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I'm aware that they both use different programming paradigms, but from a high level perspective apart from differing syntax it seems most basic tasks can be achieved in similar fashion.
I only say this because when I've previously touched functional programming languages such as Haskell, writing code for basics tasks was (at first) difficult, frustrating, and required a completely different mindset.
For example the following took some time to get to grips with using recursive syntax:
loop :: Int -> IO ()
loop n = if 0 == n then return () else loop (n-1)
Where as an F# loop is recognisable and understable almost immediately:
let list1 = [ 1; 5; 100; 450; 788 ]
for i in list1 do
printfn "%d" i
When C# programmers start learning F# they are advised to completely re-think their thought pattern (which was definitely required for Haskell), but I've now written several F# programs dealing with conditions, loops, data sets etc to perform practical tasks, and I'm wondering where the 'different-paradigm' barrier really kicks in?
Hopefully someone will be able to solve my confusion.
wThe main difference when the barrier kicks in is when people have to think in terms of functions, not in terms of objects.
Yes, it is totally possible to do object-oriented code in F#, and in this matter there is not that much of a difference between these two besides syntax. But that's not the point when using F#, even if F# allows you do to it.
The barrier kicks in when developers start solving problems in a functional way.
Here are the some of the topics that are new for C#/OO developers when learning F#/FP
Pattern matching. Sometimes people have hard times comprehending its usefulness.
Tail recursion (and the "recursive" way of solving problems)
Discriminated unions (people still try to look at them as to hierarchy of classes, IEquatable/IComparable implementations, etc instead of just thinking declaratively)
The "unit" value over "void".
Partial application (gets a bit easier as latest versions of C# allows us to deal with Funcs, but as it looks ugly not many do)
The whole concept of values over variables (including immutability)
The main difference between C# and F# is that F# gives you all this, and it makes sense to take it and use it for good.
However, yes, it is still possible writing "Csharpish" code in F# without kicking any barrier except that in this case one will hate F# for its syntax.
Your question is a bit misleading. From a very high-level perspective, pretty much all programming language are equivalent. They are all turing-complete and as such, allow you to solve the same set of problems.
From a still high-level, but more concrete perspective, C# and F# differ in so far, as F#'s functionality is a superset of C#'s. (please, do not flame me for this, I know it is not true, strictly speaking, but it gives a picture)
F# being a .net language, it inherits .net's object model and in the object-oriented subset is therefore very similar to C#, with a more lightweight syntax due to better type inference.
However, F# also supports two other paradigms:
functional programming: F# "variables", they are in fact called values, are immutable by default and as such a c# style int i = 0; i = i+1; looks very differently in F#, because you need to allow for mutability explicitly let mutable i = 0; i <- i + 1;. So if you look at the functional subset, F# is, in fact a lot closer to Haskell than it is to C#.
imperative programming: You can also write F# code in a script-oriented style, without classes, modules, etc. Just a pure script, and in this case it also looks very differently from C#.
Your example used loops similar in style to how you would write C# code and therefore it felt similar.
If you do a very small change, however, you can achieve the same thing in a way that is already quite different from C#. [ 1; 5; 100; 450; 788 ] |> List.iter (printfn "%d")
The reason why people tend to claim you need to change the way how you think about problems, is because the incentive of F#, for a C# programmer, usually is the functional subset, not the object-oriented one.
Looks like you haven't done too much Haskell?
How is, for example,
let list1 = [ 1, 5, 100, 450, 788 ]
forM_ list1 printStrLn
less recognzable?
If you like, you can even have an alias for for forM_
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I know that this might be a stupid question but I was curious.
Since Lisp treats code and data the same, does this mean that it's easier to write a payload and pass it as "innocent" data that can be used to exploit programs? In comparison to languages that don't do so?
For e.g. In python you can do something like this.
malicious_str = "print('this is a malicious string')"
user_in = eval(malicious_str)
>>> this is a malicious string
P.S I have just started learning Lisp.
No, I don't think it does. In fact because of what is normally meant by 'code is data' in Lisp, it is potentially less vulnerable than some other languages.
[Note: this answer is really about Common Lisp: see the end for a note about that.]
There are two senses in which 'code can be data' in a language.
Turning objects into executable code: eval & friends
This is the first sense. What this means is that you can, say, take a string or some other object (not all types of object, obviously) and say 'turn this into something I can execute, and do that'.
Any language that can do this has either
to be extremely careful about doing this on unconstrained data;
or to be able to be certain that a given program does not actually do this.
Plenty of languages have equivalents of eval and its relations, so plenty of languages have this problem. You give an example of Python for instance, which is a good one, and there are probably other examples in Python (I've written programs even in Python 2 which supported dynamic loading of modules at runtime, which executes potentially arbitrary code, and I think this stuff is much better integrated in Python 3).
This is also not just a property of a language: it's a property of a system. C can't do this, right? Well, yes it can if you're on any kind of reasonable *nixy platform. Not only can you use an exec-family function, but you can probably dynamically load a shared library and execute code in it.
So one solution to this problem is to, somehow, be able to be certain that a given program doesn't do this. One thing that helps is if there are a finite, known number of ways of doing it. In Common Lisp I think those are probably
eval of course;
unconstrained read (because of *read-eval*);
load;
compile;
compile-file;
and probably some others that I have forgotten.
Well, can you detect calls to those, statically, in a program? Not really: consider this:
(funcall (symbol-function (find-symbol s)) ...)
and now you're in trouble unless you have very good control over what s is: it might be "EVAL" for instance.
So that's frightening, but I don't think it's more frightening than what Python can do, for instance (almost certainly you can poke around in the namespace to find eval or something?). And something like that in a program ought to be a really big hint that bad things might happen.
I think there are probably two approaches to this, neither of which CL adopts but which implementations could (and perhaps even programs written in CL could).
One would be to be able to run programs in such a way that the finite set of bad functions above simply are disallowed: they'd signal errors if you tried to call them. An implementation could clearly do that (see below).
The other would be to have something like Perl's 'tainting' where data which came from a user needs to be explicitly looked-at by the program somehow before it's used. That doesn't guarantee safety of course, but it does make it harder to make silly mistakes: if s above came from user input and was thus tainted you'd have to explicitly say 'it's OK to use it' and, well, then it's up to you.
So this is a problem, but I don't think it's worse than the problems that very many other languages (and language-families) have.
An example of an implementation that can address the first approach is LispWorks: if you're building an application with LW, you typically create the binary with a function called deliver, which has options which allow you to remove the definitions of functions from the resulting binary whether or not the delivery process would otherwise leave them there. So, for instance
(deliver 'foo "x" 5
:functions-to-remove '(eval load compile compile-file read))
would result in an executable x which, whatever else it did, couldn't call those functions, because they're not present, at all.
Other implementations probably have similar features: I just don't know them as well.
But there's another sense in which 'code is data' in Lisp.
Program source code is available as structured data
This is the sense that people probably really mean when they say 'code is data' in Lisp, even if they don't know that. It's worth looking at your Python example again:
>>> eval("exit('exploded')")
exploded
$
So what eval eats is a string: a completely unstructured vector of characters. If you want to know whether that string contains something nasty, well, you've got a lot of work ahead of you (disclaimer: see below).
Compare this with CL:
> (let ((trying-to-be-bad "(end-the-world :now t)"))
(eval trying-to-be-bad))
"(end-the-world :now t)"
OK, so that clearly didn't end the world. And it didn't end the world because eval evaluates a bit of Lisp source code, and the value of a string, as source code, is the string.
If I want to do something nasty I have to hand it an actual interesting structure:
> (let ((actually-bad '(eval (progn
(format *query-io* "? ")
(finish-output *query-io*)
(read *query-io*)))))
(eval actually-bad))
? (defun foo () (foo))
foo
Now that's potentially quite nasty in at least several ways. But wait: in order to do this nasty thing, I had to hand eval a chunk of source code represented as an s-expression. And the structure of that s-expression is completely open to inspection by me. I can write a program which inspects this s-expression in any arbitrary way I like, and decides whether or not it is acceptable to me. That's just hugely easier than 'given this string, interpret it as a piece of source text for the language and tell me if it is dangerous':
the process of turning the sequence of characters into an s-expression has happened already;
the structure of s-expressions is both simple and standard.
So in this sense of 'code is data', Lisp is potentially much safer than other languages which have versions of eval which eat strings, like Python, say, because code is structured, standard, simple data. Lisp has an answer to the terrible 'language in a string' problem.
I am fairly sure that Python does in fact have some approach to making the parse tree available in a standard way which can be inspected. But eval still happily eats strings.
As I said above, this answer is about Common Lisp. But there are many other Lisps of course, which will have varying versions of this problem. Racket for instance probably can really fairly tightly constrain things, using sandboxed execution and modules, although I haven't explored this.
Any language can be exploited if you are not careful.
A well-known attack against Lisp is via the #. reader macro:
(read-from-string "#.(start-the-war)")
will start the war if *read-eval* is non-nil - this is why one should always bind it when reading from an un-trusted stream.
However, this is not directly related to "code is data" doctrine...
I am currently working on writing my own language(shameless plug), which is centered around flexibility. I am trying to make almost any part of the language syntax exchangeable through things like extensions/plugins. While writing the whole thing, it has got me thinking. I am wondering how that sort of flexibility could affect the language.
I know that Lisp is often referred to as one of the most extensible languages due to its extensive macro system. I do understand that concept of macros, but I am yet to find a language that allows someone to change the way it is parsed. To my knowledge, almost every language has an extremely concrete syntax as defined by some long specification.
My question is how could having a flexible syntax affect the intuitiveness and usability of the language? I know the basic "people might be confused when the syntax changes" and "semantic analysis will be hard". Those are things that I am already starting to compensate for. I am looking for a more conceptual answer on the pros and cons of having a flexible syntax.
The topic of language design is still quite foreign to me, so I apologize if I am asking an obvious or otherwise stupid question!
Edit:
I was just wanting to clarify the question I was asking. Where exactly does flexibility in a language's syntax stand, in terms of language theory? I don't really need examples or projects/languages with flexibility, I want to understand how it can affect the language's readability, functionality, and other things like that.
Perl is the most flexible language I know. That a look at Moose, a postmodern object system for Perl 5. It's syntax is very different than Perl's but it is still very Perl-ish.
IMO, the biggest problem with flexibility is precedence in infix notation. But none I know of allow a datatype to have its own infix syntax. For example, take sets. It would be nice to use ⊂ and ⊇ in their syntax. But not only would a compiler have to recognize these symbols, it would have to be told their order of precedence.
Common Lisp allows to change the way it's parsed - see reader macros. Racket allows to modify its parser, see racket languages.
And of course you can have a flexible, dynamically extensible parsing alongside with powerful macros if you use the right parsing techniques (e.g., PEG). Have a look at an example here - mostly a C syntax, but extensible with both syntax and semantic macros.
As for precedence, PEG goes really well together with Pratt.
To answer your updated question - there is surprisingly little research done on programming languages readability anyway. You may want to have a look at what Dr. Blackwell group was up to, but it's still far from conclusive.
So I can only share my hand-wavy anecdotes - flexible syntax languages facilitates eDSL construction, and, in my opinion, eDSLs is the only way to eliminate unnecessary complexity from code, to make code actually maintainable in a long term. I believe that non-flexible languages are one of the biggest mistakes made by this industry, and it must be corrected at all costs, ASAP.
Flexibility allows you to manipulate the syntax of the language. For example, Lisp Macros can enable you to write programs that write programs and manipulate your syntax at compile-time to valid Lisp expressions. For example the Loop Macro:
(loop for x from 1 to 5
do(format t "~A~%" x))
1
2
3
4
5
NIL
And we can see how the code was translated with macroexpand-1:
(pprint(macroexpand-1 '(loop for x from 1 to 5
do (format t "~a~%" x))))
We can then see how a call to that macro is translated:
(LET ((X 1))
(DECLARE (TYPE (AND REAL NUMBER) X))
(TAGBODY
SB-LOOP::NEXT-LOOP
(WHEN (> X '5) (GO SB-LOOP::END-LOOP))
(FORMAT T "~a~%" X)
(SB-LOOP::LOOP-DESETQ X (1+ X))
(GO SB-LOOP::NEXT-LOOP)
SB-LOOP::END-LOOP)))
Language Flexibility just allows you to create your own embedded language within a language and reduce the length of your program in terms of characters used. So in theory, this can make a language very unreadable since we can manipulate the syntax. For example we can create invalid code that's translated to valid code:
(defmacro backwards (expr)
(reverse expr))
BACKWARDS
CL-USER> (backwards ("hello world" nil format))
"hello world"
CL-USER>
Clearly the above code can become complex since:
("hello world" nil format)
is not a valid Lisp expression.
Thanks to SK-logic's answer for pointing me in the direction of Alan Blackwell. I sent him an email asking his stance on the matter, and he responded with an absolutely wonderful explanation. Here it is:
So the person who responded to your StackOverflow question, saying
that flexible syntax could be useful for DSLs, is certainly correct.
It actually used to be fairly common to use the C preprocessor to
create alternative syntax (that would be turned into regular syntax in
an initial compile phase). A lot of the early esolangs were built this
way.
In practice, I think we would have to say that a lot of DSLs are
implemented as libraries within regular programming languages, and
that the library design is far more significant than the syntax. There
may be more purpose for having variety in visual languages, but making
customisable general purpose compilers for arbitrary graphical syntax
is really hard - much worse than changing text syntax features.
There may well be interesting things that your design could enable, so
I wouldn’t discourage experimentation. However, I think there is one reason why
customisable syntax is not so common. This is related to the famous
programmer’s editor EMACS. In EMACS, everything is customisable - all
key bindings, and all editor functions. It’s fun to play with, and
back in the day, many of us made our own personalised version that
only we knew how to operate. But it turned out that it was a real
hassle that everyone’s editor worked completely differently. You could
never lean over and make suggestions on another person’s session, and
teams always had to know who was logged in order to know whether the
editor would work. So it turned out that, over the years, we all just
started to use the default distribution and key bindings, which made
things easier for everyone.
At this point in time, that is just about enough of an explanation that I was looking for. If anyone feels as though they have a better explanation or something to add, feel free to contact me.
I'm writing a small tool for generating php checks from javascript code, and I would like to know if anyone knows of a standard way of transforming functional code into imperative code?
I found this paper: Defunctionalization at Work it explains defunctionalization pretty well.
Lambdalifting and defunctionalization somewhat answered the question, but what about datastructures, we are still parsing lists as if they are all linkedlists. Would there be a way of transforming the linkedlists of functional languages into other high-level datastructures like c++ vectors or java arraylists?
Here are a few additions to the list of #Artyom:
you can convert tail recursion into loops and assignments
linear types can be used to introduce assignments, e.g. y = f x can be replaced with x := f x if x is linear and has the same type as y
at least two kinds of defunctionalization are possible: Reynolds-type defunctionalization when you replace a high-order application with a switch full of first-order applications, and inlining (however, recursive functions is not always possible to inline)
Perhaps you are interested in removing some language elements (such as higher-order functions), right?
For eliminating HOFs from a program, there are techniques such as defunctionalization. For removing closures, you can use lambda-lifting (aka closure conversion). Is this something you are interested in?
I think you need to provide a concrete example of code you have, and the target code you intend to produce, so that others may propose solutions.
Added:
Would there be a way of transforming the linkedlists of functional languages into other high-level datastructures like c++ vectors or java arraylists?
Yes. Linked lists are represented with pointers in C++ (a structure "node" with two fields: one for the "payload", another for the "next" pointer; empty list is then represented as a NULL pointer, but sometimes people prefer to use special "sentinel values"). Note that, if the code in the source language does not rely on the representation of singly linked lists (in the source language implementation), you can also implement the "cons"/"nil" operations using a vector in the target language (not sure if this suits your needs, though). The idea here is to give an alternative implementations for the familiar operations.
No, there is not.
The reason is that there is no such concrete and well defined thing like functional code or imperative code.
Such transformations exist only for concrete instances of your abstraction: for example, there are transformations from Haskell code to LLVM bytecode, F# code to CLI bytecode or Frege code to Java code.
(I doubt if there is one from Javascript to PHP.)
Depends on what you need. The usual answer is "there is no such tool", because the result will not be usable. However look at this from this standpoint:
The set of Assembler instructions in a computer defines an imperative machine. Hence the compiler needs to do such a translation. However I assume you do not want to have assembler code but something more readable.
Usually these kinds of heavy program transformations are done manually, if one is interested in the result, or automatically if the result will never be looked at by a human.
This is a reopened question.
I look for a language and supporting platform for it, where the language could have pass-by-reference or pass-by-name semantics by default. I know the history a little, that there were Algol, Fortran and there still is C++ which could make it possible; but, basically, what I look for is something more modern and where the mentioned value pass methodology is preferred and by default (implicitly assumed).
I ask this question, because, to my mind, some of the advantages of pass-by-ref/name seem kind of obvious. For example when it is used in a standalone agent, where copyiong of values is not necessary (to some extent) and performance wouldn't be downgraded much in that case. So, I could employ it in e.g. rich client app or some game-style or standalone service-kind application.
The main advantage to me is the clear separation between identity of a symbol, and its current value. I mean when there is no reduntant copying, you know that you're working with the exact symbol/path you have queried/received. And intristing boxing of values will not interfere with the actual logic of program.
I know that there is C# ref keyword, but it's something not so intristic, though acceptable. Equally, I realize that pass-by-reference semantics could be simulated in virtually any language (Java as an instant example) and so on.. not sure about pass by name :)
What would you recommend - create a something like DSL for such needs wherever it be appropriate; or use some languages that I already know? Maybe, there is something that I'm missing?
Thank you!
UPDATE: Currently, I think that Haskell would be appropriate. But I didn't investigate much, so I think I'll update this text later.
Scala provides very flexible parameter passing semantics including real call-by-name:
def whileLoop(cond: => Boolean)(body: => Unit) {
if (cond) {
body
whileLoop(cond)(body)
}
}
And it really works
var i = 10
whileLoop (i > 0) {
println(i)
i -= 1
}
Technical details:
Though all parameters are passed by value (and these are usually references) much like Java, the notation => Type will make Scala generate the required closures automatically in order to emulate call-by-name.
Note that there is lazy evaluation too.
lazy val future = evalFunc()
The interesting thing is that you have consistent strict call-by-value semantics but can punctually change these where you really need to - nearly without any syntactic overhead.
Haskell has call-by-need as its default (and indeed only) evaluation strategy.
Now, you asked for two things: call-by-name and modern. Well, Haskell is a pure language and in a pure language call-by-name and call-by-need are semantically the same thing, or more precisely they always have the same result, the only difference being that call-by-need is usually faster and at worst only a constant factor slower than call-by-name. And Haskell surely is a modern language: it is merely 23 years old and in many of its features it is actually 10 years ahead of many languages that were created just recently.
The other thing you asked about is call-by-reference. Again, in a pure language, call-by-value and call-by-reference are the same thing, except that the latter is faster. (Which is why, even though most functional languages are usually described as being call-by-value, they actually implement call-by-reference.)
Now, call-by-name (and by extension call-by-need) are not the same thing as call-by-value (and by extension call-by-reference), because call-by-name may return a result in cases where call-by-value doesn't terminate.
However, in all cases where call-by-value or call-by-reference terminates, in a pure language, call-by-value, call-by-reference, call-by-name and call-by-need are the same thing. And in cases where they are not the same thing, call-by-name and call-by-need are in some sense "better", because they give you an answer in cases where call-by-value and call-by-reference would basically have run into an infinite loop.
Ergo, Haskell is your answer. Although probably not the one you were looking for :-)
Pass-by name is rare nowadays. However, you can simulate it in most functional programming languages using a lambda-nill:
// Pass by value
(dosomething (random))
// Pass by name hack
(dosomething (lambda () (random)))
Other then that: ML and O'CaML has a distinction between pass-by-value (default), pass-by-ref (using ref variables) and of course using lambdas. However, I'm not sure either of them qualifies as a "modern" language.
I'm not quite following your reasoning for why C#'s ref and out modifiers aren't "intrinsic." Seems to me that it provides almost exactly what you're looking for: A modern language and environment that supports pass-by-value and pass-by-reference. (As Little Bobby Tables pointed out, pass-by-name is very rare these days, you're better off with a lambda/closure.)
AFAIK, modern Fortran is pass-by-reference (preserving compatibility with ye olde FORTRAN).
Modern Fortran has all the niceties you expect of a modular language, so you can build just fine systems in it. Nobody does, because "Fortran is passe" and everybody wants to code in C# "because its cool.".
In Java, all objects are passed by reference.
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I keep hearing this term tossed around in several different contexts. What is it?
Declarative programming is when you write your code in such a way that it describes what you want to do, and not how you want to do it. It is left up to the compiler to figure out the how.
Examples of declarative programming languages are SQL and Prolog.
The other answers already do a fantastic job explaining what declarative programming is, so I'm just going to provide some examples of why that might be useful.
Context Independence
Declarative Programs are context-independent. Because they only declare what the ultimate goal is, but not the intermediary steps to reach that goal, the same program can be used in different contexts. This is hard to do with imperative programs, because they often depend on the context (e.g. hidden state).
Take yacc as an example. It's a parser generator aka. compiler compiler, an external declarative DSL for describing the grammar of a language, so that a parser for that language can automatically be generated from the description. Because of its context independence, you can do many different things with such a grammar:
Generate a C parser for that grammar (the original use case for yacc)
Generate a C++ parser for that grammar
Generate a Java parser for that grammar (using Jay)
Generate a C# parser for that grammar (using GPPG)
Generate a Ruby parser for that grammar (using Racc)
Generate a tree visualization for that grammar (using GraphViz)
simply do some pretty-printing, fancy-formatting and syntax highlighting of the yacc source file itself and include it in your Reference Manual as a syntactic specification of your language
And many more …
Optimization
Because you don't prescribe the computer which steps to take and in what order, it can rearrange your program much more freely, maybe even execute some tasks in parallel. A good example is a query planner and query optimizer for a SQL database. Most SQL databases allow you to display the query that they are actually executing vs. the query that you asked them to execute. Often, those queries look nothing like each other. The query planner takes things into account that you wouldn't even have dreamed of: rotational latency of the disk platter, for example or the fact that some completely different application for a completely different user just executed a similar query and the table that you are joining with and that you worked so hard to avoid loading is already in memory anyway.
There is an interesting trade-off here: the machine has to work harder to figure out how to do something than it would in an imperative language, but when it does figure it out, it has much more freedom and much more information for the optimization stage.
Loosely:
Declarative programming tends towards:-
Sets of declarations, or declarative statements, each of which has meaning (often in the problem domain) and may be understood independently and in isolation.
Imperative programming tends towards:-
Sequences of commands, each of which perform some action; but which may or may not have meaning in the problem domain.
As a result, an imperative style helps the reader to understand the mechanics of what the system is actually doing, but may give little insight into the problem that it is intended to solve. On the other hand, a declarative style helps the reader to understand the problem domain and the approach that the system takes towards the solution of the problem, but is less informative on the matter of mechanics.
Real programs (even ones written in languages that favor the ends of the spectrum, such as ProLog or C) tend to have both styles present to various degrees at various points, to satisfy the varying complexities and communication needs of the piece. One style is not superior to the other; they just serve different purposes, and, as with many things in life, moderation is key.
Here's an example.
In CSS (used to style HTML pages), if you want an image element to be 100 pixels high and 100 pixels wide, you simply "declare" that that's what you want as follows:
#myImageId {
height: 100px;
width: 100px;
}
You can consider CSS a declarative "style sheet" language.
The browser engine that reads and interprets this CSS is free to make the image appear this tall and this wide however it wants. Different browser engines (e.g., the engine for IE, the engine for Chrome) will implement this task differently.
Their unique implementations are, of course, NOT written in a declarative language but in a procedural one like Assembly, C, C++, Java, JavaScript, or Python. That code is a bunch of steps to be carried out step by step (and might include function calls). It might do things like interpolate pixel values, and render on the screen.
I am sorry, but I must disagree with many of the other answers. I would like to stop this muddled misunderstanding of the definition of declarative programming.
Definition
Referential transparency (RT) of the sub-expressions is the only required attribute of a declarative programming expression, because it is the only attribute which is not shared with imperative programming.
Other cited attributes of declarative programming, derive from this RT. Please click the hyperlink above for the detailed explanation.
Spreadsheet example
Two answers mentioned spreadsheet programming. In the cases where the spreadsheet programming (a.k.a. formulas) does not access mutable global state, then it is declarative programming. This is because the mutable cell values are the monolithic input and output of the main() (the entire program). The new values are not written to the cells after each formula is executed, thus they are not mutable for the life of the declarative program (execution of all the formulas in the spreadsheet). Thus relative to each other, the formulas view these mutable cells as immutable. An RT function is allowed to access immutable global state (and also mutable local state).
Thus the ability to mutate the values in the cells when the program terminates (as an output from main()), does not make them mutable stored values in the context of the rules. The key distinction is the cell values are not updated after each spreadsheet formula is performed, thus the order of performing the formulas does not matter. The cell values are updated after all the declarative formulas have been performed.
Declarative programming is the picture, where imperative programming is instructions for painting that picture.
You're writing in a declarative style if you're "Telling it what it is", rather than describing the steps the computer should take to get to where you want it.
When you use XML to mark-up data, you're using declarative programming because you're saying "This is a person, that is a birthday, and over there is a street address".
Some examples of where declarative and imperative programming get combined for greater effect:
Windows Presentation Foundation uses declarative XML syntax to describe what a user interface looks like, and what the relationships (bindings) are between controls and underlying data structures.
Structured configuration files use declarative syntax (as simple as "key=value" pairs) to identify what a string or value of data means.
HTML marks up text with tags that describe what role each piece of text has in relation to the whole document.
Declarative Programming is programming with declarations, i.e. declarative sentences. Declarative sentences have a number of properties that distinguish them from imperative sentences. In particular, declarations are:
commutative (can be reordered)
associative (can be regrouped)
idempotent (can repeat without change in meaning)
monotonic (declarations don't subtract information)
A relevant point is that these are all structural properties and are orthogonal to subject matter. Declarative is not about "What vs. How". We can declare (represent and constrain) a "how" just as easily as we declare a "what". Declarative is about structure, not content. Declarative programming has a significant impact on how we abstract and refactor our code, and how we modularize it into subprograms, but not so much on the domain model.
Often, we can convert from imperative to declarative by adding context. E.g. from "Turn left. (... wait for it ...) Turn Right." to "Bob will turn left at intersection of Foo and Bar at 11:01. Bob will turn right at the intersection of Bar and Baz at 11:06." Note that in the latter case the sentences are idempotent and commutative, whereas in the former case rearranging or repeating the sentences would severely change the meaning of the program.
Regarding monotonic, declarations can add constraints which subtract possibilities. But constraints still add information (more precisely, constraints are information). If we need time-varying declarations, it is typical to model this with explicit temporal semantics - e.g. from "the ball is flat" to "the ball is flat at time T". If we have two contradictory declarations, we have an inconsistent declarative system, though this might be resolved by introducing soft constraints (priorities, probabilities, etc.) or leveraging a paraconsistent logic.
Describing to a computer what you want, not how to do something.
imagine an excel page. With columns populated with formulas to calculate you tax return.
All the logic is done declared in the cells, the order of the calculation is by determine by formula itself rather than procedurally.
That is sort of what declarative programming is all about. You declare the problem space and the solution rather than the flow of the program.
Prolog is the only declarative language I've use. It requires a different kind of thinking but it's good to learn if just to expose you to something other than the typical procedural programming language.
I have refined my understanding of declarative programming, since Dec 2011 when I provided an answer to this question. Here follows my current understanding.
The long version of my understanding (research) is detailed at this link, which you should read to gain a deep understanding of the summary I will provide below.
Imperative programming is where mutable state is stored and read, thus the ordering and/or duplication of program instructions can alter the behavior (semantics) of the program (and even cause a bug, i.e. unintended behavior).
In the most naive and extreme sense (which I asserted in my prior answer), declarative programming (DP) is avoiding all stored mutable state, thus the ordering and/or duplication of program instructions can NOT alter the behavior (semantics) of the program.
However, such an extreme definition would not be very useful in the real world, since nearly every program involves stored mutable state. The spreadsheet example conforms to this extreme definition of DP, because the entire program code is run to completion with one static copy of the input state, before the new states are stored. Then if any state is changed, this is repeated. But most real world programs can't be limited to such a monolithic model of state changes.
A more useful definition of DP is that the ordering and/or duplication of programming instructions do not alter any opaque semantics. In other words, there are not hidden random changes in semantics occurring-- any changes in program instruction order and/or duplication cause only intended and transparent changes to the program's behavior.
The next step would be to talk about which programming models or paradigms aid in DP, but that is not the question here.
It's a method of programming based around describing what something should do or be instead of describing how it should work.
In other words, you don't write algorithms made of expressions, you just layout how you want things to be. Two good examples are HTML and WPF.
This Wikipedia article is a good overview: http://en.wikipedia.org/wiki/Declarative_programming
Since I wrote my prior answer, I have formulated a new definition of the declarative property which is quoted below. I have also defined imperative programming as the dual property.
This definition is superior to the one I provided in my prior answer, because it is succinct and it is more general. But it may be more difficult to grok, because the implication of the incompleteness theorems applicable to programming and life in general are difficult for humans to wrap their mind around.
The quoted explanation of the definition discusses the role pure functional programming plays in declarative programming.
Declarative vs. Imperative
The declarative property is weird, obtuse, and difficult to capture in a technically precise definition that remains general and not ambiguous, because it is a naive notion that we can declare the meaning (a.k.a semantics) of the program without incurring unintended side effects. There is an inherent tension between expression of meaning and avoidance of unintended effects, and this tension actually derives from the incompleteness theorems of programming and our universe.
It is oversimplification, technically imprecise, and often ambiguous to define declarative as “what to do” and imperative as “how to do”. An ambiguous case is the “what” is the “how” in a program that outputs a program— a compiler.
Evidently the unbounded recursion that makes a language Turing complete, is also analogously in the semantics— not only in the syntactical structure of evaluation (a.k.a. operational semantics). This is logically an example analogous to Gödel's theorem— “any complete system of axioms is also inconsistent”. Ponder the contradictory weirdness of that quote! It is also an example that demonstrates how the expression of semantics does not have a provable bound, thus we can't prove2 that a program (and analogously its semantics) halt a.k.a. the Halting theorem.
The incompleteness theorems derive from the fundamental nature of our universe, which as stated in the Second Law of Thermodynamics is “the entropy (a.k.a. the # of independent possibilities) is trending to maximum forever”. The coding and design of a program is never finished— it's alive!— because it attempts to address a real world need, and the semantics of the real world are always changing and trending to more possibilities. Humans never stop discovering new things (including errors in programs ;-).
To precisely and technically capture this aforementioned desired notion within this weird universe that has no edge (ponder that! there is no “outside” of our universe), requires a terse but deceptively-not-simple definition which will sound incorrect until it is explained deeply.
Definition:
The declarative property is where there can exist only one possible set of statements that can express each specific modular semantic.
The imperative property3 is the dual, where semantics are inconsistent under composition and/or can be expressed with variations of sets of statements.
This definition of declarative is distinctively local in semantic scope, meaning that it requires that a modular semantic maintain its consistent meaning regardless where and how it's instantiated and employed in global scope. Thus each declarative modular semantic should be intrinsically orthogonal to all possible others— and not an impossible (due to incompleteness theorems) global algorithm or model for witnessing consistency, which is also the point of “More Is Not Always Better” by Robert Harper, Professor of Computer Science at Carnegie Mellon University, one of the designers of Standard ML.
Examples of these modular declarative semantics include category theory functors e.g. the Applicative, nominal typing, namespaces, named fields, and w.r.t. to operational level of semantics then pure functional programming.
Thus well designed declarative languages can more clearly express meaning, albeit with some loss of generality in what can be expressed, yet a gain in what can be expressed with intrinsic consistency.
An example of the aforementioned definition is the set of formulas in the cells of a spreadsheet program— which are not expected to give the same meaning when moved to different column and row cells, i.e. cell identifiers changed. The cell identifiers are part of and not superfluous to the intended meaning. So each spreadsheet result is unique w.r.t. to the cell identifiers in a set of formulas. The consistent modular semantic in this case is use of cell identifiers as the input and output of pure functions for cells formulas (see below).
Hyper Text Markup Language a.k.a. HTML— the language for static web pages— is an example of a highly (but not perfectly3) declarative language that (at least before HTML 5) had no capability to express dynamic behavior. HTML is perhaps the easiest language to learn. For dynamic behavior, an imperative scripting language such as JavaScript was usually combined with HTML. HTML without JavaScript fits the declarative definition because each nominal type (i.e. the tags) maintains its consistent meaning under composition within the rules of the syntax.
A competing definition for declarative is the commutative and idempotent properties of the semantic statements, i.e. that statements can be reordered and duplicated without changing the meaning. For example, statements assigning values to named fields can be reordered and duplicated without changed the meaning of the program, if those names are modular w.r.t. to any implied order. Names sometimes imply an order, e.g. cell identifiers include their column and row position— moving a total on spreadsheet changes its meaning. Otherwise, these properties implicitly require global consistency of semantics. It is generally impossible to design the semantics of statements so they remain consistent if randomly ordered or duplicated, because order and duplication are intrinsic to semantics. For example, the statements “Foo exists” (or construction) and “Foo does not exist” (and destruction). If one considers random inconsistency endemical of the intended semantics, then one accepts this definition as general enough for the declarative property. In essence this definition is vacuous as a generalized definition because it attempts to make consistency orthogonal to semantics, i.e. to defy the fact that the universe of semantics is dynamically unbounded and can't be captured in a global coherence paradigm.
Requiring the commutative and idempotent properties for the (structural evaluation order of the) lower-level operational semantics converts operational semantics to a declarative localized modular semantic, e.g. pure functional programming (including recursion instead of imperative loops). Then the operational order of the implementation details do not impact (i.e. spread globally into) the consistency of the higher-level semantics. For example, the order of evaluation of (and theoretically also the duplication of) the spreadsheet formulas doesn't matter because the outputs are not copied to the inputs until after all outputs have been computed, i.e. analogous to pure functions.
C, Java, C++, C#, PHP, and JavaScript aren't particularly declarative.
Copute's syntax and Python's syntax are more declaratively coupled to
intended results, i.e. consistent syntactical semantics that eliminate the extraneous so one can readily
comprehend code after they've forgotten it. Copute and Haskell enforce
determinism of the operational semantics and encourage “don't repeat
yourself” (DRY), because they only allow the pure functional paradigm.
2 Even where we can prove the semantics of a program, e.g. with the language Coq, this is limited to the semantics that are expressed in the typing, and typing can never capture all of the semantics of a program— not even for languages that are not Turing complete, e.g. with HTML+CSS it is possible to express inconsistent combinations which thus have undefined semantics.
3 Many explanations incorrectly claim that only imperative programming has syntactically ordered statements. I clarified this confusion between imperative and functional programming. For example, the order of HTML statements does not reduce the consistency of their meaning.
Edit: I posted the following comment to Robert Harper's blog:
in functional programming ... the range of variation of a variable is a type
Depending on how one distinguishes functional from imperative
programming, your ‘assignable’ in an imperative program also may have
a type placing a bound on its variability.
The only non-muddled definition I currently appreciate for functional
programming is a) functions as first-class objects and types, b)
preference for recursion over loops, and/or c) pure functions— i.e.
those functions which do not impact the desired semantics of the
program when memoized (thus perfectly pure functional
programming doesn't exist in a general purpose denotational semantics
due to impacts of operational semantics, e.g. memory
allocation).
The idempotent property of a pure function means the function call on
its variables can be substituted by its value, which is not generally
the case for the arguments of an imperative procedure. Pure functions
seem to be declarative w.r.t. to the uncomposed state transitions
between the input and result types.
But the composition of pure functions does not maintain any such
consistency, because it is possible to model a side-effect (global
state) imperative process in a pure functional programming language,
e.g. Haskell's IOMonad and moreover it is entirely impossible to
prevent doing such in any Turing complete pure functional programming
language.
As I wrote in 2012 which seems to the similar consensus of
comments in your recent blog, that declarative programming is an
attempt to capture the notion that the intended semantics are never
opaque. Examples of opaque semantics are dependence on order,
dependence on erasure of higher-level semantics at the operational
semantics layer (e.g. casts are not conversions and reified generics
limit higher-level semantics), and dependence on variable values
which can not be checked (proved correct) by the programming language.
Thus I have concluded that only non-Turing complete languages can be
declarative.
Thus one unambiguous and distinct attribute of a declarative language
could be that its output can be proven to obey some enumerable set of
generative rules. For example, for any specific HTML program (ignoring
differences in the ways interpreters diverge) that is not scripted
(i.e. is not Turing complete) then its output variability can be
enumerable. Or more succinctly an HTML program is a pure function of
its variability. Ditto a spreadsheet program is a pure function of its
input variables.
So it seems to me that declarative languages are the antithesis of
unbounded recursion, i.e. per Gödel's second incompleteness
theorem self-referential theorems can't be proven.
Lesie Lamport wrote a fairytale about how Euclid might have
worked around Gödel's incompleteness theorems applied to math proofs
in the programming language context by to congruence between types and
logic (Curry-Howard correspondence, etc).
Declarative programming is "the act of programming in languages that conform to the mental model of the developer rather than the operational model of the machine".
The difference between declarative and imperative programming is well
illustrated by the problem of parsing structured data.
An imperative program would use mutually recursive functions to consume input
and generate data. A declarative program would express a grammar that defines
the structure of the data so that it can then be parsed.
The difference between these two approaches is that the declarative program
creates a new language that is more closely mapped to the mental model of the
problem than is its host language.
It may sound odd, but I'd add Excel (or any spreadsheet really) to the list of declarative systems. A good example of this is given here.
I'd explain it as DP is a way to express
A goal expression, the conditions for - what we are searching for. Is there one, maybe or many?
Some known facts
Rules that extend the know facts
...and where there is a deduct engine usually working with a unification algorithm to find the goals.
As far as I can tell, it started being used to describe programming systems like Prolog, because prolog is (supposedly) about declaring things in an abstract way.
It increasingly means very little, as it has the definition given by the users above. It should be clear that there is a gulf between the declarative programming of Haskell, as against the declarative programming of HTML.
A couple other examples of declarative programming:
ASP.Net markup for databinding. It just says "fill this grid with this source", for example, and leaves it to the system for how that happens.
Linq expressions
Declarative programming is nice because it can help simplify your mental model* of code, and because it might eventually be more scalable.
For example, let's say you have a function that does something to each element in an array or list. Traditional code would look like this:
foreach (object item in MyList)
{
DoSomething(item);
}
No big deal there. But what if you use the more-declarative syntax and instead define DoSomething() as an Action? Then you can say it this way:
MyList.ForEach(DoSometing);
This is, of course, more concise. But I'm sure you have more concerns than just saving two lines of code here and there. Performance, for example. The old way, processing had to be done in sequence. What if the .ForEach() method had a way for you to signal that it could handle the processing in parallel, automatically? Now all of a sudden you've made your code multi-threaded in a very safe way and only changed one line of code. And, in fact, there's a an extension for .Net that lets you do just that.
If you follow that link, it takes you to a blog post by a friend of mine. The whole post is a little long, but you can scroll down to the heading titled "The Problem" _and pick it up there no problem.*
It depends on how you submit the answer to the text. Overall you can look at the programme at a certain view but it depends what angle you look at the problem. I will get you started with the programme:
Dim Bus, Car, Time, Height As Integr
Again it depends on what the problem is an overall. You might have to shorten it due to the programme. Hope this helps and need the feedback if it does not.
Thank You.