A CreditCard instance never outlives the Customer that it refers to. To represent this, the Customer class has an optional card property, but the CreditCard class has an unowned and non-optional customer property.
Furthermore, a new CreditCard instance can only be created by passing a number value and a customer instance to a custom CreditCard initializer. This ensures that a CreditCard instance always has a customer instance associated with it when the CreditCard instance is created. Because a credit card will always have a customer, you define its customer property as an unowned reference, to avoid a strong reference cycle:.
This next code snippet defines an optional Customer variable called john , which will be used to store a reference to a specific customer. This variable has an initial value of nil, by virtue of being optional:.
The Customer instance now has a strong reference to the CreditCard instance, and the CreditCard instance has an unowned reference to the Customer instance. Because of the unowned customer reference, when you break the strong reference held by the john variable, there are no more strong references to the Customer instance:. After this happens, there are no more strong references to the CreditCard instance, and it too is deallocated:.
The examples above show how to use safe unowned references. Swift also provides unsafe unowned references for cases where you need to disable runtime safety checks—for example, for performance reasons. As with all unsafe operations, you take on the responsibility for checking that code for safety. You indicate an unsafe unowned reference by writing unowned unsafe.
If you try to access an unsafe unowned reference after the instance that it refers to is deallocated, your program will try to access the memory location where the instance used to be, which is an unsafe operation. You can mark an optional reference to a class as unowned. In terms of the ARC ownership model, an unowned optional reference and a weak reference can both be used in the same contexts.
Department maintains a strong reference to each course that the department offers. In the ARC ownership model, a department owns its courses. The code above creates a department and its three courses. The intro and intermediate courses both have a suggested next course stored in their nextCourse property, which maintains an unowned optional reference to the course a student should take after completing this one.
It behaves the same as an unowned reference does under ARC, except that an unowned optional reference can be nil. In this case, for example, when you delete a course from department. The underlying type of an optional value is Optional , which is an enumeration in the Swift standard library.
The Person and Apartment example shows a situation where two properties, both of which are allowed to be nil , have the potential to cause a strong reference cycle. This scenario is best resolved with a weak reference. This scenario is best resolved with an unowned reference. This enables both properties to be accessed directly without optional unwrapping once initialization is complete, while still avoiding a reference cycle. This section shows you how to set up such a relationship.
The example below defines two classes, Country and City , each of which stores an instance of the other class as a property. In this data model, every country must always have a capital city, and every city must always belong to a country.
To represent this, the Country class has a capitalCity property, and the City class has a country property:. To set up the interdependency between the two classes, the initializer for City takes a Country instance, and stores this instance in its country property. The initializer for City is called from within the initializer for Country.
To cope with this requirement, you declare the capitalCity property of Country as an implicitly unwrapped optional property, indicated by the exclamation point at the end of its type annotation City! This means that the capitalCity property has a default value of nil , like any other optional, but can be accessed without the need to unwrap its value as described in Implicitly Unwrapped Optionals.
Because capitalCity has a default nil value, a new Country instance is considered fully initialized as soon as the Country instance sets its name property within its initializer. This means that the Country initializer can start to reference and pass around the implicit self property as soon as the name property is set.
The Country initializer can therefore pass self as one of the parameters for the City initializer when the Country initializer is setting its own capitalCity property.
All of this means that you can create the Country and City instances in a single statement, without creating a strong reference cycle, and the capitalCity property can be accessed directly, without needing to use an exclamation point to unwrap its optional value:.
In the example above, the use of an implicitly unwrapped optional means that all of the two-phase class initializer requirements are satisfied. The capitalCity property can be used and accessed like a non-optional value once initialization is complete, while still avoiding a strong reference cycle.
You saw above how a strong reference cycle can be created when two class instance properties hold a strong reference to each other. You also saw how to use weak and unowned references to break these strong reference cycles. A strong reference cycle can also occur if you assign a closure to a property of a class instance, and the body of that closure captures the instance.
This strong reference cycle occurs because closures, like classes, are reference types. When you assign a closure to a property, you are assigning a reference to that closure. It would be nice to know also why I get minus for my question. I really don't know these things and it would be nice to know what's wrong with my question so I could find info about subjects without having to ask all the time.
What would trigger decrementing the counter in your scenario? Not accessing the memory anymore might be a bit tricky to detect You shouldn't need reference counters for this. Your library only needs to supply a function to free the given memory.
It's up to the caller to decide when it doesn't need that memory anymore and call your cleanup function. Show 2 more comments. Active Oldest Votes. Improve this answer. Thank you very much! This helped me a lot and now I got this problem fixed. The program now works as supposed : — J.
Thanks, please can you mark that the question is answered : — zakum1. Add a comment. Sign up or log in Sign up using Google. Sign up using Facebook. Sign up using Email and Password. Post as a guest Name. Email Required, but never shown. The Overflow Blog. Does ES6 make JavaScript frameworks obsolete? Tin Man 2 2 bronze badges. This is largely correct, although it's not really true that classes in managed languages can't be used to encapsulate OS resources.
NET, there's an interface IDisposable and a whole set of guidance around doing just that. That is a common misconception. Here is a concrete counter example: researcher.
That is another common misconception. Non-deferred reference counting like ARC has worse case unbounded pause times when the last reference to a DAG falls out of scope, worse than even the simplest incremental GC. Boehm even found that RC has worse max pause times than Hotspot: hpl. I often see that asserted, even by experts, but I have never seen any evidence to support that belief.
RC keeps objects alive until the end of scope whereas tracing garbage collectors do not. Show 7 more comments. The instructor is wrong. You better know how garbage collection and reference counting works. I would also add that modern languages provide data structures to abstract and automate memory management. Java has weak collections which serve well for e. Snowman: "modern languages There's something so very wrong with that.
The vast majority of GC research over the past 56 years has concluded that tracing is faster than reference counting though a few die hards continue to pursue RC, e. Getting reference counting back in the ring" users. And these are not minor tweaks: they are receiving major features that one would expect from a programming language in Manual memory management, reference counting, and garbage collection all have their pro's and con's: Manual memory management: Unbeatable fast, but prone to bugs due to errors in freeing the memory.
Weak references may be used to break some reference cycles, however, they come with quite a bit of additional costs: Weak references require a second reference count to manage the weak reference itself.
This can all be done, but it's not as simple as reference counting without weak references. The claim that reference counting has better real-time behavior than tracing GCs is oft repeated and makes intuitive sense, but as it turns out the best known realtime tracing GCs beat the best known realtime reference-counting GCs when it comes to pause times. For example, Metronome's pause times are less than the context switching time of a modern realtime OS!
So, if you can afford threads, you can afford a tracing GC as well. And as it turns out, proving correctness and upper bounds of tracing GCs seems to be much easier than for reference-counting GCs. Note that manual memory management is only unbeatable if you can match the rather sophisticated locality optimizations of a good relocating GC ref-counted or tracing. If you can't, cache misses will eat your gains. See e. RC-Immix for explorations of how important this is. If GC vs reference counting makes a measurable difference, then you are spending a lot of time creating and destroying objects anyway, so maybe you should try to avoid that.
And I think modern Java compilers can figure out sometimes that an object will be created and will become garbage very soon after, so they don't bother creating the object at all. Snowman While I buy your "Computers even phones are fast" in general, that does not mean that you can ignore performance considerations everywhere.
As I said in a comment above, I work in a field where computing never can be fast enough. And I strongly object to your assertion "algorithms are highly optimized": It is true that highly optimized algorithms are known , but that does not translate into them being implemented : The number of people who can do proper optimization is wanning precisely because "computers are fast"!
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