when would I use a shallow copy? - reference

I understand what the difference between a shallow and deep copy are, but I really don't understand in what situations a shallow copy would be preferred.
If I'm not mistaken, shallow copy makes a new copy of the value types and simply copies the address of reference types so they are pointing to the same object, correct? Why would I ever want this effect?

In fact a shallow copy is the way with least effort, doing less. It is especially suited for immutable objects, where sharing is optimal.
An immutable object does not have an internal state, cannot be changed, only variables can be set to another value.
In java String and BigDecimal are immutable.
Immutable objects allow making better use of threads too.
For mutable classes you might be interested in copy-on-write data structures, where sharing happens till one variable is written to.

I think one good example could help understanding the concept. Suppose you have a list of tuples. And you the list to a function to process something on. Creating some sub-lists from the original one could help in a function and this is not necessary to deep-copy all the tuples in the list. And you just need to copy those pointers (shallow-copy).

Related

What's the most efficient: a reference to an ArrayBase or an ArrayView?

I'm doing improvement on a Rust codebase that uses the ndarray crate to manipulate arrays. I have one question I could not find an explicit answer in the documentation.
Is it more efficient to pass an instance of ArrayView as an argument to a function or should I use a reference to an Array instead? My intuition is that since ArrayView is a view of an array, when doing computations, it only passes a view of the array and does not grant ownership to the function (hence does not copy) the underlying data.
In short, is there any speed gain to expect from switching from passing instances of ArrayView to passing references of Array?
My goal is to avoid useless memory allocation/duplication which can be very costly when dealing with large arrays.
ArrayBase is a generic struct that can act as both an ArrayView and an Array, so I assume you mean a reference to the owned data, i.e. an Array.
Neither version will clone the array, so they should be approximately equally efficient. You can always benchmark to verify this.
As I see it, the difference is mostly that ArrayView will make the function more flexible – you can pass in parts of larger arrays, or an ArrayView created from a slice, whereas the variant that takes a reference to Array can only be called when you really have an Array of the desired size.

(Beginner) Why does the temporary variable change in example 1, but not in example 2? [duplicate]

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

Data to be determined later: interior mutability or separate HashMap?

I have a struct, call it Book, which let's say stores data on a book sold by a bookstore. It needs to be referenced at many places in some data structure (e.g. with Rc) and so cannot be borrowed mutably in the normal way. However, it has some attribute, say its price, that needs to be filled in at some time later than initialization, after the object already has outstanding references.
So far I can think of two ways to do this, but they both have disadvantages:
Interior mutability: give Book a field such as price: RefCell<Option<i32>> which is initialized to RefCell::new(Option::None) when Book is initialized. Later on, when we determine the price of the book, we can use borrow_mut to set price to Some(10) instead, and from then on we can borrow it to retrieve its value.
My sense is that in general, one wants to avoid interior mutability unless necessary, and it doesn't seem here like it ought to be all that necessary. This technique is also a little awkward because of the Option, which we need because the price won't have a value until later (and setting it to 0 or -1 in the meantime seems un-Rustlike), but which requires lots of matches or unwraps in places where we may be logically certain that the price will have already been filled in.
Separate table: don't store the price inside Book at all, but make a separate data structure to store it, e.g. price_table: HashMap<Rc<Book>, i32>. Have a function which creates and populates this table when prices are determined, and then pass it around by reference (mutably or not) to every function that needs to know or change the prices of books.
Coming from a C background as I do, the HashMap feels like unnecessary overhead both in speed and memory, for data that already has a natural place to live (inside Book) and "should" be accessible via a simple pointer chase. This solution also means I have to clutter up lots of functions with an additional argument that's a reference to price_table.
Is one of these two methods generally more idiomatic in Rust, or are there other approaches that avoid the dilemma? I did see Once, but I don't think it's what I want, because I'd still have to know at initialization time how to fill in price, and I don't know that.
Of course, in other applications, we may need some other type than i32 to represent our desired attribute, so I'd like to be able to handle the general case.
I think that your first approach is optimal for this situation. Since you have outstanding references to some data that you want to write to, you have to check the borrowing rules at runtime, so RefCell is the way to go.
Inside the RefCell, prefer an Option or a custom enum with variants like Price::NotSet and Price::Set(i32). If you are really sure, that all prices are initialized at some point, you could write a method price() that calls unwrap for you or does an assertion with better debug output in the case your RefCell contains a None.
I guess that the HashMap approach would be fine for this case, but if you wanted to have something that is not Copy as your value in there, you could run into the same problem, since there might be outstanding references into the map somewhere.
I agree that the HashMap would not be the idiomatic way to go here and still choose your first approach, even with i32 as the value type.
Edit:
As pointed out in the comments (thanks you!), there are two performance considerations for this situation. Firstly, if you really know, that the contained price is never zero, you can use std::num::NonZeroU16 and get the Option variant None for free (see documentation).
If you are dealing with a type that is Copy (e.g. i32), you should consider using Cell instead of RefCell, because it is lighter. For a more detailed comparison, see https://stackoverflow.com/a/30276150/13679671
Here are two more approaches.
Use Rc<RefCell<<Book>> everywhere, with price: Option<i32>> in the struct.
Declare a strict BookId(usize) and make a library: HashMap<BookId, Book>. Make all your references BookId and thus indirectly reference books through them everywhere you need to do so.

What's the advantage of a String being Immutable?

Once I studied about the advantage of a string being immutable because of something to improve performace in memory.
Can anybody explain this to me? I can't find it on the Internet.
Immutability (for strings or other types) can have numerous advantages:
It makes it easier to reason about the code, since you can make assumptions about variables and arguments that you can't otherwise make.
It simplifies multithreaded programming since reading from a type that cannot change is always safe to do concurrently.
It allows for a reduction of memory usage by allowing identical values to be combined together and referenced from multiple locations. Both Java and C# perform string interning to reduce the memory cost of literal strings embedded in code.
It simplifies the design and implementation of certain algorithms (such as those employing backtracking or value-space partitioning) because previously computed state can be reused later.
Immutability is a foundational principle in many functional programming languages - it allows code to be viewed as a series of transformations from one representation to another, rather than a sequence of mutations.
Immutable strings also help avoid the temptation of using strings as buffers. Many defects in C/C++ programs relate to buffer overrun problems resulting from using naked character arrays to compose or modify string values. Treating strings as a mutable types encourages using types better suited for buffer manipulation (see StringBuilder in .NET or Java).
Consider the alternative. Java has no const qualifier. If String objects were mutable, then any method to which you pass a reference to a string could have the side-effect of modifying the string. Immutable strings eliminate the need for defensive copies, and reduce the risk of program error.
Immutable strings are cheap to copy, because you don't need to copy all the data - just copy a reference or pointer to the data.
Immutable classes of any kind are easier to work with in multiple threads, the only synchronization needed is for destruction.
Perhaps, my answer is outdated, but probably someone will found here a new information.
Why Java String is immutable and why it is good:
you can share a string between threads and be sure no one of them will change the string and confuse another thread
you don’t need a lock. Several threads can work with immutable string without conflicts
if you just received a string, you can be sure no one will change its value after that
you can have many string duplicates – they will be pointed to a single instance, to just one copy. This saves computer memory (RAM)
you can do substring without copying, – by creating a pointer to an existing string’s element. This is why Java substring operation implementation is so fast
immutable strings (objects) are much better suited to use them as key in hash-tables
a) Imagine StringPool facility without making string immutable , its not possible at all because in case of string pool one string object/literal e.g. "Test" has referenced by many reference variables , so if any one of them change the value others will be automatically gets affected i.e. lets say
String A = "Test" and String B = "Test"
Now String B called "Test".toUpperCase() which change the same object into "TEST" , so A will also be "TEST" which is not desirable.
b) Another reason of Why String is immutable in Java is to allow String to cache its hashcode , being immutable String in Java caches its hash code and do not calculate every time we call hashcode method of String, which makes it very fast as hashmap key.
Think of various strings sitting on a common pool. String variables then point to locations in the pool. If u copy a string variable, both the original and the copy shares the same characters. These efficiency of sharing outweighs the inefficiency of string editing by extracting substrings and concatenating.
Fundamentally, if one object or method wishes to pass information to another, there are a few ways it can do it:
It may give a reference to a mutable object which contains the information, and which the recipient promises never to modify.
It may give a reference to an object which contains the data, but whose content it doesn't care about.
It may store the information into a mutable object the intended data recipient knows about (generally one supplied by that data recipient).
It may return a reference to an immutable object containing the information.
Of these methods, #4 is by far the easiest. In many cases, mutable objects are easier to work with than immutable ones, but there's no easy way to share with "untrusted" code the information that's in a mutable object without having to first copy the information to something else. By contrast, information held in an immutable object to which one holds a reference may easily be shared by simply sharing a copy of that reference.

Is 'mutable' the same as the word 'modifiable' in relation to strings?

When we talk about strings as being mutable, is this synonymous with using the word 'changeable' or 'modifiable' or is there some additional nuance to explain why this jargon is used instead of a simpler word like 'modifiable'?
I think the word "mutable" is a good option for this.
If you used "modifiable", it would be less clear. For example, if your string is a heap allocated type, when you say you are modifying the "string", it's not clear whether you're changing the data on the heap (the string's contents) or the string's heap pointer.
However, "mutable" suggests that the string's actual data is changing, to me. I think it's due to it being the same root as to mutate. If something is mutating, it's not changing from looking at A to looking at B (ie: changing a pointer), but rather mutating itself, or becoming (iteratively) something it was not originally.
A mutable object is an object that can be modified after it has been created. So in a way, it is synonymous with "modifiable." The word "mutable" means "liable or subject to change or alteration." I think it sounds better than "modifiable."
mutable
"liable or subject to change or alteration."
modifiable
"to change somewhat the form or qualities of; alter partially;"
conversely
immutable
"not mutable; unchangeable; changeless"
unmodifiable
"incapable of being modified in form or character or strength"
In programming you more often hear the terms mutable and immutable than you do modifiable and unmodifiable. However I think it is safe to say that either way has the same meaning.
But when in Rome... so you should use mutable and immutable as they are the more commonly used terms (at least in my experience).
As to why that choice? I asked my mother in law (she is up on words :-) and from a non-programming point of view "mutable" is shorter then "modifiable"... seems likely enough of a reason to me.
Yes, mutable is the term for an object that is capable of being changed after it is created, whereas immutable refers to an object that cannot change. Mutable literally means "ability to mutate" which I think fits perfectly with how mutable objects behave.
Specifically in relation to strings, in a mutable string, if you change the first character from 'A' to 'B', you're still dealing with the same bytes in memory; one of them has just taken a different value. With immutable strings, i.e. in Java, a new object would be created at a new location in memory, because the original one cannot be changed.
Mutable is a decent word to describe that, and it has the advantage of not being loaded with real-world meanings or interpretations that would make it difficult to use precisely.
And since you didn't point out the specific context you're speaking of (and so please forgive me if this is scope creep)...
Strings in .NET specifically are immutable, not mutable. Once they're created, that's it. They never change. If change attempts are made, new strings are created and the old ones get released for garbage collection.
Here is a pretty simple explanation of mutable/immutable using java as an example:
Mutable
can be changed without reallocating memory
a StringBuffer api documentation is a mutable version the standard string class
to change the standard value of the String class you need to reallocate memory
I have never really heard of using the term modifiable.

Resources