In Java and C++ designing program's objects hierarchy is pretty obvious. But beginning Scala I found myself difficult to decide what classes to define to better employ Scala's syntactic sugar facilities (an even idealess about how should I design for better performance). Any good readings on this question?
I have read 4 books on Scala, but I have not found what you are asking for. I guess you have read "Programming in Scala" by Odersky (Artima) already. If not, this is a link to the on-line version:
http://www.docstoc.com/docs/8692868/Programming-In-Scala
This book gives many examples how to construct object-oriented models in Scala, but all examples are very small in number of classes. I do not know of any book that will teach you how to structure large scale systems using Scala.
Imperative object-orientation has
been around since Smalltalk, so we
know a lot about this paradigm.
Functional object-orientation on the
other hand, is a rather new concept,
so in a few years I expect books
describing large scale FOO systems to
appear. Anyway, I think that the PiS
book gives you a pretty good picture
how you can put together the basic
building blocks of a system, like
Factory pattern, how to replace the
Strategy pattern with function
literals and so on.
One thing that Viktor Klang once told me (and something I really agree upon) is that one difference between C++/Java and Scala OO is that you define a lot more (smaller) classes when you use Scala. Why? Because you can! The syntactic sugar for the case class result in a very small penalty for defining a class, both in typing and in readability of the code. And as you know, many small classes usually means better OO (fewer bugs) but worse performance.
One other thing I have noticed is that I use the factory pattern a lot more when dealing with immutable objects, since all "changes" of an instance results in creating a new instance. Thank God for the copy() method on the case class. This method makes the factory methods a lot shorter.
I do not know if this helped you at all, but I think this subject is very interesting myself, and I too await more literature on this subject.
Cheers!
This is still an evolving matter. For instance, the just released Scala 2.8.0 brought support of type constructor inference, which enabled a pattern of type classes in Scala. The Scala library itself has just began using this pattern. Just yesterday I heard of a new Lift module in which they are going to try to avoid inheritance in favor of type classes.
Scala 2.8.0 also introduced lower priority implicits, plus default and named parameters, both of which can be used, separately or together, to produce very different designs than what was possible before.
And if we go back in time, we note that other important features are not that old either:
Extractor methods on case classes object companions where introduced February 2008 (before that, the only way to do extraction on case classes was through pattern matching).
Lazy values and Structural types where introduced July 2007.
Abstract types support for type constructors was introduced in May 2007.
Extractors for non-case classes was introduced in January 2007.
It seems that implicit parameters were only introduced in March 2006, when they replaced the way views were implemented.
All that means we are all learning how to design Scala software. Be sure to rely on tested designs of functional and object oriented paradigms, to see how new features in Scala are used in other languages, like Haskell and type classes or Python and default (optional) and named parameters.
Some people dislike this aspect of Scala, others love it. But other languages share it. C# is adding features as fast as Scala. Java is slower, but it goes through changes too. It added generics in 2004, and the next version should bring some changes to better support concurrent and parallel programming.
I don't think that there are much tutorials for this. I'd suggest to stay with the way you do it now, but to look through "idiomatic" Scala code as well and to pay special attention in the following cases:
use case classes or case objects instead of enums or "value objects"
use objects for singletons
if you need behavior "depending on the context" or dependency-injection-like functionality, use implicits
when designing a type hierarchy or if you can factor things out of a concrete class, use traits when possible
Fine grained inheritance hierarchies are OK. Keep in mind that you have pattern matching
Know the "pimp my library" pattern
And ask as many questions as you feel you need to understand a certain point. The Scala community is very friendly and helpful. I'd suggest the Scala mailing list, Scala IRC or scala-forum.org
I've just accidentally googled to a file called "ScalaStyleGuide.pdf". Going to read...
Related
I've heard people claim that:
Scala's type system is amazing (existential types, variant, co-variant)
Because of the power of macros, everything is a library in Clojure: (pattern matching, logic programming, non-determinism, ..)
Question:
If both assertions are true, why is Scala's type system not a library in Clojure? Is it because:
types are one of these things that do not work well as a library? [i.e. the changes would somehow have to threaded through every existing clojure library, including clojure.core?]
is Scala's notion of types fundamentally incompatible with clojure protocol / records?
... ?
It's an interesting question.
You are certainly right about Scala having an amazing type system, and about Clojure being phenomenal for meta-programming and extension of the language (although that is about more than just macros....).
A few reasons I can think of:
Clojure is a dynamically typed language while Scala is a statically typed language. Having powerful type inference isn't so much use in a language where you can assume relatively little about the types of your inputs.
Clojure already has a very interesting project to add typing as a library (Typed Clojure) which looks very promising - however it's very different in approach to Scala as it is designed for a dynamic language from the start (inspired more by Typed Racket, I believe).
Clojure philosophy actually discourages certain OOP concepts (particularly implementation inheritance, mutable objects, and data encapsulation). A type system that supports these things (as Scala does) wouldn't be a good fit for Clojure idioms - at best they would be ignored, but they could easily encourage a style of development that would cause people to run into severe problems later.
Clojure already provides tools that solve many of the problems you would typically solve with types in other languages - e.g. the use of protocols for polymorphism.
There's a strong focus in the Clojure community on simplicity (in the sense of the excellent video "Simple Made Easy" - see particularly the slide at 39:30). While Scala's type system is certainly amazing, I think it's a stretch to describe it as "Simple"
Putting in a Scala-style type system would probably require a complete rewrite of the Clojure compiler and make it substantially more complex. Nobody seems to have signed up so far to take on that particular challenge... and there's a risk that even if someone were willing and able to do this then the changes could be rejected for the various cultural / technical reasons covered above.
In the absence of a major change to Clojure itself (which I think would be unlikely) then one interesting possibility would be to create a DSL within Clojure that provided Scala-style type inference for a specific domain and compiled this DSL direct to optimised Java bytecode. I could see that being a useful approach for specific problem domains (large scale numerical data crunching with big matrices, for example).
To simply answer your question "... why is Scala's type system not a library in Clojure?":
Because the type system is part of the scala compiler and not of the scala library. The whole power of scalas type system only exists at compile time. The JVM has no support for things like that, because of type erasure and also, because it would simply slow down execution. And also there is no need for it. If you have a statically typed language, you don't need type information at runtime, unless you want to do dirty stuff.
edit:
#mikera the jvm is sure capable of running the scala compiler, I did not say anything like that. I just said, that the jvm has no support for type systems like that. It does not even support generics. At runtime all these types are gone. The compiler checks for the correctness of a program and removes all the higher kinded types / generics.
example:
val xs: List[Int] = List(1,2,3,4)
val x1: Int = xs.head
will at runtime look like this:
val xs: List = List.apply(1,2,3,4)
val x1: Int = xs.head.asInstanceOf[Int]
But it doesn't matter, because the compiler checked it before. You can only get in trouble here, when you use reflection, because you could put any value in the list and it would break at runtime exactly where the value is casted to Int.
And this is one of the reasons, why the scala type system is not part of the scala library, but built into the compiler.
And also the question of the OP was "... why is Scala's type system not a library in Clojure?" and not "Is it possible to create a type system such as scalas for clojure?" and I perfectly answered that question.
After watching Martin's keynote on Reflection and Compilers I can't seem to get this crazy question out of my head. Martin talks among other things about the "(Wedding) Cake Pattern", where traits play the central part. I'm wondering, why in the world do we need packages when we already have traits? Is there anything a package can do, what a trait (at least theoretically) cannot?
I'm not talking about the current implementation, I'm just trying to imagine what programming would be like if we replace packages with traits. In my head it would be like this:
one keyword less (package is unneeded)
no need for package objects
To summarize all my questions:
Is it theoretically possible to remove packages from the language and use traits instead.
What other benefits would we gain from this change? (I was thinking about first class packages and first class imports, but mixin composition is a compile time thing, although the super calls are dynamically bound)
Is Java/JVM compatibility the only thing, which would stand in the way?
Update
Daniel Spiewak talks in this keynote about the Dependency Injection being just the top of the iceberg of all the stuff you can do with the Cake Pattern.
Martin Odersky has said that Scala could get by with just traits, objects, methods and paths (I hope I didn't forget something).
Both classes and packages are just there because Scala is intended to be a hosted language, i.e. a language which runs on (this is actually not the interesting bit) and interoperates with (this is the important point) a host platform. Some of the host platforms that Scala is intended to interoperate with are the Java platform and the CLI, both which have a concept of classes and packages (namespaces in the case of the CLI) that is significantly distinct enough that it cannot be easily expressed as traits or objects. This is unlike interfaces, which can be trivially mapped to and from purely abstract traits.
The above statement was made in a discussion about potentially removing generics from Scala, because everything generics can do can also be achieved by abstract types.
In scala the object and package serve almost the same purpose and objects are also called modules. Objects deserve to be thought of as modules because they can contain any definition including other objects of course and, significantly, types.
A trait can be thought of as an abstract module. It can contain any definition and any member can be abstract including, again significantly, type members. I am reciting all this just to highlight the symmetry. Perhaps OT but to me traits seem to be as big an innovation in scala as the merging of object and functional ideas.
To finally give an answer:
I think packages could be removed in favour of objects (not traits).
The benefit would be a simplification - package objects would not need to be explicitly defined.
I think packages are distinct from objects for Java/JVM compatibility.
Some more commentary: in the video Martin talks of traits (abstract modules) more than concrete modules because the latter only appear at the last moment to assemble and reify some combination of abstract modules.
It is good to use abstract modules even when not "mixing a cake". e.g. when sketching out some code you might define a module to contain definitions. But as soon as you come to a type or value you are not ready to fill in, don't supply a dummy such as null. Instead switch the object to a trait and leave the member abstract.
Soooo...
Semigroups, Monoids, Monads, Functors, Lenses, Catamorphisms, Anamorphisms, Arrows... These all sound good, and after an exercise or two (or ten), you can grasp their essence. And with Scalaz, you get them for free...
However, in terms of real-world programming, I find myself struggling to find usages to these notions. Yes, of course I always find someone on the web using Monads for IO or Lenses in Scala, but... still...
What I am trying to find is something along the "prescriptive" lines of a pattern. Something like: "here, you are trying to solves this, and one good way to solve it is by using lenses this way!"
Suggestions?
Update: Something along these lines, with a book or two, would be great (thanks Paul): Examples of GoF Design Patterns in Java's core libraries
The key to functional programming is abstraction, and composability of abstractions. Monads, Arrows, Lenses, these are all abstractions which have proven themselves useful, mostly because they are composable. You've asked for a "prescriptive" answer, but I'm going to say no. Perhaps you're not convinced that functional programming matters?
I'm sure plenty of people on StackOverflow would be more than happy to try and help you solve a specific problem the FP way. Have a list of stuff and you want to traverse the list and build up some result? Use a fold. Want to parse XML? hxt uses arrows for that. And monads? Well, tons of data types turn out to be Monads, so learn about them and you'll discover a wealth of ways you can manipulate these data types. But its kind of hard to just pull examples out of thin air and say "lenses are the Right Way to do this", "monoids are the best way to do that", etc. How would you explain to a newbie what the use of a for loop is? If you want to [blank], then use a for loop [in this way]. It's so general; there are tons of ways to use a for loop. The same goes for these FP abstractions.
If you have many years of OOP experience, then don't forget you were once a newbie at OOP. It takes time to learn the FP way, and even more time to unlearn some OOP tendencies. Give it time and you will find plenty of uses for a Functional approach.
I gave a talk back in September focused on the practical application of monoids and applicative functors/monads via scalaz.Validation. I gave another version of the same talk at the scala Lift Off, where the emphasis was more on the validation. I would watch the first talk until I start on validations and then skip to the second talk (27 minutes in).
There's also a gist I wrote which shows how you might use Validation in a "practical" application. That is, if you are designing software for nightclub bouncers.
I think you can take the reverse approach and instead when writing a small piece of functionality, ask yourself whether any of those would apply: Semigroups, Monoids, Monads, Functors, Lenses, Catamorphisms, Anamorphisms, Arrows... A lots of those concepts can be used in a local way.
Once you start down that route, you may see usage everywhere. For me, I sort of get Semigroups, Monoids, Monads, Functors. So take the example of answering this question How do I populate a list of objects with new values. It's a real usage for the person asking the question (a self described noob). I am trying to answer in a simple way but I have to refrain myself from scratching the itch "there are monoids in here".
Scratching it now: using foldMap and the fact that Int and List are monoids and that the monoid property is preserved when dealing with tuple, maps and options:
// using scalaz
listVar.sliding(2).toList.foldMap{
case List(prev, i) => Some(Map(i -> (1, Some(List(math.abs(i - prev))))))
case List(i) => Some(Map(i -> (1, None)))
case _ => None
}.map(_.mapValues{ case (count, gaps) => (count, gaps.map(_.min)) })
But I don't come to that result by thinking I will use hard core functional programming. It comes more naturally by thinking this seems simpler if I compose those monoids combined with the fact that scalaz has utility methods like foldMap. Interestingly when looking at the resulting code it's not obvious that I'm totally thinking in terms of monoid.
You might like this talk by Chris Marshall. He covers a couple of Scalaz goodies - namely Monoid and Validation - with many practical examples. Ittay Dror has written a very accessible post on how Functor, Applicative Functor, and Monad can be useful in practice. Eric Torreborre and Debasish Gosh's blogs also have a bunch of posts covering use cases for categorical constructs.
This answer just lists a few links instead of providing some real substance here. (Too lazy to write.) Hope you find it helpful anyway.
I understand your situation, but you will find that to learn functional programming you will need to adjust your point of view to the documentation you find, instead of the other way around. Luckily in Scala you have the possibility of becoming a functional programmer gradually.
To answer your questions and explain the point-of-view difference, I need to distinguish between "type classes" (monoids, functors, arrows), mathematically called "structures", and generic operations or algorithms (catamorphisms or folds, anamorphisms or unfolds, etc.). These two often interact, since many generic operations are defined for specific classes of data types.
You look for prescriptive answers similar to design patterns: when does this concept apply? The truth is that you have surely seen the prescriptive answers, and they are simply the definitions of the different concepts. The problem (for you) is that those answers are intrinsically different from design patterns, but it is so for good reasons.
On the one hand, generic algorithms are not design patterns, which suggest a structure for the code you write; they are abstractions defined in the language which you can directly apply. They are general descriptions for common algorithms which you already implement today, but by hand. For instance, whenever you are computing the maximum element of a list by scanning it, you are hardcoding a fold; when you sum elements, you are doing the same; and so on. When you recognize that, you can declare the essence of the operation you are performing by calling the appropriate fold function. This way, you save code and bugs (no opportunity for off-by-one errors), and you save the reader the effort to read all the needed code.
On the other hand, structures concern not the goal you have in mind but properties of the entities you are modeling. They are more useful for bottom-up software construction, rather than top-down: when defining your data, you can declare that it is a e.g. a monoid. Later, when processing your data, you have the opportunity to use operations on e.g. monoids to implement your processing. In some cases it is useful to strive to express your algorithm in terms of the predefined ones. For instance, very often if you need to reduce a tree to a single value, a fold can do most or all of what you need. Of course, you can also declare that your data type is a monoid when you need a generic algorithm on monoids; but the earlier you notice that, the earlier you can start reusing generic algorithms for monoids.
Last advice is that probably most of the documentation you will find about these concepts concerns Haskell, because this language has been around for much more time and supports them in a quite elegant way. Quite recommended here are Learn you a Haskell for Great Good, a Haskell course for beginners, where among others chapters 11 to 14 focus on some type classes, and Typeclassopedia (which contains links to various articles with specific examples). EDIT: Finally, an example of applications of Monoids, taken from Typeclassopedia, is here: http://apfelmus.nfshost.com/articles/monoid-fingertree.html. I'm not saying there is little documentation for Scala, just that there is more in Haskell, and Haskell is where the application of these concepts to programming was born.
I've been hearing a lot about different JVM languages, still in vaporware mode, that propose to implement reification somehow. I have this nagging half-remembered (or wholly imagined, don't know which) thought that somewhere I read that Scala somehow took advantage of the JVM's type erasure to do things that it wouldn't be able to do with reification. Which doesn't really make sense to me since Scala is implemented on the CLR as well as on the JVM, so if reification caused some kind of limitation it would show up in the CLR implementation (unless Scala on the CLR is just ignoring reification).
So, is there a good side to type erasure for Scala, or is reification an unmitigated good thing?
See Ola Bini's blog. As we all know, Java has use-site covariance, implemented by having little question marks wherever you think variance is appropriate. Scala has definition-site covariance, implemented by the class designer. He says:
Generics is a complicated language feature. It becomes even more
complicated when added to an existing language that already has
subtyping. These two features don’t play very well together in the
general case, and great care has to be taken when adding them to a
language. Adding them to a virtual machine is simple if that machine
only has to serve one language - and that language uses the same
generics. But generics isn’t done. It isn’t completely understood how
to handle correctly and new breakthroughs are happening (Scala is a
good example of this). At this point, generics can’t be considered
“done right”. There isn’t only one type of generics - they vary in
implementation strategies, feature and corner cases.
...
What this all means is that if you want to add reified generics to the
JVM, you should be very certain that that implementation can encompass
both all static languages that want to do innovation in their own
version of generics, and all dynamic languages that want to create a
good implementation and a nice interfacing facility with Java
libraries. Because if you add reified generics that doesn’t fulfill
these criteria, you will stifle innovation and make it that much
harder to use the JVM as a multi language VM.
i.e. If we had reified generics in the JVM, most likely those reified generics wouldn't be suitable for the features we really like about Scala, and we'd be stuck with something suboptimal.
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Closed 9 years ago.
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..