Just a quote from hack documentation :
Legacy Vector, Map, and Set
These container types should be avoided in new code; use dict,
keyset, and vec instead.
Early in Hack's life, the library provided mutable and immutable
generic class types called: Vector, ImmVector, Map, ImmMap, Set, and
ImmSet. However, these have been replaced by vec, dict, and keyset,
whose use is recommended in all new code. Each generic type had a
corresponding literal form. For example, a variable of type
Vector might be initialized using Vector {22, 33, $v}, where $v
is a variable of type int.
I wonder why this change was made.
I mean, one of PHP weaknesses is that it has bad oop standard library.
Ex : str_replace and array_values methods are outside of the string/array type itself. The PHP standard library is not consistent, sometimes we must pass the array as the first parameter, other times as the second...
I was glad to see that Hack introduced true OOP encapsulation for collections.
Do you know why they stepped back and wrote utility classes such as C\, Dict\, Keyset\ and Vec\ ?
Will there be in the future an addition to add methods to built-in types (ex : Str\starts_with => "toto"->startsWith("t")) ?
Based on Dwayne Reeves' blog post introducing HSL, it seems that the main advantage is the fact that arrays are native values, not objects. This has two important consequences:
For users, the semantics are different when the values cross through arguments. Objects are passed as references, and mutations affect the original object. On the other hand, values are copied on write after passing through arguments, so without references (which are finally to be completely banned in Hack) the callee can't mutate the value of the caller, with the exception of the much stricter inout parameters.
The article cites the invariance of the mutable containers (Vector, Set, etc.) and generally how shared mutable state couples functions closer together. The soundness issues as discussed in the article are somewhat moot because there were also immutable object containers (ImmVector, ImmSet, etc.), although since these interfaces were written in userland, variance boxed the function type signature into tight constraints. There are tangible differences from this: ImmMap<Tk, +Tv> is invariant in Tk solely because of the (function(Tk): Tv) getter. Meanwhile, dict<+Tk, +Tv> is covariant in both type parameters thanks to the inherent mutation protection from copy-on-write.
For the compiler, static values can be allocated quickly and persist over the lifetime of the server. Objects on the other hand have arbitrarily complicated construction routines in general, and the collection objects weren't going to be special-cased it seems.
I will also mention that for most use cases, there is minimal difference even in code style: e.g. the -> reference chains can be directly replaced with the |> pipe operator. There is also no longer a boundary between the privileged "standard functions" and custom user functions on collection types. Finally, the collection types were final of course, so their objective nature didn't offer any actual hierarchical or polymorphic advantages to the end user anyways.
Related
I want to start with what I know, or at least I think I know, so what I'm asking would be more clear.
First of all, I know that you can declare a variable of a supertype and assign an object of a subtype to take advantage of polymorphism with Inheritence and Interfaces.
I know that generics provide type safety because the type parameters are invariant by definition, so where A is a subtype of B, Foo<A> is not necessarily a subtype of Foo<B>, and may not be used in place depending on mutability of the object. With this, possible exceptions that could arise at runtime due to dynamic dispatching can be caught in compile time.
They also help to define a generic logic for different types: Like in Lists where you have collections of type A objects, but it doesn't change the implementation for type B objects.
Also, I understood why MutableList<String> doesn't count as the subtype of MutableList<Any> because that could result in cases where you create a variable with type MutableList<Any> that holds a reference to a MutableList<String> object, and add an Int element to a List of Strings, which is obviously a problem.
I also understood why List version of the previous example works because Lists are immutable so you can't make any modification to the object that could result in type mismatches.
Lastly, I know that type parameters with in can only be used as function parameters, being consumed, and the ones with out can be used as the function return types, being produced.
Now to the part what I don't understand:
I didn't quite understand what the words consumer and producer actually means in terms of in and out. What does it mean for a type to be in consumed or produced position? Does that mean the object with that type can only be read or write only? Does that have anything to do with the object at all?
What would be the behaviour of the object if, let's say, we don't define it using in or out, or, opposite, we define it using in or out, not talking about the subtype-supertype relationship that I explained above.
I spend the last few days looking at different explanations of this, but I found the lack of examples a big problem, especially because that's how I usually learn.
I can use these concepts in code, but the lack of underlying knowledge or the logic greatly disturbs me, so please, if you decide to take the time to write an explanation, provide it with examples and counter examples of why or how a certain idea works.
Just one correction to your first bullet points: List is not immutable; it is read-only. A List could be an up-cast mutable implementation and some other object that references it could be mutating it.
Producer means the generic type appears as a return type in any functions or properties of the object. You can get T’s out of a List, for instance.
Consumer means the generic type appears as a parameter of any functions or as the type of any var properties of the object. You can put T’s into a MutableList, for example.
Since List produces but doesn’t consume (it doesn’t have any functions with T as a parameter), its type is marked as producing-only, aka covariant, aka out right at the declaration site so its type can always be assumed to be out wherever it’s used even if the out keyword is not used.
Since the List type is always covariant out, any List can be safely upcast to a List where the type is a supertype of the originating type. A List<String> can be cast to List<CharSequence> because any item you get out of it (anything it produces) is going to be a String, and therefore also qualifies as the supertype CharSequence.
The reverse logic would apply for something that is purely a consumer with the type marked in, but it’s harder to come up with a simple example where you would actually have a useful object like this.
A MutableList both produces and consumes, so it is invariant by default, but since it is also a List, a MutableList<String> could be safely cast to a List<CharSequence>. If you have a reference to the List<CharSequence>, you can get CharSequences out of it. The underlying object might continue to have new Strings put into it from the original reference.
I have read a lot about abstract data types (ADTs) and I'm askig myself if there are non-abstract/ concrete datatypes?
There is already a question on SO about ADTs, but this question doesn't cover "non-abstract" data types.
The definition of ADT only mentions what operations are to be
performed but not how these operations will be implemented
reference
So a ADT is hiding the concrete implementation from the user and "only" offers a bunch of permissible operations/ methods; e.g., the Stack in Java (reference). Only methods like pop(), push(), empty() are visible and the concrete implementation is hidden.
Following this argumentation leads me to the question, if there is a "non-abstract" data type?
Even a primitive data type like java.lang.Integer has well defined operations, like +, -, ... and according to wikipedia it is a ADT.
For example, integers are an ADT, defined as the values …, −2, −1, 0, 1, 2, …, and by the operations of addition, subtraction, multiplication, and division, together with greater than, less than, etc.,
reference
The java.lang.Integer is not a primitive type. It is an ADT that wraps the primitve java type int. The same holds for the other Java primitive types and the corresponding wrappers.
You don't need OOP support in a language to have ADTs. If you don't have support, you establish conventions for the ADT in the code you write (i.e. you only use it as previoulsy defined by the operations and possible values of the ADT)
That's why ADT's predate the class and object concepts present in OOP languages.They existed before. Statements like class just introduced direct support in the languages, allowing compilers to check what you are doing with the ADTs.
Primitive types are just values that can be stored in memory, without any other associated code. They don't know about themselves or their operations. And their internal representation is known by external actors, unlike the ADTs. Just like the possible operations. These are manipulations to the values done externally, from the outside.
Primitive types carry with them, although you don't necessary see it, implementation details relating the CPU or virtual machine architecture. Because they map to CPU available register sizes and instructions that the CPU executes directly. Hence the maximum integer value limits, for example.
If I am allowed to say this, the hardware knows your primitive types.
So your non-abstract data types are the primitive types of a language,
if those types aren't themselves ADT's too. If they happen to be ADTs,
you probably have to create them (not just declare them; there will
be code setting up things in memory, not only the storage in a certain
address), so they have an identity, and they usually offer methods
invoked through that identity, that is, they know about themselves.
Because in some languages everything is an object, like in Python, the
builtin types (the ones that are readily available with no
need to define classes) are sometimes called primitive too, despite
being no primitive at all by the above definition.
Edit:
As mentioned by jaco0646, there is more about concrete/abstract
words in OOP.
An ADT is already an abstraction. It represents a category
of similar objects you can instantiate from.
But an ADT can be even more abstract, and is referred as such (as
opposed to concrete data types) if you declare it with no intention of
instantiating objects from it. Usually you do this because other "concrete"
ADTs (the ones you instantiate) inherit from the "abstract" ADT. This allows the sharing and extension of behaviour between several different ADTs.
For example you can define an API like that, and make one or more different
ADTs offer (and respect) that API to their users, just by inheritance.
Abstract ADTs maybe defined by you or be available in language types or
libraries.
For example a Python builtin list object is also a collections.abc.Iterable.
In Python you can use multiple inheritance to add functionality like that.
Although there are other ways.
In Java you can't, but you have interfaces instead, and can declare a class to implement one or more interfaces, besides possibly extending another class.
So an ADT definition whose purpose is to be directly instantiated, is a
concrete ADT. Otherwise it is abstract.
A closely related notion is that of an abstract method in a class.
It is a method you don't fill with code, because it is meant to be filled by children classes that should implement it, respecting its signature (name and parameters).
So depending on your language you will find possible different (or similar) ways of implementing this concepts.
I agree with the answer from #progmatico, but I would add that concrete (non-abstract) data types include more than primitives.
In Java, Stack happens to be a concrete data type, which extends another concrete data type Vector, which extends an ADT AbstractList.
The interfaces implemented by AbstractList are also ADTs: Iterable, Collection, List.
In object oriented programming languages when you define a variable it ends up becoming a reference to an object. The variable is not itself the object, and instead points to the object that carries the value that was assigned to that variable.
Question is how does this work so efficiently? What is the mechanism of how a variable is assigned to an object?
The way I think about the organization is as a linked list, however could not find references how the data is structured in languages such as Ruby or Java.
In object oriented programming languages when you define a variable it ends up becoming a reference to an object.
This is not always true. For example, C++ can be considered an object-oriented language, yet a user of the language can use a variable as a reference/pointer or explicitly as a value.
However, you are right in that some (typically higher-level) OO languages implicitly use references so that the user of the language does not have to worry about these kinds of implementation "details" in regards to performance. They try to take responsibility for this instead.
how does this work so efficiently? What is the mechanism of how a variable is assigned to an object?
Consider a simple example. What happens when an object is passed as a parameter to a function? A copy of that object must be made so that the function can refer to that object locally. For an OO language that implicitly uses references, only the address of the object needs to be copied, whereas a true pass-by-value would require a copy of the complete memory contents of the object, which could potentially be very large (think a collection of objects or similar).
A detailed explanation of this involves getting into the guts of assembly. For example, why does a copy of an object to a function call even need to be made in the first place? Why does the indirection of an address not take longer than a direct value? Etc.
Related
What's the difference between passing by reference vs. passing by value?
What is open recursion? Is it specific to OOP?
(I came across this term in this tweet by Daniel Spiewak.)
just copying http://www.comlab.ox.ac.uk/people/ralf.hinze/talks/Open.pdf:
"Open recursion Another handy feature offered by most languages with objects and classes is the ability for one method body to invoke another method of the same object via a special variable called self or, in some langauges, this. The special behavior of self is that it is late-bound, allowing a method defined in one class to invoke another method that is defined later, in some subclass of the first. "
This paper analyzes the possibility of adding OO to ML, with regards to expressivity and complexity. It has the following excerpt on objects, which seems to make this term relatively clear –
3.3. Objects
The simplest form of object is just a record of functions that share a common closure environment that
carries the object state (we can call these simple objects). The function members of the record may or may not
be defined as mutually recursive. However, if one wants to support inheritance with overriding, the structure
of objects becomes more complicated. To enable open recursion, the call-graph of the method functions
cannot be hard-wired, but needs to be implemented indirectly, via object self-reference. Object self-reference
can be achieved either by construction, making each object a recursive, self-referential value (the fixed-point
model), or dynamically, by passing the object as an extra argument on each method call (the self-application
or self-passing model).5 In either case, we will call these self-referential objects.
The name "open recursion" is a bit misleading at first, because it has nothing to do with the recursion that normally is used (a function calling itself); and to that extent, there is no closed recursion.
It basically means, that a thing is referring to itself. I can only guess, but I do think that the term "open" comes from open as in "open for extension".
In that sense an object is open to extension, but still referring to itself.
Perhaps a small example can shed some light on the concept.
Imaging you write a Python class like this one:
class SuperClass:
def method1(self):
self.method2()
def method2(self):
print(self.__class__.__name__)
If you ran this by
s = SuperClass()
s.method1()
It will print "SuperClass".
Now we create a subclass from SuperClass and override method2:
class SubClass(SuperClass):
def method2(self):
print(self.__class__.__name__)
and run it:
sub = SubClass()
sub.method1()
Now "SubClass" will be printed.
Still, we only call method1() as before. Inside method1() the method2() is called, but both are bound to the same reference (self in Python, this in Java). During sub-classing SuperClass method2() is changed, which means that an object of SubClass refers to a different version of this method.
That is open recursion.
In most cases, you override methods and call the overridden methods directly.
This scheme here is using an indirection over self-reference.
P.S.: I don't think this has been invented but discovered and then explained.
Open recursion allows to call another methods of object from within, through special variable like this or self.
In short, open recursion is about something actually not related to OOP, but more general.
The relation with OOP comes from the fact that many typical "OOP" PLs have such properties, but it is essentially not tied to any distinguishing features about OOP.
So there are different meanings, even in same "OOP" language. I will illustrate it later.
Etymology
As mentioned here, the terminology is likely coined in the famous TAPL by BCP, which illustrates the meaning by concrete OOP languages.
TAPL does not define "open recursion" formally. Instead, it points out the "special behavior of self (or this) is that it is late-bound, allowing a method defined in one class to invoke another method that is defined later, in some subclass of the first".
Nevertheless, neither of "open" and "recursion" comes from the OOP basis of a language. (Actually, it is also nothing to do with static types.) So the interpretation (or the informal definition, if any) in that source is overspecified in nature.
Ambiguity
The mentioning in TAPL clearly shows "recursion" is about "method invocation". However, it is not that simple in real languages, which usually do not have primitive semantic rules on the recursive invocation itself. Real languages (including the ones considered as OOP languages) usually specify the semantics of such invocation for the notation of the method calls. As syntactic devices, such calls are subject to the evaluation of some kind of expressions relying on the evaluations of its subexpressions. These evaluations imply the resolution of method name, under some independent rules. Specifically, such rules are about name resolution, i.e. to determine the denotation of a name (typically, a symbol, an identifier, or some "qualified" name expressions) in the subexpression. Name resolution often respects to scoping rules.
OTOH, the "late-bound" property emphasizes how to find the target implementation of the named method. This is a shortcut of evaluation of specific call expressions, but it is not general enough, because entities other than methods can also have such "special" behavior, even make such behavior not special at all.
A notable ambiguity comes from such insufficient treatment. That is, what does a "binding" mean. Traditionally, a binding can be modeled as a pair of a (scoped) name and its bound value, i.e. a variable binding. In the special treatment of "late-bound" ones, the set of allowed entities are smaller: methods instead of all named entities. Besides the considerably undermining the abstraction power of the language rules at meta level (in the language specification), it does not cease the necessity of traditional meaning of a binding (because there are other non-method entities), hence confusing. The use of a "late-bound" is at least an instance of bad naming. Instead of "binding", a more proper name would be "dispatching".
Worse, the use in TAPL directly mix the two meanings when dealing with "recusion". The "recursion" behavior is all about finding the entity denoted by some name, not just specific to method invocation (even in those OOP language).
The title of the chapter (Case Study: Imperative Objects) also suggests some inconsistency. Obviously, the so-called late binding of method invocation has nothing to do with imperative states, because the resolution of the dispatching does not require mutable metadata of invocation. (In some popular sense of implementation, the virtual method table need not to be modifiable.)
Openness
The use of "open" here looks like mimic to open (lambda) terms. An open term has some names not bound yet, so the reduction of such a term must do some name resolution (to compute the value of the expression), or the term is not normalized (never terminate in evaluation). There is no difference between "late" or "early" for the original calculi because they are pure, and they have the Church-Rosser property, so whether "late" or not does not alter the result (if it is normalized).
This is not the same in the language with potentially different paths of dispatching. Even that the implicit evaluation implied by the dispatching itself is pure, it is sensitive to the order among other evaluations with side effects which may have dependency on the concrete invocation target (for example, one overrider may mutate some global state while another can not). Of course in a strictly pure language there can be no observable differences even for any radically different invocation targets, a language rules all of them out is just useless.
Then there is another problem: why it is OOP-specific (as in TAPL)? Given that the openness is qualifying "binding" instead of "dispatching of method invocation", there are certainly other means to get the openness.
One notable instance is the evaluation of a procedure body in traditional Lisp dialects. There can be unbound symbols in the body and they are only resolved when the procedure being called (rather than being defined). Since Lisps are significant in PL history and the are close to lambda calculi, attributing "open" specifically to OOP languages (instead of Lisps) is more strange from the PL tradition. (This is also a case of "making them not special at all" mentioned above: every names in function bodies are just "open" by default.)
It is also arguable that the OOP style of self/this parameter is equivalent to the result of some closure conversion from the (implicit) environment in the procedure. It is questionable to treat such features primitive in the language semantics.
(It may be also worth noting, the special treatment of function calls from symbol resolution in other expressions is pioneered by Lisp-2 dialects, not any of typical OOP languages.)
More cases
As mentioned above, different meanings of "open recursion" may coexist in a same "OOP" language.
C++ is the first instance here, because there are sufficient reasons to make them coexist.
In C++, name resolution are all static, normatively name lookup. The rules of name lookup vary upon different scopes. Most of them are consistent with identifier lookup rules in C (except for the allowance of implicit declarations in C but not in C++): you must first declare the name, then the name can be lookup in the source code (lexically) later, otherwise the program is ill-formed (and it is required to issue an error in the implementation of the language). The strict requirement of such dependency of names are considerable "closed", because there are no later chance to recover from the error, so you cannot directly have names mutually referenced across different declarations.
To work around the limitation, there can be some additional declarations whose sole duty is to break the cyclic dependency. Such declarations are called "forward" declarations. Using of forward declarations still does not require "open" recursion, because every well-formed use must statically see the previous declaration of that name, so each name lookup does not require additional "late" binding.
However, C++ classes have special name lookup rules: some entities in the class scope can be referred in the context prior to their declaration. This makes mutual recursive use of name across different declarations possible without any additional "forward" declarations to break the cycle. This is exactly the "open recursion" in TAPL sense except that it is not about method invocation.
Moreover, C++ does have "open recursion" as per the descriptions in TAPL: this pointer and virtual functions. Rules to determine the target (overrider) of virtual functions are independent to the name lookup rules. A non-static member defined in a derived class generally just hide the entities with same name in the base classes. The dispatching rules kick in only on virtual function calls, after the name lookup (the order is guaranteed since evaulations of C++ function calls are strict, or applicative). It is also easy to introduce a base class name by using-declaration without worry about the type of the entity.
Such design can be seen as an instance of separate of concerns. The name lookup rules allows some generic static analysis in the language implementation without special treatment of function calls.
OTOH, Java have some more complex rules to mix up name lookup and other rules, including how to identify the overriders. Name shadowing in Java subclasses is specific to the kind of entities. It is more complicate to distinguish overriding with overloading/shadowing/hiding/obscuring for different kinds. There also cannot be techniques of C++'s using-declarations in the definition of subclasses. Such complexity does not make Java more or less "OOP" than C++, anyway.
Other consequences
Collapsing the bindings about name resolution and dispatching of method invocation leads to not only ambiguity, complexity and confusion, but also more difficulties on the meta level. Here meta means the fact that name binding can exposing properties not only available in the source language semantics, but also subject to the meta languages: either the formal semantic of the language or its implementation (say, the code to implement an interpreter or a compiler).
For example, as in traditional Lisps, binding-time can be distinguished from evaluation-time, because program properties revealed in binding-time (value binding in the immediate contexts) is more close to meta properties compared to evaluation-time properties (like the concrete value of arbitrary objects). An optimizing compiler can deploy the code generation immediately depending on the binding-time analysis either statically at the compile-time (when the body is to be evaluate more than once) or derferred at runtime (when the compilation is too expensive). There is no such option for languages blindly assume all resolutions in closed recursion faster than open ones (and even making them syntactically different at the very first). In such sense, OOP-specific open recursion is not just not handy as advertised in TAPL, but a premature optimization: giving up metacompilation too early, not in the language implementation, but in the language design.
I'm trying to get my head around mutable vs immutable objects. Using mutable objects gets a lot of bad press (e.g. returning an array of strings from a method) but I'm having trouble understanding what the negative impacts are of this. What are the best practices around using mutable objects? Should you avoid them whenever possible?
Well, there are a few aspects to this.
Mutable objects without reference-identity can cause bugs at odd times. For example, consider a Person bean with a value-based equals method:
Map<Person, String> map = ...
Person p = new Person();
map.put(p, "Hey, there!");
p.setName("Daniel");
map.get(p); // => null
The Person instance gets "lost" in the map when used as a key because its hashCode and equality were based upon mutable values. Those values changed outside the map and all of the hashing became obsolete. Theorists like to harp on this point, but in practice I haven't found it to be too much of an issue.
Another aspect is the logical "reasonability" of your code. This is a hard term to define, encompassing everything from readability to flow. Generically, you should be able to look at a piece of code and easily understand what it does. But more important than that, you should be able to convince yourself that it does what it does correctly. When objects can change independently across different code "domains", it sometimes becomes difficult to keep track of what is where and why ("spooky action at a distance"). This is a more difficult concept to exemplify, but it's something that is often faced in larger, more complex architectures.
Finally, mutable objects are killer in concurrent situations. Whenever you access a mutable object from separate threads, you have to deal with locking. This reduces throughput and makes your code dramatically more difficult to maintain. A sufficiently complicated system blows this problem so far out of proportion that it becomes nearly impossible to maintain (even for concurrency experts).
Immutable objects (and more particularly, immutable collections) avoid all of these problems. Once you get your mind around how they work, your code will develop into something which is easier to read, easier to maintain and less likely to fail in odd and unpredictable ways. Immutable objects are even easier to test, due not only to their easy mockability, but also the code patterns they tend to enforce. In short, they're good practice all around!
With that said, I'm hardly a zealot in this matter. Some problems just don't model nicely when everything is immutable. But I do think that you should try to push as much of your code in that direction as possible, assuming of course that you're using a language which makes this a tenable opinion (C/C++ makes this very difficult, as does Java). In short: the advantages depend somewhat on your problem, but I would tend to prefer immutability.
Immutable Objects vs. Immutable Collections
One of the finer points in the debate over mutable vs. immutable objects is the possibility of extending the concept of immutability to collections. An immutable object is an object that often represents a single logical structure of data (for example an immutable string). When you have a reference to an immutable object, the contents of the object will not change.
An immutable collection is a collection that never changes.
When I perform an operation on a mutable collection, then I change the collection in place, and all entities that have references to the collection will see the change.
When I perform an operation on an immutable collection, a reference is returned to a new collection reflecting the change. All entities that have references to previous versions of the collection will not see the change.
Clever implementations do not necessarily need to copy (clone) the entire collection in order to provide that immutability. The simplest example is the stack implemented as a singly linked list and the push/pop operations. You can reuse all of the nodes from the previous collection in the new collection, adding only a single node for the push, and cloning no nodes for the pop. The push_tail operation on a singly linked list, on the other hand, is not so simple or efficient.
Immutable vs. Mutable variables/references
Some functional languages take the concept of immutability to object references themselves, allowing only a single reference assignment.
In Erlang this is true for all "variables". I can only assign objects to a reference once. If I were to operate on a collection, I would not be able to reassign the new collection to the old reference (variable name).
Scala also builds this into the language with all references being declared with var or val, vals only being single assignment and promoting a functional style, but vars allowing a more C-like or Java-like program structure.
The var/val declaration is required, while many traditional languages use optional modifiers such as final in java and const in C.
Ease of Development vs. Performance
Almost always the reason to use an immutable object is to promote side effect free programming and simple reasoning about the code (especially in a highly concurrent/parallel environment). You don't have to worry about the underlying data being changed by another entity if the object is immutable.
The main drawback is performance. Here is a write-up on a simple test I did in Java comparing some immutable vs. mutable objects in a toy problem.
The performance issues are moot in many applications, but not all, which is why many large numerical packages, such as the Numpy Array class in Python, allow for In-Place updates of large arrays. This would be important for application areas that make use of large matrix and vector operations. This large data-parallel and computationally intensive problems achieve a great speed-up by operating in place.
Immutable objects are a very powerful concept. They take away a lot of the burden of trying to keep objects/variables consistent for all clients.
You can use them for low level, non-polymorphic objects - like a CPoint class - that are used mostly with value semantics.
Or you can use them for high level, polymorphic interfaces - like an IFunction representing a mathematical function - that is used exclusively with object semantics.
Greatest advantage: immutability + object semantics + smart pointers make object ownership a non-issue, all clients of the object have their own private copy by default. Implicitly this also means deterministic behavior in the presence of concurrency.
Disadvantage: when used with objects containing lots of data, memory consumption can become an issue. A solution to this could be to keep operations on an object symbolic and do a lazy evaluation. However, this can then lead to chains of symbolic calculations, that may negatively influence performance if the interface is not designed to accommodate symbolic operations. Something to definitely avoid in this case is returning huge chunks of memory from a method. In combination with chained symbolic operations, this could lead to massive memory consumption and performance degradation.
So immutable objects are definitely my primary way of thinking about object-oriented design, but they are not a dogma.
They solve a lot of problems for clients of objects, but also create many, especially for the implementers.
Check this blog post: http://www.yegor256.com/2014/06/09/objects-should-be-immutable.html. It explains why immutable objects are better than mutable. In short:
immutable objects are simpler to construct, test, and use
truly immutable objects are always thread-safe
they help to avoid temporal coupling
their usage is side-effect free (no defensive copies)
identity mutability problem is avoided
they always have failure atomicity
they are much easier to cache
You should specify what language you're talking about. For low-level languages like C or C++, I prefer to use mutable objects to conserve space and reduce memory churn. In higher-level languages, immutable objects make it easier to reason about the behavior of the code (especially multi-threaded code) because there's no "spooky action at a distance".
A mutable object is simply an object that can be modified after it's created/instantiated, vs an immutable object that cannot be modified (see the Wikipedia page on the subject). An example of this in a programming language is Pythons lists and tuples. Lists can be modified (e.g., new items can be added after it's created) whereas tuples cannot.
I don't really think there's a clearcut answer as to which one is better for all situations. They both have their places.
Shortly:
Mutable instance is passed by reference.
Immutable instance is passed by value.
Abstract example. Lets suppose that there exists a file named txtfile on my HDD. Now, when you are asking me to give you the txtfile file, I can do it in the following two modes:
I can create a shortcut to the txtfile and pass shortcut to you, or
I can do a full copy of the txtfile file and pass copied file to you.
In the first mode, the returned file represents a mutable file, because any change into the shortcut file will be reflected into the original one as well, and vice versa.
In the second mode, the returned file represents an immutable file, because any change into the copied file will not be reflected into the original one, and vice versa.
If a class type is mutable, a variable of that class type can have a number of different meanings. For example, suppose an object foo has a field int[] arr, and it holds a reference to a int[3] holding the numbers {5, 7, 9}. Even though the type of the field is known, there are at least four different things it can represent:
A potentially-shared reference, all of whose holders care only that it encapsulates the values 5, 7, and 9. If foo wants arr to encapsulate different values, it must replace it with a different array that contains the desired values. If one wants to make a copy of foo, one may give the copy either a reference to arr or a new array holding the values {1,2,3}, whichever is more convenient.
The only reference, anywhere in the universe, to an array which encapsulates the values 5, 7, and 9. set of three storage locations which at the moment hold the values 5, 7, and 9; if foo wants it to encapsulate the values 5, 8, and 9, it may either change the second item in that array or create a new array holding the values 5, 8, and 9 and abandon the old one. Note that if one wanted to make a copy of foo, one must in the copy replace arr with a reference to a new array in order for foo.arr to remain as the only reference to that array anywhere in the universe.
A reference to an array which is owned by some other object that has exposed it to foo for some reason (e.g. perhaps it wants foo to store some data there). In this scenario, arr doesn't encapsulate the contents of the array, but rather its identity. Because replacing arr with a reference to a new array would totally change its meaning, a copy of foo should hold a reference to the same array.
A reference to an array of which foo is the sole owner, but to which references are held by other object for some reason (e.g. it wants to have the other object to store data there--the flipside of the previous case). In this scenario, arr encapsulates both the identity of the array and its contents. Replacing arr with a reference to a new array would totally change its meaning, but having a clone's arr refer to foo.arr would violate the assumption that foo is the sole owner. There is thus no way to copy foo.
In theory, int[] should be a nice simple well-defined type, but it has four very different meanings. By contrast, a reference to an immutable object (e.g. String) generally only has one meaning. Much of the "power" of immutable objects stems from that fact.
Mutable collections are in general faster than their immutable counterparts when used for in-place
operations.
However, mutability comes at a cost: you need to be much more careful sharing them between
different parts of your program.
It is easy to create bugs where a shared mutable collection is updated
unexpectedly, forcing you to hunt down which line in a large codebase is performing the unwanted update.
A common approach is to use mutable collections locally within a function or private to a class where there
is a performance bottleneck, but to use immutable collections elsewhere where speed is less of a concern.
That gives you the high performance of mutable collections where it matters most, while not sacrificing
the safety that immutable collections give you throughout the bulk of your application logic.
If you return references of an array or string, then outside world can modify the content in that object, and hence make it as mutable (modifiable) object.
Immutable means can't be changed, and mutable means you can change.
Objects are different than primitives in Java. Primitives are built in types (boolean, int, etc) and objects (classes) are user created types.
Primitives and objects can be mutable or immutable when defined as member variables within the implementation of a class.
A lot of people people think primitives and object variables having a final modifier infront of them are immutable, however, this isn't exactly true. So final almost doesn't mean immutable for variables. See example here
http://www.siteconsortium.com/h/D0000F.php.
General Mutable vs Immutable
Unmodifiable - is a wrapper around modifiable. It guarantees that it can not be changed directly(but it is possibly using backing object)
Immutable - state of which can not be changed after creation. Object is immutable when all its fields are immutable. It is a next step of Unmodifiable object
Thread safe
The main advantage of Immutable object is that it is a naturally for concurrent environment. The biggest problem in concurrency is shared resource which can be changed any of thread. But if an object is immutable it is read-only which is thread safe operation. Any modification of an original immutable object return a copy
source of truth, side-effects free
As a developer you are completely sure that immutable object's state can not be changed from any place(on purpose or not). For example if a consumer uses immutable object he is able to use an original immutable object
compile optimisation
Improve performance
Disadvantage:
Copying of object is more heavy operation than changing a mutable object, that is why it has some performance footprint
To create an immutable object you should use:
1. Language level
Each language contains tools to help you with it. For example:
Java has final and primitives
Swift has let and struct[About].
Language defines a type of variable. For example:
Java has primitive and reference type,
Swift has value and reference type[About].
For immutable object more convenient is primitives and value type which make a copy by default. As for reference type it is more difficult(because you are able to change object's state out of it) but possible. For example you can use clone pattern on a developer level to make a deep(instead of shallow) copy.
2. Developer level
As a developer you should not provide an interface for changing state
[Swift] and [Java] immutable collection