In C#, all the value fields like int, float are kept in stack and all the reference variables pointers are in stack and the actual values are kept in heap. (hope my understanding is correct here).
1. Since in functional programming model there is no value and reference type, where do the name symbol values are kept?
2.How does the stack and heap come into play on functional programs?
Thanks
You're trying to compare C#, which is one specific language, with functional languages all as a group. This is an apples-to-oranges comparison (or maybe more accurately, apples-to-spices comparison?).
Within imperative languages already you can observe differences between what values are stored in the stack vs. which ones go on the heap. For example, C and C++ (as I understand it) allow the programmer to manually choose which of these two ways they want for any type.
And another subtlety is the difference between what the language guarantees to the programmer vs. the way the language is implemented. One example is that recent versions of Oracle's Java VM have an optimization that they call "escape analysis", which is able to allocate an object on the stack if the VM can prove that the object reference does not escape the method (determined after inlining is performed). So even though Java calls its object types "reference" types, this doesn't mean that it will be allocated in the heap. Quoting this article by Brian Goetz:
The Java language does not offer any way to explicitly allocate an object on the stack, but this fact doesn't prevent JVMs from still using stack allocation where appropriate. JVMs can use a technique called escape analysis, by which they can tell that certain objects remain confined to a single thread for their entire lifetime, and that lifetime is bounded by the lifetime of a given stack frame. Such objects can be safely allocated on the stack instead of the heap. Even better, for small objects, the JVM can optimize away the allocation entirely and simply hoist the object's fields into registers.
Similar considerations apply to functional languages—it all depends on (a) what does the language promise, and (b) how the language implementation works and how sophisticated it is. But we can divide the functional language world into two important camps:
Eager functional languages like Scheme, Scala, Clojure or ML.
Lazy functional languages like Haskell.
There are several types of implementation for eager languages:
Pure stack-based implementations. These work same way as modern imperative languages. Common Lisp works this way. Since JVM functional languages use the same VM as Java does, so do they.
Pure continuation-passing style implementations. These are completely stackless—everything, including activation frames, is allocated on the heap. These make it easy to support tail-call optimization and first-class continuations. This technique I believe was pioneered by Scheme implementations, and is also used by the Standard ML of New Jersey compiler.
Mixed implementations. These typically are trying to be mostly stack-based but also support tail-call optimization, and maybe first-class continuations. Example: a bunch of random Scheme systems.
Lazy languages are another story, because the conventional call-stack implementation does not translate directly to lazy evaluation. The GHC Haskell compiler is based on a model called the "STG Machine", which does use a stack and a heap, but the way the STG stack works is different from imperative languages; an entry in the STG stack does not correspond to a "function call" as conventional stack entries do.
Since functional languages generally use immutable values (meaning: "variables" that you can't modify), it doesn't matter for the user whether the values are stored on the stack or on the heap.
Because of this, typically the compiler will decide how to store the values. For example, it might decide that small values (integers, floats, pairs of integers, 8 byte arrays, etc) are stored on the stack and large values (strings, lists, ...) are stored on the heap. It is fully the compiler's decision.
For languages like Haskell, that supports lazy evaluation, values need to be stored on the heap (except when some tricks are used). This is because a variable needs to either be a pointer to the function/closure that computes the value, or a pointer to the actual already computed value.
Since Scala is mentioned in the tags, I'll add and answer about that language. Scala compiles to JVM bytecode, so, at the end of the day, it works just like any other JVM language (including Java):
references and locally defined primitives go on the stack;
objects (including their primitive fields) go on the heap.
About primitive types, it's worth noting that Scala doesn't actually have primitive types in the language; but value types (like Int or Long) do get compiled to the JVM's primitive types in the bytecode, when possible.
edit: To avoid leaving somethign incorrect in this answer: as mentioned in Luis Casillas' extensive answer, objects may end up stored on the stack (or even not allocated as objects at all) if the JVM can judge that it's safe and efficient to do so.
Related
In Java, within a method when we create primitives they are stored in stack memory, while objects instantiated (like using new) are put on heap. In scala, AnyVal’s subtypes(like Int) are immutable value instances that can’t be instantiated. So if I create an Int in a Scala method, does it go to heap or stack. I am asking it because in Scala Int is an object.
The Scala Language Specification does not say anything about how memory is organized. Every implementation is free to organize its memory however it wants.
By the way, your statements about Java are wrong:
In Java, within a method when we create primitives they are stored in stack memory,
There is nothing in the Java Language Specification which says that. And in fact, for many implementations, this isn't true. For example, Oracle JDK's implementation will try to store primitives in registers, or elide them completely, instead of storing them on the stack.
while objects instantiated (like using 'new') are put on heap.
Again, there is nothing in the Java Language Specification which says that. And again, for example in Oracle's implementation, this is not necessarily true. Oracle's optimizing compilers will perform Escape Analysis and allocate objects on the stack whenever possible, i.e. when the compiler can prove that the reference doesn't escape the scope. Azul's implementation always allocates objects on the stack (unless it can prove that the reference will definitely escape the local scope), and performs Escape Detection, i.e. when it detects a reference escaping the local scope, it will move the object from the stack to the heap.
In fact, you can implement Java without a stack at all, and be perfectly compliant with the Java Language Specification.
In scala, AnyVal’s subtypes(like Int) are immutable value instances that can’t be instantiated. So if I create an Int in a Scala method, does it go to heap or stack.
That depends on the implementation, the version, the specific circumstances, and many other things. The Scala Language Specification doesn't say one way or the other, in fact, it doesn't say anything about how to memory, let alone about stack and heap.
I am asking it because in Scala Int is an object.
But again, that doesn't say anything about how it is implemented. Scala-JVM, for example, implements scala.Int as a JVM primitive, and then simply "fakes" the methods.
I am learning some Typed Racket at the moment and i have a somewhat philosophical dilemma:
Racket claims to be a language development framework and Typed Racket is one such languages implemented on top of it. The documentation mentions that due to types being used, the compiler now can do more/better optimizations.
The concrete question:
Where do these optimizations happen?
1) In the compile/expand part (which is "programmable" as part of the language building framework)
-or-
2) further down the line in the (bytecode) optimizer (which is written in C and not directly modifieable via the framework).
If 2) is true, does that mean the type information is lost after the compile/expand stage and later "rebuilt/guessed" by the optimizer or has the intermediate representation been altered to to accomodate the type information and inform later stages about them?
The reason i am asking this specific question is because i want to get a feeling for how general the Racket language framework really is, i.e. is also viable for statically typed languages without any modifications in the backend versus the type system being only a front-end thing, while the code at runtime is still dynamically typed (but statically checked of course).
Thank you.
Typed Racket's optimizations occur during macro expansion. To see for yourself, you can change #lang typed/racket to #lang typed/racket #:no-optimize, which shows Typed Racket is in complete control of what optimizations are applied.
The optimizations consist of using type information to replace various uses of certain procedures with their unsafe equivalents. The unsafe procedures perform no runtime checks on the types of their arguments and cause undefined behavior (read: segfaults) if used incorrectly. You can find out more in the documentation section entitled Optimization in Typed Racket.
The exposure of the unsafe variants of procedures is what really makes it possible for user-defined languages to implement these optimizations. For example, if you wrote your own language with a type system that could prove vectors were never accessed with out-of-bounds indices you could replaces uses of vector-ref with unsafe-vector-ref.
There are similar optimizations that occur at the bytecode level, but these mostly apply when the JIT can infer type information that's not visible at macro expansion time. These are not user-controlled, but you don't have to rely on them.
The title might be a little confusing so let me elaborate, I've been reading some criticism regarding Scala. It was an email sent to Tyepsafe regarding some deficiencies in Scala from Coda Hale (Yammer's Infrastructure Architect), so to quote:
we stopped seeing lambdas as free and started seeing them as syntactic sugar on top of anonymous classes and thus acquired the same distaste for them as we did anonymous classes.
So, from this, I have a couple of questions regarding how lambdas work in Scala:
What is the difference between a free function and a function that is bound to an anonymous class (technically, aren't all functions bound to the main singleton object)?
What is the impact on performance of using an anonymous class bound function instead of a free function?
Yes, lambdas are still objects, instances of anonymous classes.
This is how the JVM works, all references are objects. You can have either references or values (primitives) and there's no way around it.
Later versions of Java have MethodHandles. But it's worth noting that MethodHandle is also still just an abstract class - albeit one that the JVM specifically knows how to optimise away at runtime.
Also also worth noting is that the JVM can often perform escape analysis on abstract classes (such as Scala's functions), and optimise these away too.
On top of this, Scala can use any object with an apply method as though it were a Function. In this case, the explicit call to apply is emitted in the bytecode and you're not dealing with anonymous classes any more.
Given all of the above, it's impossible to make a general statement regarding the performance of Scala's function implementation, it depends on your specific code/use case. In general, I wouldn't worry unless you hit a corner case where your profiler pinpoints a problem here (which is very unlikely)
Well, in C for example a function is just a 32 or 64 bit pointer to a place in memory to jump to and the concept of a closure doesn't really apply since you can't declare an anonymous c function. I don't know how the C++ lambdas work, I guess the compiler makes a method and passes the fields you want in the closure along with parameters. Maybe that's what you're looking for. In the JVM you have to wrap your logic in a class so now you have a virtual table of methods, fields, and some methods related to synchronization and the type system.
What is the impact on performance?...I don't know, have you noticed an impact on performance? A lot of that extra Java stuff I described really isn't needed for an anonymous class and might just get optimized out. I imagine there are butterflies that influence the weather more than the extra JVM stuff would effect your software.
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What are the most commonly held misconceptions about the Scala language, and what counter-examples exist to these?
UPDATE
I was thinking more about various claims I've seen, such as "Scala is dynamically typed" and "Scala is a scripting language".
I accept that "Scala is [Simple/Complex]" might be considered a myth, but it's also a viewpoint that's very dependent on context. My personal belief is that it's the very same features that can make Scala appear either simple or complex depending oh who's using them. Ultimately, the language just offers abstractions, and it's the way that these are used that shapes perceptions.
Not only that, but it has a certain tendency to inflame arguments, and I've not yet seen anyone change a strongly-held viewpoint on the topic...
Myth: That Scala’s “Option” and Haskell’s “Maybe” types won’t save you from null. :-)
Debunked: Why Scala's "Option" and Haskell's "Maybe" types will save you from null by James Iry.
Myth: Scala supports operator overloading.
Actually, Scala just has very flexible method naming rules and infix syntax for method invocation, with special rules for determining method precedence when the infix syntax is used with 'operators'. This subtle distinction has critical implications for the utility and potential for abuse of this language feature compared to true operator overloading (a la C++), as explained more thoroughly in James Iry's answer to this question.
Myth: methods and functions are the same thing.
In fact, a function is a value (an instance of one of the FunctionN classes), while a method is not. Jim McBeath explains the differences in greater detail. The most important practical distinctions are:
Only methods can have type parameters
Only methods can take implicit arguments
Only methods can have named and default parameters
When referring to a method, an underscore is often necessary to distinguish method invocation from partial function application (e.g. str.length evaluates to a number, while str.length _ evaluates to a zero-argument function).
I disagree with the argument that Scala is hard because you can use very advanced features to do hard stuff with it. The scalability of Scala means that you can write DSL abstractions and high-level APIs in Scala itself that otherwise would need a language extension. So to be fair you need to compare Scala libraries to other languages compilers. People don't say that C# is hard because (I assume, don't have first hand knowledge on this) the C# compiler is pretty impenetrable. For Scala it's all out in the open. But we need to get to a point where we make clear that most people don't need to write code on this level, nor should they do it.
I think a common misconception amongst many scala developers, those at EPFL (and yourself, Kevin) is that "scala is a simple language". The argument usually goes something like this:
scala has few keywords
scala reuses the same few constructs (e.g. PartialFunction syntax is used as the body of a catch block)
scala has a few simple rules which allow you to create library code (which may appear as if the language has special keywords/constructs). I'm thinking here of implicits; methods containing colons; allowed identifier symbols; the equivalence of X(a, b) and a X b with extractors. And so on
scala's declaration-site variance means that the type system just gets out of your way. No more wildcards and ? super T
My personal opinion is that this argument is completely and utterly bogus. Scala's type system taken together with implicits allows one to write frankly impenetrable code for the average developer. Any suggestion otherwise is just preposterous, regardless of what the above "metrics" might lead you to think. (Note here that those who I've seen scoffing at the non-complexity of Java on Twitter and elsewhere happen to be uber-clever types who, it sometimes seems, had a grasp of monads, functors and arrows before they were out of short pants).
The obvious arguments against this are (of course):
you don't have to write code like this
you don't have to pander to the average developer
Of these, it seems to me that only #2 is valid. Whether or not you write code quite as complex as scalaz, I think it's just silly to use the language (and continue to use it) with no real understanding of the type system. How else can one get the best out of the language?
There is a myth that Scala is difficult because Scala is a complex language.
This is false--by a variety of metrics, Scala is no more complex than Java. (Size of grammar, lines of code or number of classes or number of methods in the standard API, etc..)
But it is undeniably the case that Scala code can be ferociously difficult to understand. How can this be, if Scala is not a complex language?
The answer is that Scala is a powerful language. Unlike Java, which has many special constructs (like enums) that accomplish one particular thing--and requires you to learn specialized syntax that applies just to that one thing, Scala has a variety of very general constructs. By mixing and matching these constructs, one can express very complex ideas with very little code. And, unsurprisingly, if someone comes along who has not had the same complex idea and tries to figure out what you're doing with this very compact code, they may find it daunting--more daunting, even, than if they saw a couple of pages of code to do the same thing, since then at least they'd realize how much conceptual stuff there was to understand!
There is also an issue of whether things are more complex than they really need to be. For example, some of the type gymnastics present in the collections library make the collections a joy to use but perplexing to implement or extend. The goals here are not particularly complicated (e.g. subclasses should return their own types), but the methods required (higher-kinded types, implicit builders, etc.) are complex. (So complex, in fact, that Java just gives up and doesn't try, rather than doing it "properly" as in Scala. Also, in principle, there is hope that this will improve in the future, since the method can evolve to more closely match the goal.) In other cases, the goals are complex; list.filter(_<5).sorted.grouped(10).flatMap(_.tail.headOption) is a bit of a mess, but if you really want to take all numbers less than 5, and then take every 2nd number out of 10 in the remaining list, well, that's just a somewhat complicated idea, and the code pretty much says what it does if you know the basic collections operations.
Summary: Scala is not complex, but it allows you to compactly express complex ideas. Compact expression of complex ideas can be daunting.
There is a myth that Scala is non-deployable, whereas a wide range of third-party Java libraries can be deployed without a second thought.
To the extent that this myth exists, I suspect it exists among people who are not accustomed to separating a virtual machine and API from a language and compiler. If java == javac == Java API in your mind, you might get a little nervous if someone suggests using scalac instead of javac, because you see how nicely your JVM runs.
Scala ends up as JVM bytecode, plus its own custom library. There's no reason to be any more worried about deploying Scala on a small scale or as part of some other large project as there is in deploying any other library that may or may not stay compatible with whichever JVM you prefer. Granted, the Scala development team is not backed by quite as much force as the Google collections, or Apache Commons, but its got at least as much weight behind it as things like the Java Advanced Imaging project.
Myth:
def foo() = "something"
and
def bar = "something"
is the same.
It is not; you can call foo(), but bar() tries to call the apply method of StringLike with no arguments (results in an error).
Some common misconceptions related to Actors library:
Actors handle incoming messages in a parallel, in multiple threads / against a thread pool (in fact, handling messages in multiple threads is contrary to the actors concept and may lead to racing conditions - all messages are sequentially handled in one thread (thread-based actors use one thread both for mailbox processing and execution; event-based actors may share one VM thread for execution, using multi-threaded executor to schedule mailbox processing))
Uncaught exceptions don't change actor's behavior/state (in fact, all uncaught exceptions terminate the actor)
Myth: You can replace a fold with a reduce when computing something like a sum from zero.
This is a common mistake/misconception among new users of Scala, particularly those without prior functional programming experience. The following expressions are not equivalent:
seq.foldLeft(0)(_+_)
seq.reduceLeft(_+_)
The two expressions differ in how they handle the empty sequence: the fold produces a valid result (0), while the reduce throws an exception.
Myth: Pattern matching doesn't fit well with the OO paradigm.
Debunked here by Martin Odersky himself. (Also see this paper - Matching Objects with Patterns - by Odersky et al.)
Myth: this.type refers to the same type represented by this.getClass.
As an example of this misconception, one might assume that in the following code the type of v.me is B:
trait A { val me: this.type = this }
class B extends A
val v = new B
In reality, this.type refers to the type whose only instance is this. In general, x.type is the singleton type whose only instance is x. So in the example above, the type of v.me is v.type. The following session demonstrates the principle:
scala> val s = "a string"
s: java.lang.String = a string
scala> var v: s.type = s
v: s.type = a string
scala> v = "another string"
<console>:7: error: type mismatch;
found : java.lang.String("another string")
required: s.type
v = "another string"
Scala has type inference and refinement types (structural types), whereas Java does not.
The myth is busted by James Iry.
Myth: that Scala is highly scalable, without qualifying what forms of scalability.
Scala may indeed be highly scalable in terms of the ability to express higher-level denotational semantics, and this makes it a very good language for experimentation and even for scaling production at the project-level scale of top-down coordinated compositionality.
However, every referentially opaque language (i.e. allows mutable data structures), is imperative (and not declarative) and will not scale to WAN bottom-up, uncoordinated compositionality and security. In other words, imperative languages are compositional (and security) spaghetti w.r.t. uncoordinated development of modules. I realize such uncoordinated development is perhaps currently considered by most to be a "pipe dream" and thus perhaps not a high priority. And this is not to disparage the benefit to compositionality (i.e. eliminating corner cases) that higher-level semantic unification can provide, e.g. a category theory model for standard library.
There will possibly be significant cognitive dissonance for many readers, especially since there are popular misconceptions about imperative vs. declarative (i.e. mutable vs. immutable), (and eager vs. lazy,) e.g. the monadic semantic is never inherently imperative yet there is a lie that it is. Yes in Haskell the IO monad is imperative, but it being imperative has nothing to with it being a monad.
I explained this in more detail in the "Copute Tutorial" and "Purity" sections, which is either at the home page or temporarily at this link.
My point is I am very grateful Scala exists, but I want to clarify what Scala scales and what is does not. I need Scala for what it does well, i.e. for me it is the ideal platform to prototype a new declarative language, but Scala itself is not exclusively declarative and afaik referential transparency can't be enforced by the Scala compiler, other than remembering to use val everywhere.
I think my point applies to the complexity debate about Scala. I have found (so far and mostly conceptually, since so far limited in actual experience with my new language) that removing mutability and loops, while retaining diamond multiple inheritance subtyping (which Haskell doesn't have), radically simplifies the language. For example, the Unit fiction disappears, and afaics, a slew of other issues and constructs become unnecessary, e.g. non-category theory standard library, for comprehensions, etc..
With the growth of dynamically typed languages, as they give us more flexibility, there is the very likely probability that people will write programs that go beyond what the specification allows.
My thinking was influenced by this question, when I read the answer by bobince:
A question about JavaScript's slice and splice methods
The basic thought is that splice, in Javascript, is specified to be used in only certain situations, but, it can be used in others, and there is nothing that the language can do to stop it, as the language is designed to be extremely flexible.
Unless someone reads through the specification, and decides to adhere to it, I am fairly certain that there are many such violations occuring.
Is this a problem, or a natural extension of writing such flexible languages? Or should we expect tools like JSLint to help be the specification police?
I liked one answer in this question, that the implementation of python is the specification. I am curious if that is actually closer to the truth for these types of languages, that basically, if the language allows you to do something then it is in the specification.
Is there a Python language specification?
UPDATE:
After reading a couple of comments, I thought I would check the splice method in the spec and this is what I found, at the bottom of pg 104, http://www.mozilla.org/js/language/E262-3.pdf, so it appears that I can use splice on the array of children without violating the spec. I just don't want people to get bogged down in my example, but hopefully to consider the question.
The splice function is intentionally generic; it does not require that its this value be an Array object.
Therefore it can be transferred to other kinds of objects for use as a method. Whether the splice function
can be applied successfully to a host object is implementation-dependent.
UPDATE 2:
I am not interested in this being about javascript, but language flexibility and specs. For example, I expect that the Java spec specifies you can't put code into an interface, but using AspectJ I do that frequently. This is probably a violation, but the writers didn't predict AOP and the tool was flexible enough to be bent for this use, just as the JVM is also flexible enough for Scala and Clojure.
Whether a language is statically or dynamically typed is really a tiny part of the issue here: a statically typed one may make it marginally easier for code to enforce its specs, but marginally is the key word here. Only "design by contract" -- a language letting you explicitly state preconditions, postconditions and invariants, and enforcing them -- can help ward you against users of your libraries empirically discovering what exactly the library will let them get away with, and taking advantage of those discoveries to go beyond your design intentions (possibly constraining your future freedom in changing the design or its implementation). And "design by contract" is not supported in mainstream languages -- Eiffel is the closest to that, and few would call it "mainstream" nowadays -- presumably because its costs (mostly, inevitably, at runtime) don't appear to be justified by its advantages. "Argument x must be a prime number", "method A must have been previously called before method B can be called", "method C cannot be called any more once method D has been called", and so on -- the typical kinds of constraints you'd like to state (and have enforced implicitly, without having to spend substantial programming time and energy checking for them yourself) just don't lend themselves well to be framed in the context of what little a statically typed language's compiler can enforce.
I think that this sort of flexibility is an advantage as long as your methods are designed around well defined interfaces rather than some artificial external "type" metadata. Most of the array functions only expect an object with a length property. The fact that they can all be applied generically to lots of different kinds of objects is a boon for code reuse.
The goal of any high level language design should be to reduce the amount of code that needs to be written in order to get stuff done- without harming readability too much. The more code that has to be written, the more bugs get introduced. Restrictive type systems can be, (if not well designed), a pervasive lie at worst, a premature optimisation at best. I don't think overly restrictive type systems aid in writing correct programs. The reason being that the type is merely an assertion, not necessarily based on evidence.
By contrast, the array methods examine their input values to determine whether they have what they need to perform their function. This is duck typing, and I believe that this is more scientific and "correct", and it results in more reusable code, which is what you want. You don't want a method rejecting your inputs because they don't have their papers in order. That's communism.
I do not think your question really has much to do with dynamic vs. static typing. Really, I can see two cases: on one hand, there are things like Duff's device that martin clayton mentioned; that usage is extremely surprising the first time you see it, but it is explicitly allowed by the semantics of the language. If there is a standard, that kind of idiom may appear in later editions of the standard as a specific example. There is nothing wrong with these; in fact, they can (unless overused) be a great productivity boost.
The other case is that of programming to the implementation. Such a case would be an actual abuse, coming from either ignorance of a standard, or lack of a standard, or having a single implementation, or multiple implementations that have varying semantics. The problem is that code written in this way is at best non-portable between implementations and at worst limits the future development of the language, for fear that adding an optimization or feature would break a major application.
It seems to me that the original question is a bit of a non-sequitor. If the specification explicitly allows a particular behavior (as MUST, MAY, SHALL or SHOULD) then anything compiler/interpreter that allows/implements the behavior is, by definition, compliant with the language. This would seem to be the situation proposed by the OP in the comments section - the JavaScript specification supposedly* says that the function in question MAY be used in different situations, and thus it is explicitly allowed.
If, on the other hand, a compiler/interpreter implements or allows behavior that is expressly forbidden by a specification, then the compiler/interpreter is, by definition, operating outside the specification.
There is yet a third scenario, and an associated, well defined, term for those situations where the specification does not define a behavior: undefined. If the specification does not actually specify a behavior given a particular situation, then the behavior is undefined, and may be handled either intentionally or unintentionally by the compiler/interpreter. It is then the responsibility of the developer to realize that the behavior is not part of the specification, and, should s/he choose to leverage the behavior, the developer's application is thereby dependent upon the particular implementation. The interpreter/compiler providing that implementation is under no obligation to maintain the officially undefined behavior beyond backwards compatibility and whatever commitments the producer may make. Furthermore, a later iteration of the language specification may define the previously undefined behavior, making the compiler/interpreter either (a) non-compliant with the new iteration, or (b) come out with a new patch/version to become compliant, thereby breaking older versions.
* "supposedly" because I have not seen the spec, myself. I go by the statements made, above.