only permitted if the compiler can refactor it into a loop. (Of course the primitive compilers I discuss above were not capable of complicated tasks like refactoring code.)

The teacher wants to know whether you have studied or not. Apparently you didn't solve the problem the way he taught you (the good way; iteration), and thus, considers that you didn't. I'm all for creative solutions but in this case I have to agree with your teacher for a different reason: If the user provides invalid input too many times (i.e. by keeping enter pressed), you'll have a stack overflow exception and your solution will crash. In addition, the iterative solution is more efficient and easier to maintain. I think that's the reason your teacher should have given you.

Deducting points because "we didn't cover recursion in class" is awful. If you learnt how to call function A which calls function B which calls function C which returns back to B which returns back to A which returns back to the caller, and the teacher didn't tell you explicitly that these must be different functions (which would be the case in old FORTRAN versions, for example), there is no reason that A, B and C cannot all be the same function.
On the other hand, we'd have to see the actual code to decide whether in your particular case using recursion is really the right thing to do. There are not many details, but it does sound wrong.

There are many point of views to look at regarding the specific question you asked but what I can say is that from the standpoint of learning a language, recursion isn't a feature on its own. If your professor really docked you marks for using a "feature" he hadn't taught yet, that was wrong but like I said, there are other point of views to consider here which actually make the professor being right when deducting points.
From what I can deduce from your question, using a recursive function to ask for input in case of input failure is not a good practice since every recursive functions' call gets pushed on to the stack. Since this recursion is driven by user input it is possible to have an infinite recursive function and thus resulting in a StackOverflow.
There is no difference between these 2 examples you mentioned in your question in the sense of what they do (but do differ in other ways)- In both cases, a return address and all method info is being loaded to the stack. In a recursion case, the return address is simply the line right after the method calling (of course its not exactly what you see in the code itself, but rather in the code the compiler created). In Java, C, and Python, recursion is fairly expensive compared to iteration (in general) because it requires the allocation of a new stack frame. Not to mention you can get a stack overflow exception if the input is not valid too many times.
I believe the professor deducted points since recursion is considered a subject of its own and its unlikely that someone with no programming experience would think of recursion. (Of course it doesn't mean they won't, but it's unlikely).
IMHO, I think the professor is right by deducting you the points. You could have easily taken the validation part to a different method and use it like this:
public bool foo()
{
validInput = GetInput();
while(!validInput)
{
MessageBox.Show("Wrong Input, please try again!");
validInput = GetInput();
}
return hasWon(x, y, piece);
}
If what you did can indeed be solved in that manner then what you did was a bad practice and should be avoided.

Maybe your professor hasn't taught it yet, but it sounds like you're ready to learn the advantages and disadvantages of recursion.
The main advantage of recursion is that recursive algorithms are often much easier and quicker to write.
The main disadvantage of recursion is that recursive algorithms can cause stack overflows, since each level of recursion requires an additional stack frame to be added to the stack.
For production code, where scaling can result in many more levels of recursion in production than in the programmer's unit tests, the disadvantage usually outweighs the advantage, and recursive code is often avoided when practical.

Regarding the specific question, is recursion a feature, I'm inclined to say yes, but after re-interpreting the question. There are common design choices of languages and compilers that make recursion possible, and Turing-complete languages do exist that don't allow recursion at all. In other words, recursion is an ability that is enabled by certain choices in language/compiler design.
Supporting first-class functions makes recursion possible under very minimal assumptions; see writing loops in Unlambda for an example, or this obtuse Python expression containing no self-references, loops or assignments:
>>> map((lambda x: lambda f: x(lambda g: f(lambda v: g(g)(v))))(
... lambda c: c(c))(lambda R: lambda n: 1 if n < 2 else n * R(n - 1)),
... xrange(10))
[1, 1, 2, 6, 24, 120, 720, 5040, 40320, 362880]
Languages/compilers that use late binding, or that define forward declarations, make recursion possible. For example, while Python allows the below code, that's a design choice (late binding), not a requirement for a Turing-complete system. Mutually recursive functions often depend on support for forward declarations.
factorial = lambda n: 1 if n < 2 else n * factorial(n-1)
Statically typed languages that allow recursively defined types contribute to enabling recursion. See this implementation of the Y Combinator in Go. Without recursively-defined types, it would still be possible to use recursion in Go, but I believe the Y combinator specifically would be impossible.

From what I can deduce from your question, using a recursive function to ask for input in case of input failure is not a good practice. Why?
Because every recursive functions call gets pushed on to the stack. Since this recursion is driven by user input it is possible to have an infinite recursive function and thus resulting in a StackOverflow :-p
Having a non recursive loop to do this is the way to go.

Recursion is a programming concept, a feature (like iteration), and a practice. As you can see from the link, there's a large domain of research dedicated to the subject. Perhaps we don't need to go that deep in the topic to understand these points.
Recursion as a feature
In plain terms, Java supports it implicitly, because it allows a method (which is basically a special function) to have "knowledge" of itself and of others methods composing the class it belongs to. Consider a language where this is not the case: you would be able to write the body of that method a, but you wouldn't be able to include a call to a within it. The only solution would be to use iteration to obtain the same result. In such a language, you would have to make a distinction between functions aware of their own existence (by using a specific syntax token), and those who don't! Actually, a whole group of languages do make that distinction (see the Lisp and ML families for instance). Interestingly, Perl does even allow anonymous functions (so called lambdas) to call themselves recursively (again, with a dedicated syntax).
no recursion?
For languages which don't even support the possibility of recursion, there is often another solution, in the form of the Fixed-point combinator, but it still requires the language to support functions as so called first class objects (i.e. objects which may be manipulated within the language itself).
Recursion as a practice
Having that feature available in a language doesn't necessary mean that it is idiomatic. In Java 8, lambda expressions have been included, so it might become easier to adopt a functional approach to programming. However, there are practical considerations:
the syntax is still not very recursion friendly
compilers may not be able to detect that practice and optimize it
The bottom line
Luckily (or more accurately, for ease of use), Java does let methods be aware of themselves by default, and thus support recursion, so this isn't really a practical problem, but it still remain a theoretical one, and I suppose that your teacher wanted to address it specifically. Besides, in the light of the recent evolution of the language, it might turn into something important in the future.

Related

What is the mechanism behind Function Application in Functional Programming

OK, let me try to rephrase my question.
Actually I wanted to know how is Function Application implemented in FP.
Is it done like a function call in imperative languages, where a stack frame is added for each call and removed on each return.
Or, is it like in inline functions, where the function call statement is replaced by the function definition.
Also, in terms of implementation of a function application, what is the significance of the statement functions in FP are mappings between domains and corresponding ranges. It is obviously not possible to maintain a mapping for each domain-range entry pair, so what exactly does the statement imply...
This question is broad enough that I can't answer it completely, since I don't know every single functional programming language. But I can tell you how it's done in one language, F#. You asked whether function application is done like a function call in imperative languages (another stack frame added for each call) or whether it's done as inline functions... and in F# the answer is both. The F# compiler is allowed to choose whether to create a stack-frame-using function call, or whether to inline the function at the call site; generally the choice is made based on the size of the compiled function. If the function compiles down to fewer than N bytes of compiled code (I can't tell you the exact number, but knowing the exact number doesn't actually matter) then the compiler will usually inline that function call; if it takes more than N bytes then the function call will use a stack frame. (Except in the case of tail-recursive calls, which are compiled to the equivalent of a goto and don't use a stack frame).
P.S. You can force the compiler's hand by using the inline keyword, which forces that function to be inlined at the call site every time. Most F# programmers don't recommend doing that on a regular basis, because the compiler is smart enough that it's usually not a good idea to override its decisions. (Also, the inline keyword means that the types of the function's parameters must be resolvable at compile time, so there are some functions for which that changes the semantics, but that's a little off-topic for the question you asked so I won't go into it. Except to say that in F#, statically-resolved type parameters or SRTPs are a very complicated subject, and you can do some very advanced things with them if you understand them.)

Do purely functional languages really guarantee immutability?

In a purely functional language, couldn't one still define an "assignment" operator, say, "<-", such that the command, say, "i <- 3", instead of directly assigning the immutable variable i, would create a copy of the entire current call stack, except replacing i with 3 in the new call stack, and executing the new call stack from that point onward? Given that no data actually changed, wouldn't that still be considered "purely functional" by definition? Of course the compiler would simply make the optimization to simply assign 3 to i, in which case what's the difference between imperative and purely functional?
Purely functional languages, such as Haskell, have ways of modelling imperative languages, and they are not shy about admitting it either. :)
See http://www.haskell.org/tutorial/io.html, in particular 7.5:
So, in the end, has Haskell simply
re-invented the imperative wheel?
In some sense, yes. The I/O monad
constitutes a small imperative
sub-language inside Haskell, and thus
the I/O component of a program may
appear similar to ordinary imperative
code. But there is one important
difference: There is no special
semantics that the user needs to deal
with. In particular, equational
reasoning in Haskell is not
compromised. The imperative feel of
the monadic code in a program does not
detract from the functional aspect of
Haskell. An experienced functional
programmer should be able to minimize
the imperative component of the
program, only using the I/O monad for
a minimal amount of top-level
sequencing. The monad cleanly
separates the functional and
imperative program components. In
contrast, imperative languages with
functional subsets do not generally
have any well-defined barrier between
the purely functional and imperative
worlds.
So the value of functional languages is not that they make state mutation impossible, but that they provide a way to allow you to keep the purely functional parts of your program separate from the state-mutating parts.
Of course, you can ignore this and write your entire program in the imperative style, but then you won't be taking advantage of the facilities of the language, so why use it?
Update
Your idea is not as flawed as you assume. Firstly, if someone familiar only with imperative languages wanted to loop through a range of integers, they might wonder how this could be achieved without a way to increment a counter.
But of course instead you just write a function that acts as the body of the loop, and then make it call itself. Each invocation of the function corresponds to an "iteration step". And in the scope of each invocation the parameter has a different value, acting like an incrementing variable. Finally, the runtime can note that the recursive call appears at the end of the invocation, and so it can reuse the top of the function-call stack instead of growing it (tail call). Even this simple pattern has almost all of the flavour of your idea - including the compiler/runtime quietly stepping in and actually making mutation occur (overwriting the top of the stack). Not only is it logically equivalent to a loop with a mutating counter, but in fact it makes the CPU and memory do the same thing physically.
You mention a GetStack that would return the current stack as a data structure. That would indeed be a violation of functional purity, given that it would necessarily return something different each time it was called (with no arguments). But how about a function CallWithStack, to which you pass a function of your own, and it calls back to your function and passes it the current stack as a parameter? That would be perfectly okay. CallCC works a bit like that.
Haskell doesn't readily give you ways to introspect or "execute" call stacks, so I wouldn't worry too much about that particular bizarre scheme. However in general it is true that one can subvert the type system using unsafe "functions" such as unsafePerformIO :: IO a -> a. The idea is to make it difficult, not impossible, to violate purity.
Indeed, in many situations, such as when making Haskell bindings for a C library, these mechanisms are quite necessary... by using them you are removing the burden of proof of purity from the compiler and taking it upon yourself.
There is a proposal to actually guarantee safety by outlawing such subversions of the type system; I'm not too familiar with it, but you can read about it here.
Immutability is a property of the language, not of the implementation.
An operation a <- expr that copies data is still an imperative operation, if values that refer to the location a appear to have changed from the programmers point of view.
Likewise, a purely functional language implementation may overwrite and reuse variables to its heart's content, as long as each modification is invisible to the programmer. For example, the map function can in principle overwrite a list instead of creating a new, whenever the language implementation can deduce that the old list won't be needed anywhere.

What are the practical advantages of currying?

I see a lot of documentation and questions about what the currying technique is, but I have found very little information on why one would use it in practice. My question is, what are the advantages of currying? Perhaps you can provide a trivial example where currying would be preferable to conventional method invocation.
I work in C++ while the sun is up, so to date I have had little exposure to currying other than out-of work tinkering with languages.
First, it's very common to mistake partial function application for currying. See this for example (I'm sure there are better resources describing it, but this was the first one i found). I've almost never seen anyone use currying in practice (except for languages like Haskell, where every function is curried by the language itself, so to speak, but even that is in order to enable simple partial function application). Partial function application on the other hand is quite useful in many languages.
Anyway, assuming you're talking about partial function application (since that's what most people are talking about when they're asking about currying), the concept is not quite as natural in C++ as in a (purely) functional language, such as Haskell for example.
For example, here we define a function sum that takes an array of numbers list and sums all the numbers together. If you're unfamilir with the concept of fold (or reduce or inject, as it is sometimes called), read this. Anyway, it would look like this:
sum list = foldl (+) 0 list
But wait a minute. We could shorten it by using partial function application! Instead of supplying an argument, we just say that sum is a function that is equal to foldl, with + and 0 partially applied.
sum = foldl (+) 0
Which one is easier to read? A matter of preference probably, but the latter emphazises the relation between sum and foldl more clearly in my opinion. And please take into account that this is a very simple example. I honestly don't know how to write a good example in C++, so you'll have to excuse me there. In any case, what is the practical advantage? Readability. Clearer intent. Shorter code.
Disclaimer: If you actually wanted to know the advantages of currying (as opposed to partial function application) I'm sorry to have made you read all this. But on the other hand, if you understand the difference between the two will also understand that currying is a great way to implement partial function application.

What is a practical difference between a loop and recursion

I am currently working in PHP, so this example will be in PHP, but the question applies to multiple languages.
I am working on this project with a fiend of mine, and as always we were held up by a big problem. Now we both went home, couldn't solve the problem. That night we both found the solution, only I used a loop to tackle the problem, and he used recursion.
Now I wanted to tell him the difference between the loop and recursion, but I couldn't come up with a solution where you need recursion over a normal loop.
I am going to make a simplified version of both, I hope someone can explain how one is different from the other.
Please forgive me for any coding errors
The loop:
printnumbers(1,10);
public function printnumbers($start,$stop)
{
for($i=$start;$i<=$stop;$i++)
{
echo $i;
}
}
Now the code above just simply prints out the numbers.
Now let's do this with recursion:
printnumbers(1,10);
public function printnumbers($start,$stop)
{
$i = $start;
if($i <= $stop)
{
echo $i;
printnumbers($start+1,$stop);
}
}
This method above will do the exact same thing as the loop, but then only with recursion.
Can anyone explain to me what there is different about using one of these methods.
Loops and recursions are in many ways equivalent. There are no programs the need one or the other, in principle you can always translate from loops to recursion or vice versa.
Recursions is more powerful in the sense that to translating recursion to a loop might need a stack that you have to manipulate yourself. (Try traversing a binary tree using a loop and you will feel the pain.)
On the other hand, many languages (and implementations), e.g., Java, don't implement tail recursion properly. Tail recursion is when the last thing you do in a function is to call yourself (like in your example). This kind of recursion does not have to consume any stack, but in many languages they do, which means you can't always use recursion.
Often, a problem is easier expressed using recursion. This is especially true when you talk about tree-like data structures (e.g. directories, decision trees...).
These data structures are finite in nature, so most of the time processing them is clearer with recursion.
When stack-depth is often limited, and every function call requires a piece of stack, and when talking about a possibly infinite data structure you will have to abandon recursion and translate it into iteration.
Especially functional languages are good at handling 'infinite' recursion. Imperative languages are focused on iteration-like loops.
In general, a recursive function will consume more stack space (since it's really a large set of function calls), while an iterative solution won't. This also means that an iterative solution, in general, will be faster because.
I am not sure if this applies to an interpreted language like PHP though, it is possible that the interpreter can handle this better.
A loop will be faster because there's always overhead in executing an extra function call.
A problem with learning about recursion is a lot of the examples given (say, factorials) are bad examples of using recursion.
Where possible, stick with a loop unless you need to do something different. A good example of using recursion is looping over each node in a Tree with multiple levels of child nodes.
Recursion is a bit slower (because function calls are slower than setting a variable), and uses more space on most languages' call stacks. If you tried to printnumbers(1, 1000000000), the recursive version would likely throw a PHP fatal error or even a 500 error.
There are some cases where recursion makes sense, like doing something to every part of a tree (getting all files in a directory and its subdirectories, or maybe messing with an XML document), but it has its price -- in speed, stack footprint, and the time spent to make sure it doesn't get stuck calling itself over and over til it crashes. If a loop makes more sense, it's definitely the way to go.
Well, I don't know about PHP but most languages generate a function call (at the machine level) for every recursion. So they have the potential to use a lot of stack space, unless the compiler produces tail-call optimizations (if your code allows it).
Loops are more 'efficient' in that sense because they don't grow the stack. Recursion has the advantage of being able to express some tasks more naturally though.
In this specific case, from a conceptual (rather than implementative) point of view, the two solutions are totally equivalent.
Compared to loops, a function call has its own overhead like allocating stack etc. And in most cases, loops are more understandable than their recursive counterparts.
Also, you will end up using more memory and can even run out of stack space if the difference between start and stop is high and there are too many instances of this code running simultaneously (which can happen as you get more traffic).
You don't really need recursion for a flat structure like that. The first code I ever used recursion in involved managing physical containers. Each container might contain stuff (a list of them, each with weights) and/or more containers, which have a weight. I needed the total weight of a container and all it held. (I was using it to predict the weight of large backpacks full of camping equipment without packing and weighing them.) This was easy to do with recursion and would have been a lot harder with loops. But many kinds of problems that naturally suit themselves to one approach can also be tackled with the other.
Stack overflow.
And no, I don't mean a website or something. I MEAN a "stack overflow".

Advantages of stateless programming?

I've recently been learning about functional programming (specifically Haskell, but I've gone through tutorials on Lisp and Erlang as well). While I found the concepts very enlightening, I still don't see the practical side of the "no side effects" concept. What are the practical advantages of it? I'm trying to think in the functional mindset, but there are some situations that just seem overly complex without the ability to save state in an easy way (I don't consider Haskell's monads 'easy').
Is it worth continuing to learn Haskell (or another purely functional language) in-depth? Is functional or stateless programming actually more productive than procedural? Is it likely that I will continue to use Haskell or another functional language later, or should I learn it only for the understanding?
I care less about performance than productivity. So I'm mainly asking if I will be more productive in a functional language than a procedural/object-oriented/whatever.
Read Functional Programming in a Nutshell.
There are lots of advantages to stateless programming, not least of which is dramatically multithreaded and concurrent code. To put it bluntly, mutable state is enemy of multithreaded code. If values are immutable by default, programmers don't need to worry about one thread mutating the value of shared state between two threads, so it eliminates a whole class of multithreading bugs related to race conditions. Since there are no race conditions, there's no reason to use locks either, so immutability eliminates another whole class of bugs related to deadlocks as well.
That's the big reason why functional programming matters, and probably the best one for jumping on the functional programming train. There are also lots of other benefits, including simplified debugging (i.e. functions are pure and do not mutate state in other parts of an application), more terse and expressive code, less boilerplate code compared to languages which are heavily dependent on design patterns, and the compiler can more aggressively optimize your code.
The more pieces of your program are stateless, the more ways there are to put pieces together without having anything break. The power of the stateless paradigm lies not in statelessness (or purity) per se, but the ability it gives you to write powerful, reusable functions and combine them.
You can find a good tutorial with lots of examples in John Hughes's paper Why Functional Programming Matters (PDF).
You will be gobs more productive, especially if you pick a functional language that also has algebraic data types and pattern matching (Caml, SML, Haskell).
Many of the other answers have focused on the performance (parallelism) side of functional programming, which I believe is very important. However, you did specifically ask about productivity, as in, can you program the same thing faster in a functional paradigm than in an imperative paradigm.
I actually find (from personal experience) that programming in F# matches the way I think better, and so it's easier. I think that's the biggest difference. I've programmed in both F# and C#, and there's a lot less "fighting the language" in F#, which I love. You don't have to think about the details in F#. Here's a few examples of what I've found I really enjoy.
For example, even though F# is statically typed (all types are resolved at compile time), the type inference figures out what types you have, so you don't have to say it. And if it can't figure it out, it automatically makes your function/class/whatever generic. So you never have to write any generic whatever, it's all automatic. I find that means I'm spending more time thinking about the problem and less how to implement it. In fact, whenever I come back to C#, I find I really miss this type inference, you never realise how distracting it is until you don't need to do it anymore.
Also in F#, instead of writing loops, you call functions. It's a subtle change, but significant, because you don't have to think about the loop construct anymore. For example, here's a piece of code which would go through and match something (I can't remember what, it's from a project Euler puzzle):
let matchingFactors =
factors
|> Seq.filter (fun x -> largestPalindrome % x = 0)
|> Seq.map (fun x -> (x, largestPalindrome / x))
I realise that doing a filter then a map (that's a conversion of each element) in C# would be quite simple, but you have to think at a lower level. Particularly, you'd have to write the loop itself, and have your own explicit if statement, and those kinds of things. Since learning F#, I've realised I've found it easier to code in the functional way, where if you want to filter, you write "filter", and if you want to map, you write "map", instead of implementing each of the details.
I also love the |> operator, which I think separates F# from ocaml, and possibly other functional languages. It's the pipe operator, it lets you "pipe" the output of one expression into the input of another expression. It makes the code follow how I think more. Like in the code snippet above, that's saying, "take the factors sequence, filter it, then map it." It's a very high level of thinking, which you don't get in an imperative programming language because you're so busy writing the loop and if statements. It's the one thing I miss the most whenever I go into another language.
So just in general, even though I can program in both C# and F#, I find it easier to use F# because you can think at a higher level. I would argue that because the smaller details are removed from functional programming (in F# at least), that I am more productive.
Edit: I saw in one of the comments that you asked for an example of "state" in a functional programming language. F# can be written imperatively, so here's a direct example of how you can have mutable state in F#:
let mutable x = 5
for i in 1..10 do
x <- x + i
Consider all the difficult bugs you've spent a long time debugging.
Now, how many of those bugs were due to "unintended interactions" between two separate components of a program? (Nearly all threading bugs have this form: races involving writing shared data, deadlocks, ... Additionally, it is common to find libraries that have some unexpected effect on global state, or read/write the registry/environment, etc.) I would posit that at least 1 in 3 'hard bugs' fall into this category.
Now if you switch to stateless/immutable/pure programming, all those bugs go away. You are presented with some new challenges instead (e.g. when you do want different modules to interact with the environment), but in a language like Haskell, those interactions get explicitly reified into the type system, which means you can just look at the type of a function and reason about the type of interactions it can have with the rest of the program.
That's the big win from 'immutability' IMO. In an ideal world, we'd all design terrific APIs and even when things were mutable, effects would be local and well-documented and 'unexpected' interactions would be kept to a minimum. In the real world, there are lots of APIs that interact with global state in myriad ways, and these are the source of the most pernicious bugs. Aspiring to statelessness is aspiring to be rid of unintended/implicit/behind-the-scenes interactions among components.
One advantage of stateless functions is that they permit precalculation or caching of the function's return values. Even some C compilers allow you to explicitly mark functions as stateless to improve their optimisability. As many others have noted, stateless functions are much easier to parallelise.
But efficiency is not the only concern. A pure function is easier to test and debug since anything that affects it is explicitly stated. And when programming in a functional language, one gets in the habit of making as few functions "dirty" (with I/O, etc.) as possible. Separating out the stateful stuff this way is a good way to design programs, even in not-so-functional languages.
Functional languages can take a while to "get", and it's difficult to explain to someone who hasn't gone through that process. But most people who persist long enough finally realise that the fuss is worth it, even if they don't end up using functional languages much.
Without state, it is very easy to automatically parallelize your code (as CPUs are made with more and more cores this is very important).
Stateless web applications are essential when you start having higher traffic.
There could be plenty of user data that you don't want to store on the client side for security reasons for example. In this case you need to store it server-side. You could use the web applications default session but if you have more than one instance of the application you will need to make sure that each user is always directed to the same instance.
Load balancers often have the ability to have 'sticky sessions' where the load balancer some how knows which server to send the users request to. This is not ideal though, for example it means every time you restart your web application, all connected users will lose their session.
A better approach is to store the session behind the web servers in some sort of data store, these days there are loads of great nosql products available for this (redis, mongo, elasticsearch, memcached). This way the web servers are stateless but you still have state server-side and the availability of this state can be managed by choosing the right datastore setup. These data stores usually have great redundancy so it should almost always be possible to make changes to your web application and even the data store without impacting the users.
My understanding is that FP also has a huge impact on testing. Not having a mutable state will often force you to supply more data to a function than you would have to for a class. There's tradeoffs, but think about how easy it would be to test a function that is "incrementNumberByN" rather than a "Counter" class.
Object
describe("counter", () => {
it("should increment the count by one when 'increment' invoked without
argument", () => {
const counter = new Counter(0)
counter.increment()
expect(counter.count).toBe(1)
})
it("should increment the count by n when 'increment' invoked with
argument", () => {
const counter = new Counter(0)
counter.increment(2)
expect(counter.count).toBe(2)
})
})
functional
describe("incrementNumberBy(startingNumber, increment)", () => {
it("should increment by 1 if n not supplied"){
expect(incrementNumberBy(0)).toBe(1)
}
it("should increment by 1 if n = 1 supplied"){
expect(countBy(0, 1)).toBe(1)
}
})
Since the function has no state and the data going in is more explicit, there are fewer things to focus on when you are trying to figure out why a test might be failing. On the tests for the counter we had to do
const counter = new Counter(0)
counter.increment()
expect(counter.count).toBe(1)
Both of the first two lines contribute to the value of counter.count. In a simple example like this 1 vs 2 lines of potentially problematic code isn't a big deal, but when you deal with a more complex object you might be adding a ton of complexity to your testing as well.
In contrast, when you write a project in a functional language, it nudges you towards keeping fancy algorithms dependent on the data flowing in and out of a particular function, rather than being dependent on the state of your system.
Another way of looking at it would be illustrating the mindset for testing a system in each paradigm.
For Functional Programming: Make sure function A works for given inputs, you make sure function B works with given inputs, make sure C works with given inputs.
For OOP: Make sure Object A's method works given an input argument of X after doing Y and Z to the state of the object. Make sure Object B's method works given an input argument of X after doing W and Y to the state of the object.
The advantages of stateless programming coincide with those goto-free programming, only more so.
Though many descriptions of functional programming emphasize the lack of mutation, the lack of mutation also goes hand in hand with the lack of unconditional control transfers, such as loops. In functional programming languages, recursion, in particularly tail recursion, replaces looping. Recursion eliminates both the unconditional control construct and the mutation of variables in the same stroke. The recursive call binds argument values to parameters, rather than assigning values.
To understand why this is advantageous, rather than turning to functional programming literature, we can consult the 1968 paper by Dijkstra, "Go To Statement Considered Harmful":
"The unbridled use of the go to statement has an immediate consequence that it becomes terribly hard to find a meaningful set of coordinates in which to describe the process progress."
Dijkstra's observations, however still apply to structured programs which avoid go to, because statements like while, if and whatnot are just window dressing on go to! Without using go to, we can still find it impossible to find the coordinates in which to describe the process progress. Dijkstra neglected to observe that bridled go to still has all the same issues.
What this means is that at any given point in the execution of the program, it is not clear how we got there. When we run into a bug, we have to use backwards reasoning: how did we end up in this state? How did we branch into this point of the code? Often it is hard to follow: the trail goes back a few steps and then runs cold due to a vastness of possibilities.
Functional programming gives us the absolute coordinates. We can rely on analytical tools like mathematical induction to understand how the program arrived into a certain situation.
For example, to convince ourselves that a recursive function is correct, we can just verify its base cases, and then understand and check its inductive hypothesis.
If the logic is written as a loop with mutating variables, we need a more complicated set of tools: breaking down the logic into steps with pre- and post-conditions, which we rewrite in terms mathematics that refers to the prior and current values of variables and such. Yes, if the program uses only certain control structures, avoiding go to, then the analysis is somewhat easier. The tools are tailored to the structures: we have a recipe for how we analyze the correctness of an if, while, and other structures.
However, by contrast, in a functional program there is no prior value of any variable to reason about; that whole class of problem has gone away.
Haskel and Prolog are good examples of languages which may be implemented as stateless programming languages. But unfortunately they are not so far. Both Prolog and Haskel have imperative implementations currently. See some SMT's, seem closer to stateless coding.
This is why you are having hard time seeing any benefits from these programing languages. Due to imperative implementations we have no performance and stability benefits. So the lack of stateless languages infrastructure is the main reason you feel no any stateless programming language due to its absence.
These are some benefits of pure stateless:
Task description is the program (compact code)
Stability due to absense of state-dependant bugs (the most of bugs)
Cachable results (a set of inputs always cause same set of outputs)
Distributable computations
Rebaseable to quantum computations
Thin code for multiple overlapping clauses
Allows differentiable programming optimizations
Consistently applying code changes (adding logic breaks nothing written)
Optimized combinatorics (no need to bruteforce enumerations)
Stateless coding is about concentrating on relations between data which then used for computing by deducing it. Basically this is the next level of programming abstraction. It is much closer to native language then any imperative programming languages because it allow describing relations instead of state change sequences.

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