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+<!-- DO NOT EDIT THIS FILE.
+
+This file is periodically generated from the content in the `/src/`
+directory, so all fixes need to be made in `/src/`.
+-->
+
+[TOC]
+
+# Smart Pointers
+
+A *pointer* is a general concept for a variable that contains an address in
+memory. This address refers to, or “points at,” some other data. The most
+common kind of pointer in Rust is a reference, which you learned about in
+Chapter 4. References are indicated by the `&` symbol and borrow the value they
+point to. They don’t have any special capabilities other than referring to
+data, and have no overhead.
+
+*Smart pointers*, on the other hand, are data structures that act like a
+pointer but also have additional metadata and capabilities. The concept of
+smart pointers isn’t unique to Rust: smart pointers originated in C++ and exist
+in other languages as well. Rust has a variety of smart pointers defined in the
+standard library that provide functionality beyond that provided by references.
+To explore the general concept, we'll look at a couple of different examples of
+smart pointers, including a *reference counting* smart pointer type. This
+pointer enables you to allow data to have multiple owners by keeping track of
+the number of owners and, when no owners remain, cleaning up the data.
+
+Rust, with its concept of ownership and borrowing, has an additional difference
+between references and smart pointers: while references only borrow data, in
+many cases, smart pointers *own* the data they point to.
+
+Though we didn't call them as such at the time, we’ve already encountered a few
+smart pointers in this book, including `String` and `Vec<T>` in Chapter 8. Both
+these types count as smart pointers because they own some memory and allow you
+to manipulate it. They also have metadata and extra capabilities or guarantees.
+`String`, for example, stores its capacity as metadata and has the extra
+ability to ensure its data will always be valid UTF-8.
+
+Smart pointers are usually implemented using structs. Unlike an ordinary
+struct, smart pointers implement the `Deref` and `Drop` traits. The `Deref`
+trait allows an instance of the smart pointer struct to behave like a reference
+so you can write your code to work with either references or smart pointers.
+The `Drop` trait allows you to customize the code that's run when an instance
+of the smart pointer goes out of scope. In this chapter, we’ll discuss both
+traits and demonstrate why they’re important to smart pointers.
+
+Given that the smart pointer pattern is a general design pattern used
+frequently in Rust, this chapter won’t cover every existing smart pointer. Many
+libraries have their own smart pointers, and you can even write your own. We’ll
+cover the most common smart pointers in the standard library:
+
+* `Box<T>` for allocating values on the heap
+* `Rc<T>`, a reference counting type that enables multiple ownership
+* `Ref<T>` and `RefMut<T>`, accessed through `RefCell<T>`, a type that enforces
+  the borrowing rules at runtime instead of compile time
+
+In addition, we’ll cover the *interior mutability* pattern where an immutable
+type exposes an API for mutating an interior value. We’ll also discuss
+*reference cycles*: how they can leak memory and how to prevent them.
+
+Let’s dive in!
+
+## Using `Box<T>` to Point to Data on the Heap
+
+The most straightforward smart pointer is a *box*, whose type is written
+`Box<T>`. Boxes allow you to store data on the heap rather than the stack. What
+remains on the stack is the pointer to the heap data. Refer to Chapter 4 to
+review the difference between the stack and the heap.
+
+Boxes don’t have performance overhead, other than storing their data on the
+heap instead of on the stack. But they don’t have many extra capabilities
+either. You’ll use them most often in these situations:
+
+* When you have a type whose size can’t be known at compile time and you want
+  to use a value of that type in a context that requires an exact size
+* When you have a large amount of data and you want to transfer ownership but
+  ensure the data won’t be copied when you do so
+* When you want to own a value and you care only that it’s a type that
+  implements a particular trait rather than being of a specific type
+
+We’ll demonstrate the first situation in the “Enabling Recursive Types with
+Boxes” section. In the second case, transferring ownership of a large amount of
+data can take a long time because the data is copied around on the stack. To
+improve performance in this situation, we can store the large amount of data on
+the heap in a box. Then, only the small amount of pointer data is copied around
+on the stack, while the data it references stays in one place on the heap. The
+third case is known as a *trait object*, and Chapter 17 devotes an entire
+section, “Using Trait Objects That Allow for Values of Different Types,” just
+to that topic. So what you learn here you’ll apply again in Chapter 17!
+
+### Using a `Box<T>` to Store Data on the Heap
+
+Before we discuss the heap storage use case for `Box<T>`, we’ll cover the
+syntax and how to interact with values stored within a `Box<T>`.
+
+Listing 15-1 shows how to use a box to store an `i32` value on the heap:
+
+Filename: src/main.rs
+
+```
+fn main() {
+    let b = Box::new(5);
+    println!("b = {}", b);
+}
+```
+
+Listing 15-1: Storing an `i32` value on the heap using a box
+
+We define the variable `b` to have the value of a `Box` that points to the
+value `5`, which is allocated on the heap. This program will print `b = 5`; in
+this case, we can access the data in the box similar to how we would if this
+data were on the stack. Just like any owned value, when a box goes out of
+scope, as `b` does at the end of `main`, it will be deallocated. The
+deallocation happens both for the box (stored on the stack) and the data it
+points to (stored on the heap).
+
+Putting a single value on the heap isn’t very useful, so you won’t use boxes by
+themselves in this way very often. Having values like a single `i32` on the
+stack, where they’re stored by default, is more appropriate in the majority of
+situations. Let’s look at a case where boxes allow us to define types that we
+wouldn’t be allowed to if we didn’t have boxes.
+
+### Enabling Recursive Types with Boxes
+
+A value of *recursive type* can have another value of the same type as part of
+itself. Recursive types pose an issue because at compile time Rust needs to
+know how much space a type takes up. However, the nesting of values of
+recursive types could theoretically continue infinitely, so Rust can’t know how
+much space the value needs. Because boxes have a known size, we can enable
+recursive types by inserting a box in the recursive type definition.
+
+As an example of a recursive type, let’s explore the *cons list*. This is a data
+type commonly found in functional programming languages. The cons list type
+we’ll define is straightforward except for the recursion; therefore, the
+concepts in the example we’ll work with will be useful any time you get into
+more complex situations involving recursive types.
+
+#### More Information About the Cons List
+
+A *cons list* is a data structure that comes from the Lisp programming language
+and its dialects and is made up of nested pairs, and is the Lisp version of a
+linked list. Its name comes from the `cons` function (short for “construct
+function”) in Lisp that constructs a new pair from its two arguments. By
+calling `cons` on a pair consisting of a value and another pair, we can
+construct cons lists made up of recursive pairs.
+
+For example, here's a pseudocode representation of a cons list containing the
+list 1, 2, 3 with each pair in parentheses:
+
+```
+(1, (2, (3, Nil)))
+```
+
+Each item in a cons list contains two elements: the value of the current item
+and the next item. The last item in the list contains only a value called `Nil`
+without a next item. A cons list is produced by recursively calling the `cons`
+function. The canonical name to denote the base case of the recursion is `Nil`.
+Note that this is not the same as the “null” or “nil” concept in Chapter 6,
+which is an invalid or absent value.
+
+The cons list isn’t a commonly used data structure in Rust. Most of the time
+when you have a list of items in Rust, `Vec<T>` is a better choice to use.
+Other, more complex recursive data types *are* useful in various situations,
+but by starting with the cons list in this chapter, we can explore how boxes
+let us define a recursive data type without much distraction.
+
+Listing 15-2 contains an enum definition for a cons list. Note that this code
+won’t compile yet because the `List` type doesn’t have a known size, which
+we’ll demonstrate.
+
+Filename: src/main.rs
+
+```
+enum List {
+    Cons(i32, List),
+    Nil,
+}
+```
+
+Listing 15-2: The first attempt at defining an enum to represent a cons list
+data structure of `i32` values
+
+> Note: We’re implementing a cons list that holds only `i32` values for the
+> purposes of this example. We could have implemented it using generics, as we
+> discussed in Chapter 10, to define a cons list type that could store values of
+> any type.
+
+Using the `List` type to store the list `1, 2, 3` would look like the code in
+Listing 15-3:
+
+Filename: src/main.rs
+
+```
+use crate::List::{Cons, Nil};
+
+fn main() {
+    let list = Cons(1, Cons(2, Cons(3, Nil)));
+}
+```
+
+Listing 15-3: Using the `List` enum to store the list `1, 2, 3`
+
+The first `Cons` value holds `1` and another `List` value. This `List` value is
+another `Cons` value that holds `2` and another `List` value. This `List` value
+is one more `Cons` value that holds `3` and a `List` value, which is finally
+`Nil`, the non-recursive variant that signals the end of the list.
+
+If we try to compile the code in Listing 15-3, we get the error shown in
+Listing 15-4:
+
+```
+error[E0072]: recursive type `List` has infinite size
+ --> src/main.rs:1:1
+  |
+1 | enum List {
+  | ^^^^^^^^^ recursive type has infinite size
+2 |     Cons(i32, List),
+  |               ---- recursive without indirection
+  |
+help: insert some indirection (e.g., a `Box`, `Rc`, or `&`) to make `List` representable
+```
+
+Listing 15-4: The error we get when attempting to define a recursive enum
+
+The error shows this type “has infinite size.” The reason is that we’ve defined
+`List` with a variant that is recursive: it holds another value of itself
+directly. As a result, Rust can’t figure out how much space it needs to store a
+`List` value. Let’s break down why we get this error. First, we'll look at how
+Rust decides how much space it needs to store a value of a non-recursive type.
+
+#### Computing the Size of a Non-Recursive Type
+
+Recall the `Message` enum we defined in Listing 6-2 when we discussed enum
+definitions in Chapter 6:
+
+```
+enum Message {
+    Quit,
+    Move { x: i32, y: i32 },
+    Write(String),
+    ChangeColor(i32, i32, i32),
+}
+```
+
+To determine how much space to allocate for a `Message` value, Rust goes
+through each of the variants to see which variant needs the most space. Rust
+sees that `Message::Quit` doesn’t need any space, `Message::Move` needs enough
+space to store two `i32` values, and so forth. Because only one variant will be
+used, the most space a `Message` value will need is the space it would take to
+store the largest of its variants.
+
+Contrast this with what happens when Rust tries to determine how much space a
+recursive type like the `List` enum in Listing 15-2 needs. The compiler starts
+by looking at the `Cons` variant, which holds a value of type `i32` and a value
+of type `List`. Therefore, `Cons` needs an amount of space equal to the size of
+an `i32` plus the size of a `List`. To figure out how much memory the `List`
+type needs, the compiler looks at the variants, starting with the `Cons`
+variant. The `Cons` variant holds a value of type `i32` and a value of type
+`List`, and this process continues infinitely, as shown in Figure 15-1.
+
+<img alt="An infinite Cons list" src="img/trpl15-01.svg" class="center" style="width: 50%;" />
+
+Figure 15-1: An infinite `List` consisting of infinite `Cons` variants
+
+#### Using `Box<T>` to Get a Recursive Type with a Known Size
+
+Because Rust can’t figure out how much space to allocate for recursively
+defined types, the compiler gives an error with this helpful suggestion:
+
+```
+help: insert some indirection (e.g., a `Box`, `Rc`, or `&`) to make `List` representable
+  |
+2 |     Cons(i32, Box<List>),
+  |               ^^^^    ^
+```
+
+In this suggestion, “indirection” means that instead of storing a value
+directly, we should change the data structure to store the value indirectly by
+storing a pointer to the value instead.
+
+Because a `Box<T>` is a pointer, Rust always knows how much space a `Box<T>`
+needs: a pointer’s size doesn’t change based on the amount of data it’s
+pointing to. This means we can put a `Box<T>` inside the `Cons` variant instead
+of another `List` value directly. The `Box<T>` will point to the next `List`
+value that will be on the heap rather than inside the `Cons` variant.
+Conceptually, we still have a list, created with lists holding other lists, but
+this implementation is now more like placing the items next to one another
+rather than inside one another.
+
+We can change the definition of the `List` enum in Listing 15-2 and the usage
+of the `List` in Listing 15-3 to the code in Listing 15-5, which will compile:
+
+Filename: src/main.rs
+
+```
+enum List {
+    Cons(i32, Box<List>),
+    Nil,
+}
+
+use crate::List::{Cons, Nil};
+
+fn main() {
+    let list = Cons(1, Box::new(Cons(2, Box::new(Cons(3, Box::new(Nil))))));
+}
+```
+
+Listing 15-5: Definition of `List` that uses `Box<T>` in order to have a known
+size
+
+The `Cons` variant needs the size of an `i32` plus the space to store the
+box’s pointer data. The `Nil` variant stores no values, so it needs less space
+than the `Cons` variant. We now know that any `List` value will take up the
+size of an `i32` plus the size of a box’s pointer data. By using a box, we’ve
+broken the infinite, recursive chain, so the compiler can figure out the size
+it needs to store a `List` value. Figure 15-2 shows what the `Cons` variant
+looks like now.
+
+<img alt="A finite Cons list" src="img/trpl15-02.svg" class="center" />
+
+Figure 15-2: A `List` that is not infinitely sized because `Cons` holds a `Box`
+
+Boxes provide only the indirection and heap allocation; they don’t have any
+other special capabilities, like those we’ll see with the other smart pointer
+types. They also don’t have the performance overhead that these special
+capabilities incur, so they can be useful in cases like the cons list where the
+indirection is the only feature we need. We’ll look at more use cases for boxes
+in Chapter 17, too.
+
+The `Box<T>` type is a smart pointer because it implements the `Deref` trait,
+which allows `Box<T>` values to be treated like references. When a `Box<T>`
+value goes out of scope, the heap data that the box is pointing to is cleaned
+up as well because of the `Drop` trait implementation. These two traits will be
+even more important to the functionality provided by the other smart pointer
+types we’ll discuss in the rest of this chapter. Let’s explore these two traits
+in more detail.
+
+## Treating Smart Pointers Like Regular References with the `Deref` Trait
+
+Implementing the `Deref` trait allows you to customize the behavior of the
+*dereference operator* `*` (not to be confused with the multiplication or glob
+operator). By implementing `Deref` in such a way that a smart pointer can be
+treated like a regular reference, you can write code that operates on
+references and use that code with smart pointers too.
+
+Let’s first look at how the dereference operator works with regular references.
+Then we’ll try to define a custom type that behaves like `Box<T>`, and see why
+the dereference operator doesn’t work like a reference on our newly defined
+type. We’ll explore how implementing the `Deref` trait makes it possible for
+smart pointers to work in ways similar to references. Then we’ll look at
+Rust’s *deref coercion* feature and how it lets us work with either references
+or smart pointers.
+
+> Note: there’s one big difference between the `MyBox<T>` type we’re about to
+> build and the real `Box<T>`: our version will not store its data on the heap.
+> We are focusing this example on `Deref`, so where the data is actually stored
+> is less important than the pointer-like behavior.
+
+### Following the Pointer to the Value
+
+A regular reference is a type of pointer, and one way to think of a pointer is
+as an arrow to a value stored somewhere else. In Listing 15-6, we create a
+reference to an `i32` value and then use the dereference operator to follow the
+reference to the value:
+
+Filename: src/main.rs
+
+```
+fn main() {
+    [1] let x = 5;
+    [2] let y = &x;
+
+    [3] assert_eq!(5, x);
+    [4] assert_eq!(5, *y);
+}
+```
+
+Listing 15-6: Using the dereference operator to follow a reference to an `i32`
+value
+
+The variable `x` holds an `i32` value `5` [1]. We set `y` equal to a reference
+to `x` [2]. We can assert that `x` is equal to `5` [3]. However, if we want to
+make an assertion about the value in `y`, we have to use `*y` to follow the
+reference to the value it’s pointing to (hence *dereference*) so the compiler
+can compare the actual value [4]. Once we dereference `y`, we have access to
+the integer value `y` is pointing to that we can compare with `5`.
+
+If we tried to write `assert_eq!(5, y);` instead, we would get this compilation
+error:
+
+```
+error[E0277]: can't compare `{integer}` with `&{integer}`
+ --> src/main.rs:6:5
+  |
+6 |     assert_eq!(5, y);
+  |     ^^^^^^^^^^^^^^^^ no implementation for `{integer} == &{integer}`
+  |
+  = help: the trait `PartialEq<&{integer}>` is not implemented for `{integer}`
+```
+
+Comparing a number and a reference to a number isn’t allowed because they’re
+different types. We must use the dereference operator to follow the reference
+to the value it’s pointing to.
+
+### Using `Box<T>` Like a Reference
+
+We can rewrite the code in Listing 15-6 to use a `Box<T>` instead of a
+reference; the dereference operator used on the `Box<T>` in Listing 15-7
+functions in the same way as the dereference operator used on the reference in
+Listing 15-6:
+
+Filename: src/main.rs
+
+```
+fn main() {
+    let x = 5;
+    [1] let y = Box::new(x);
+
+    assert_eq!(5, x);
+    [2] assert_eq!(5, *y);
+}
+```
+
+Listing 15-7: Using the dereference operator on a `Box<i32>`
+
+The main difference between Listing 15-7 and Listing 15-6 is that here we set
+`y` to be an instance of a box pointing to a copied value of `x` rather than a
+reference pointing to the value of `x` [1]. In the last assertion [2], we can
+use the dereference operator to follow the box’s pointer in the same way that
+we did when `y` was a reference. Next, we’ll explore what is special about
+`Box<T>` that enables us to use the dereference operator by defining our own
+box type.
+
+### Defining Our Own Smart Pointer
+
+Let’s build a smart pointer similar to the `Box<T>` type provided by the
+standard library to experience how smart pointers behave differently from
+references by default. Then we’ll look at how to add the ability to use the
+dereference operator.
+
+The `Box<T>` type is ultimately defined as a tuple struct with one element, so
+Listing 15-8 defines a `MyBox<T>` type in the same way. We’ll also define a
+`new` function to match the `new` function defined on `Box<T>`.
+
+Filename: src/main.rs
+
+```
+[1] struct MyBox<T>(T);
+
+impl<T> MyBox<T> {
+    [2] fn new(x: T) -> MyBox<T> {
+        [3] MyBox(x)
+    }
+}
+```
+
+Listing 15-8: Defining a `MyBox<T>` type
+
+We define a struct named `MyBox` and declare a generic parameter `T` [1],
+because we want our type to hold values of any type. The `MyBox` type is a
+tuple struct with one element of type `T`. The `MyBox::new` function takes one
+parameter of type `T` [2] and returns a `MyBox` instance that holds the value
+passed in [3].
+
+Let’s try adding the `main` function in Listing 15-7 to Listing 15-8 and
+changing it to use the `MyBox<T>` type we’ve defined instead of `Box<T>`. The
+code in Listing 15-9 won’t compile because Rust doesn’t know how to dereference
+`MyBox`.
+
+Filename: src/main.rs
+
+```
+fn main() {
+    let x = 5;
+    let y = MyBox::new(x);
+
+    assert_eq!(5, x);
+    assert_eq!(5, *y);
+}
+```
+
+Listing 15-9: Attempting to use `MyBox<T>` in the same way we used references
+and `Box<T>`
+
+Here’s the resulting compilation error:
+
+```
+error[E0614]: type `MyBox<{integer}>` cannot be dereferenced
+  --> src/main.rs:14:19
+   |
+14 |     assert_eq!(5, *y);
+   |                   ^^
+```
+
+Our `MyBox<T>` type can’t be dereferenced because we haven’t implemented that
+ability on our type. To enable dereferencing with the `*` operator, we
+implement the `Deref` trait.
+
+### Treating a Type Like a Reference by Implementing the `Deref` Trait
+
+As discussed in the “Implementing a Trait on a Type” section of Chapter 10, to
+implement a trait, we need to provide implementations for the trait’s required
+methods. The `Deref` trait, provided by the standard library, requires us to
+implement one method named `deref` that borrows `self` and returns a reference
+to the inner data. Listing 15-10 contains an implementation of `Deref` to add
+to the definition of `MyBox`:
+
+Filename: src/main.rs
+
+```
+use std::ops::Deref;
+
+impl<T> Deref for MyBox<T> {
+    [1] type Target = T;
+
+    fn deref(&self) -> &Self::Target {
+        [2] &self.0
+    }
+}
+```
+
+Listing 15-10: Implementing `Deref` on `MyBox<T>`
+
+The `type Target = T;` syntax [1] defines an associated type for the `Deref`
+trait to use. Associated types are a slightly different way of declaring a
+generic parameter, but you don’t need to worry about them for now; we’ll cover
+them in more detail in Chapter 19.
+
+We fill in the body of the `deref` method with `&self.0` so `deref` returns a
+reference to the value we want to access with the `*` operator [2]; recall from
+the “Using Tuple Structs without Named Fields to Create Different Types”
+section of Chapter 5 that `.0` accesses the first value in a tuple struct. The
+`main` function in Listing 15-9 that calls `*` on the `MyBox<T>` value now
+compiles, and the assertions pass!
+
+Without the `Deref` trait, the compiler can only dereference `&` references.
+The `deref` method gives the compiler the ability to take a value of any type
+that implements `Deref` and call the `deref` method to get a `&` reference that
+it knows how to dereference.
+
+When we entered `*y` in Listing 15-9, behind the scenes Rust actually ran this
+code:
+
+```
+*(y.deref())
+```
+
+Rust substitutes the `*` operator with a call to the `deref` method and then a
+plain dereference so we don’t have to think about whether or not we need to
+call the `deref` method. This Rust feature lets us write code that functions
+identically whether we have a regular reference or a type that implements
+`Deref`.
+
+The reason the `deref` method returns a reference to a value, and that the
+plain dereference outside the parentheses in `*(y.deref())` is still necessary,
+is to do with the ownership system. If the `deref` method returned the value
+directly instead of a reference to the value, the value would be moved out of
+`self`. We don’t want to take ownership of the inner value inside `MyBox<T>` in
+this case or in most cases where we use the dereference operator.
+
+Note that the `*` operator is replaced with a call to the `deref` method and
+then a call to the `*` operator just once, each time we use a `*` in our code.
+Because the substitution of the `*` operator does not recurse infinitely, we
+end up with data of type `i32`, which matches the `5` in `assert_eq!` in
+Listing 15-9.
+
+### Implicit Deref Coercions with Functions and Methods
+
+*Deref coercion* converts a reference to a type that implements the `Deref`
+trait into a reference to another type. For example, deref coercion can convert
+`&String` to `&str` because `String` implements the `Deref` trait such that it
+returns `&str`. Deref coercion is a convenience Rust performs on arguments to
+functions and methods, and works only on types that implement the `Deref`
+trait. It happens automatically when we pass a reference to a particular type’s
+value as an argument to a function or method that doesn’t match the parameter
+type in the function or method definition. A sequence of calls to the `deref`
+method converts the type we provided into the type the parameter needs.
+
+Deref coercion was added to Rust so that programmers writing function and
+method calls don’t need to add as many explicit references and dereferences
+with `&` and `*`. The deref coercion feature also lets us write more code that
+can work for either references or smart pointers.
+
+To see deref coercion in action, let’s use the `MyBox<T>` type we defined in
+Listing 15-8 as well as the implementation of `Deref` that we added in Listing
+15-10. Listing 15-11 shows the definition of a function that has a string slice
+parameter:
+
+Filename: src/main.rs
+
+```
+fn hello(name: &str) {
+    println!("Hello, {name}!");
+}
+```
+
+Listing 15-11: A `hello` function that has the parameter `name` of type `&str`
+
+We can call the `hello` function with a string slice as an argument, such as
+`hello("Rust");` for example. Deref coercion makes it possible to call `hello`
+with a reference to a value of type `MyBox<String>`, as shown in Listing 15-12:
+
+Filename: src/main.rs
+
+```
+fn main() {
+    let m = MyBox::new(String::from("Rust"));
+    hello(&m);
+}
+```
+
+Listing 15-12: Calling `hello` with a reference to a `MyBox<String>` value,
+which works because of deref coercion
+
+Here we’re calling the `hello` function with the argument `&m`, which is a
+reference to a `MyBox<String>` value. Because we implemented the `Deref` trait
+on `MyBox<T>` in Listing 15-10, Rust can turn `&MyBox<String>` into `&String`
+by calling `deref`. The standard library provides an implementation of `Deref`
+on `String` that returns a string slice, and this is in the API documentation
+for `Deref`. Rust calls `deref` again to turn the `&String` into `&str`, which
+matches the `hello` function’s definition.
+
+If Rust didn’t implement deref coercion, we would have to write the code in
+Listing 15-13 instead of the code in Listing 15-12 to call `hello` with a value
+of type `&MyBox<String>`.
+
+Filename: src/main.rs
+
+```
+fn main() {
+    let m = MyBox::new(String::from("Rust"));
+    hello(&(*m)[..]);
+}
+```
+
+Listing 15-13: The code we would have to write if Rust didn’t have deref
+coercion
+
+The `(*m)` dereferences the `MyBox<String>` into a `String`. Then the `&` and
+`[..]` take a string slice of the `String` that is equal to the whole string to
+match the signature of `hello`. This code without deref coercions is harder to
+read, write, and understand with all of these symbols involved. Deref coercion
+allows Rust to handle these conversions for us automatically.
+
+When the `Deref` trait is defined for the types involved, Rust will analyze the
+types and use `Deref::deref` as many times as necessary to get a reference to
+match the parameter’s type. The number of times that `Deref::deref` needs to be
+inserted is resolved at compile time, so there is no runtime penalty for taking
+advantage of deref coercion!
+
+### How Deref Coercion Interacts with Mutability
+
+Similar to how you use the `Deref` trait to override the `*` operator on
+immutable references, you can use the `DerefMut` trait to override the `*`
+operator on mutable references.
+
+Rust does deref coercion when it finds types and trait implementations in three
+cases:
+
+* From `&T` to `&U` when `T: Deref<Target=U>`
+* From `&mut T` to `&mut U` when `T: DerefMut<Target=U>`
+* From `&mut T` to `&U` when `T: Deref<Target=U>`
+
+The first two cases are the same as each other except that the second
+implements mutability. The first case states that if you have a `&T`, and `T`
+implements `Deref` to some type `U`, you can get a `&U` transparently. The
+second case states that the same deref coercion happens for mutable references.
+
+The third case is trickier: Rust will also coerce a mutable reference to an
+immutable one. But the reverse is *not* possible: immutable references will
+never coerce to mutable references. Because of the borrowing rules, if you have
+a mutable reference, that mutable reference must be the only reference to that
+data (otherwise, the program wouldn’t compile). Converting one mutable
+reference to one immutable reference will never break the borrowing rules.
+Converting an immutable reference to a mutable reference would require that the
+initial immutable reference is the only immutable reference to that data, but
+the borrowing rules don’t guarantee that. Therefore, Rust can’t make the
+assumption that converting an immutable reference to a mutable reference is
+possible.
+
+## Running Code on Cleanup with the `Drop` Trait
+
+The second trait important to the smart pointer pattern is `Drop`, which lets
+you customize what happens when a value is about to go out of scope. You can
+provide an implementation for the `Drop` trait on any type, and that code
+can be used to release resources like files or network connections.
+
+We’re introducing `Drop` in the context of smart pointers because the
+functionality of the `Drop` trait is almost always used when implementing a
+smart pointer. For example, when a `Box<T>` is dropped it will deallocate the
+space on the heap that the box points to.
+
+In some languages, for some types, the programmer must call code to free memory
+or resources every time they finish using an instance of those types. Examples
+include file handles, sockets, or locks. If they forget, the system might
+become overloaded and crash. In Rust, you can specify that a particular bit of
+code be run whenever a value goes out of scope, and the compiler will insert
+this code automatically. As a result, you don’t need to be careful about
+placing cleanup code everywhere in a program that an instance of a particular
+type is finished with—you still won’t leak resources!
+
+You specify the code to run when a value goes out of scope by implementing the
+`Drop` trait. The `Drop` trait requires you to implement one method named
+`drop` that takes a mutable reference to `self`. To see when Rust calls `drop`,
+let’s implement `drop` with `println!` statements for now.
+
+Listing 15-14 shows a `CustomSmartPointer` struct whose only custom
+functionality is that it will print `Dropping CustomSmartPointer!` when the
+instance goes out of scope, to show when Rust runs the `drop` function.
+
+Filename: src/main.rs
+
+```
+struct CustomSmartPointer {
+    data: String,
+}
+
+[1] impl Drop for CustomSmartPointer {
+    fn drop(&mut self) {
+        [2] println!("Dropping CustomSmartPointer with data `{}`!", self.data);
+    }
+}
+
+fn main() {
+    [3] let c = CustomSmartPointer {
+        data: String::from("my stuff"),
+    };
+    [4] let d = CustomSmartPointer {
+        data: String::from("other stuff"),
+    };
+    [5] println!("CustomSmartPointers created.");
+[6] }
+```
+
+Listing 15-14: A `CustomSmartPointer` struct that implements the `Drop` trait
+where we would put our cleanup code
+
+The `Drop` trait is included in the prelude, so we don’t need to bring it into
+scope. We implement the `Drop` trait on `CustomSmartPointer` [1] and provide an
+implementation for the `drop` method that calls `println!` [2]. The body of the
+`drop` function is where you would place any logic that you wanted to run when
+an instance of your type goes out of scope. We’re printing some text here to
+demonstrate visually when Rust will call `drop`.
+
+In `main`, we create two instances of `CustomSmartPointer` [3][4] and then
+print `CustomSmartPointers created` [5]. At the end of `main` [6], our
+instances of `CustomSmartPointer` will go out of scope, and Rust will call the
+code we put in the `drop` method [2], printing our final message. Note that we
+didn’t need to call the `drop` method explicitly.
+
+When we run this program, we’ll see the following output:
+
+```
+CustomSmartPointers created.
+Dropping CustomSmartPointer with data `other stuff`!
+Dropping CustomSmartPointer with data `my stuff`!
+```
+
+Rust automatically called `drop` for us when our instances went out of scope,
+calling the code we specified. Variables are dropped in the reverse order of
+their creation, so `d` was dropped before `c`. This example's purpose is to
+give you a visual guide to how the `drop` method works; usually you would
+specify the cleanup code that your type needs to run rather than a print
+message.
+
+### Dropping a Value Early with `std::mem::drop`
+
+Unfortunately, it’s not straightforward to disable the automatic `drop`
+functionality. Disabling `drop` isn’t usually necessary; the whole point of the
+`Drop` trait is that it’s taken care of automatically. Occasionally, however,
+you might want to clean up a value early. One example is when using smart
+pointers that manage locks: you might want to force the `drop` method that
+releases the lock so that other code in the same scope can acquire the lock.
+Rust doesn’t let you call the `Drop` trait’s `drop` method manually; instead
+you have to call the `std::mem::drop` function provided by the standard library
+if you want to force a value to be dropped before the end of its scope.
+
+If we try to call the `Drop` trait’s `drop` method manually by modifying the
+`main` function from Listing 15-14, as shown in Listing 15-15, we’ll get a
+compiler error:
+
+Filename: src/main.rs
+
+```
+fn main() {
+    let c = CustomSmartPointer {
+        data: String::from("some data"),
+    };
+    println!("CustomSmartPointer created.");
+    c.drop();
+    println!("CustomSmartPointer dropped before the end of main.");
+}
+```
+
+Listing 15-15: Attempting to call the `drop` method from the `Drop` trait
+manually to clean up early
+
+When we try to compile this code, we’ll get this error:
+
+```
+error[E0040]: explicit use of destructor method
+  --> src/main.rs:16:7
+   |
+16 |     c.drop();
+   |     --^^^^--
+   |     | |
+   |     | explicit destructor calls not allowed
+```
+
+This error message states that we’re not allowed to explicitly call `drop`. The
+error message uses the term *destructor*, which is the general programming term
+for a function that cleans up an instance. A *destructor* is analogous to a
+*constructor*, which creates an instance. The `drop` function in Rust is one
+particular destructor.
+
+Rust doesn’t let us call `drop` explicitly because Rust would still
+automatically call `drop` on the value at the end of `main`. This would cause a
+*double free* error because Rust would be trying to clean up the same value
+twice.
+
+We can’t disable the automatic insertion of `drop` when a value goes out of
+scope, and we can’t call the `drop` method explicitly. So, if we need to force
+a value to be cleaned up early, we use the `std::mem::drop` function.
+
+The `std::mem::drop` function is different from the `drop` method in the `Drop`
+trait. We call it by passing as an argument the value we want to force drop.
+The function is in the prelude, so we can modify `main` in Listing 15-15 to
+call the `drop` function, as shown in Listing 15-16:
+
+Filename: src/main.rs
+
+```
+fn main() {
+    let c = CustomSmartPointer {
+        data: String::from("some data"),
+    };
+    println!("CustomSmartPointer created.");
+    drop(c);
+    println!("CustomSmartPointer dropped before the end of main.");
+}
+```
+
+Listing 15-16: Calling `std::mem::drop` to explicitly drop a value before it
+goes out of scope
+
+Running this code will print the following:
+
+```
+CustomSmartPointer created.
+Dropping CustomSmartPointer with data `some data`!
+CustomSmartPointer dropped before the end of main.
+```
+
+The text ```Dropping CustomSmartPointer with data `some data`!``` is printed
+between the `CustomSmartPointer created.` and `CustomSmartPointer dropped
+before the end of main.` text, showing that the `drop` method code is called to
+drop `c` at that point.
+
+You can use code specified in a `Drop` trait implementation in many ways to
+make cleanup convenient and safe: for instance, you could use it to create your
+own memory allocator! With the `Drop` trait and Rust’s ownership system, you
+don’t have to remember to clean up because Rust does it automatically.
+
+You also don’t have to worry about problems resulting from accidentally
+cleaning up values still in use: the ownership system that makes sure
+references are always valid also ensures that `drop` gets called only once when
+the value is no longer being used.
+
+Now that we’ve examined `Box<T>` and some of the characteristics of smart
+pointers, let’s look at a few other smart pointers defined in the standard
+library.
+
+## `Rc<T>`, the Reference Counted Smart Pointer
+
+In the majority of cases, ownership is clear: you know exactly which variable
+owns a given value. However, there are cases when a single value might have
+multiple owners. For example, in graph data structures, multiple edges might
+point to the same node, and that node is conceptually owned by all of the edges
+that point to it. A node shouldn’t be cleaned up unless it doesn’t have any
+edges pointing to it and so has no owners.
+
+You have to enable multiple ownership explicitly by using the Rust type
+`Rc<T>`, which is an abbreviation for *reference counting*. The `Rc<T>` type
+keeps track of the number of references to a value to determine whether or not
+the value is still in use. If there are zero references to a value, the value
+can be cleaned up without any references becoming invalid.
+
+Imagine `Rc<T>` as a TV in a family room. When one person enters to watch TV,
+they turn it on. Others can come into the room and watch the TV. When the last
+person leaves the room, they turn off the TV because it’s no longer being used.
+If someone turns off the TV while others are still watching it, there would be
+uproar from the remaining TV watchers!
+
+We use the `Rc<T>` type when we want to allocate some data on the heap for
+multiple parts of our program to read and we can’t determine at compile time
+which part will finish using the data last. If we knew which part would finish
+last, we could just make that part the data’s owner, and the normal ownership
+rules enforced at compile time would take effect.
+
+Note that `Rc<T>` is only for use in single-threaded scenarios. When we discuss
+concurrency in Chapter 16, we’ll cover how to do reference counting in
+multithreaded programs.
+
+### Using `Rc<T>` to Share Data
+
+Let’s return to our cons list example in Listing 15-5. Recall that we defined
+it using `Box<T>`. This time, we’ll create two lists that both share ownership
+of a third list. Conceptually, this looks similar to Figure 15-3:
+
+<img alt="Two lists that share ownership of a third list" src="img/trpl15-03.svg" class="center" />
+
+Figure 15-3: Two lists, `b` and `c`, sharing ownership of a third list, `a`
+
+We’ll create list `a` that contains 5 and then 10. Then we’ll make two more
+lists: `b` that starts with 3 and `c` that starts with 4. Both `b` and `c`
+lists will then continue on to the first `a` list containing 5 and 10. In other
+words, both lists will share the first list containing 5 and 10.
+
+Trying to implement this scenario using our definition of `List` with `Box<T>`
+won’t work, as shown in Listing 15-17:
+
+Filename: src/main.rs
+
+```
+enum List {
+    Cons(i32, Box<List>),
+    Nil,
+}
+
+use crate::List::{Cons, Nil};
+
+fn main() {
+    let a = Cons(5, Box::new(Cons(10, Box::new(Nil))));
+[1]    let b = Cons(3, Box::new(a));
+[2]    let c = Cons(4, Box::new(a));
+}
+```
+
+Listing 15-17: Demonstrating we’re not allowed to have two lists using `Box<T>`
+that try to share ownership of a third list
+
+When we compile this code, we get this error:
+
+```
+error[E0382]: use of moved value: `a`
+  --> src/main.rs:11:30
+   |
+9  |     let a = Cons(5, Box::new(Cons(10, Box::new(Nil))));
+   |         - move occurs because `a` has type `List`, which does not implement the `Copy` trait
+10 |     let b = Cons(3, Box::new(a));
+   |                              - value moved here
+11 |     let c = Cons(4, Box::new(a));
+   |                              ^ value used here after move
+```
+
+The `Cons` variants own the data they hold, so when we create the `b` list [1],
+`a` is moved into `b` and `b` owns `a`. Then, when we try to use `a` again when
+creating `c` [2], we’re not allowed to because `a` has been moved.
+
+We could change the definition of `Cons` to hold references instead, but then
+we would have to specify lifetime parameters. By specifying lifetime
+parameters, we would be specifying that every element in the list will live at
+least as long as the entire list. This is the case for the elements and lists
+in Listing 15-17, but not in every scenario.
+
+Instead, we’ll change our definition of `List` to use `Rc<T>` in place of
+`Box<T>`, as shown in Listing 15-18. Each `Cons` variant will now hold a value
+and an `Rc<T>` pointing to a `List`. When we create `b`, instead of taking
+ownership of `a`, we’ll clone the `Rc<List>` that `a` is holding, thereby
+increasing the number of references from one to two and letting `a` and `b`
+share ownership of the data in that `Rc<List>`. We’ll also clone `a` when
+creating `c`, increasing the number of references from two to three. Every time
+we call `Rc::clone`, the reference count to the data within the `Rc<List>` will
+increase, and the data won’t be cleaned up unless there are zero references to
+it.
+
+Filename: src/main.rs
+
+```
+enum List {
+    Cons(i32, Rc<List>),
+    Nil,
+}
+
+use crate::List::{Cons, Nil};
+[1] use std::rc::Rc;
+
+fn main() {
+[2]    let a = Rc::new(Cons(5, Rc::new(Cons(10, Rc::new(Nil)))));
+[3]    let b = Cons(3, Rc::clone(&a));
+[4]    let c = Cons(4, Rc::clone(&a));
+}
+```
+
+Listing 15-18: A definition of `List` that uses `Rc<T>`
+
+We need to add a `use` statement to bring `Rc<T>` into scope [1] because it’s
+not in the prelude. In `main`, we create the list holding 5 and 10 and store it
+in a new `Rc<List>` in `a` [2]. Then when we create `b` [3] and `c` [4], we
+call the `Rc::clone` function and pass a reference to the `Rc<List>` in `a` as
+an argument.
+
+We could have called `a.clone()` rather than `Rc::clone(&a)`, but Rust’s
+convention is to use `Rc::clone` in this case. The implementation of
+`Rc::clone` doesn’t make a deep copy of all the data like most types’
+implementations of `clone` do. The call to `Rc::clone` only increments the
+reference count, which doesn’t take much time. Deep copies of data can take a
+lot of time. By using `Rc::clone` for reference counting, we can visually
+distinguish between the deep-copy kinds of clones and the kinds of clones that
+increase the reference count. When looking for performance problems in the
+code, we only need to consider the deep-copy clones and can disregard calls to
+`Rc::clone`.
+
+### Cloning an `Rc<T>` Increases the Reference Count
+
+Let’s change our working example in Listing 15-18 so we can see the reference
+counts changing as we create and drop references to the `Rc<List>` in `a`.
+
+In Listing 15-19, we’ll change `main` so it has an inner scope around list `c`;
+then we can see how the reference count changes when `c` goes out of scope.
+
+Filename: src/main.rs
+
+```
+fn main() {
+    let a = Rc::new(Cons(5, Rc::new(Cons(10, Rc::new(Nil)))));
+    println!("count after creating a = {}", Rc::strong_count(&a));
+    let b = Cons(3, Rc::clone(&a));
+    println!("count after creating b = {}", Rc::strong_count(&a));
+    {
+        let c = Cons(4, Rc::clone(&a));
+        println!("count after creating c = {}", Rc::strong_count(&a));
+    }
+    println!("count after c goes out of scope = {}", Rc::strong_count(&a));
+}
+```
+
+Listing 15-19: Printing the reference count
+
+At each point in the program where the reference count changes, we print the
+reference count, which we get by calling the `Rc::strong_count` function. This
+function is named `strong_count` rather than `count` because the `Rc<T>` type
+also has a `weak_count`; we’ll see what `weak_count` is used for in the
+“Preventing Reference Cycles: Turning an `Rc<T>` into a `Weak<T>`” section.
+
+This code prints the following:
+
+```
+count after creating a = 1
+count after creating b = 2
+count after creating c = 3
+count after c goes out of scope = 2
+```
+
+We can see that the `Rc<List>` in `a` has an initial reference count of 1; then
+each time we call `clone`, the count goes up by 1. When `c` goes out of scope,
+the count goes down by 1. We don’t have to call a function to decrease the
+reference count like we have to call `Rc::clone` to increase the reference
+count: the implementation of the `Drop` trait decreases the reference count
+automatically when an `Rc<T>` value goes out of scope.
+
+What we can’t see in this example is that when `b` and then `a` go out of scope
+at the end of `main`, the count is then 0, and the `Rc<List>` is cleaned up
+completely. Using `Rc<T>` allows a single value to have multiple owners, and
+the count ensures that the value remains valid as long as any of the owners
+still exist.
+
+Via immutable references, `Rc<T>` allows you to share data between multiple
+parts of your program for reading only. If `Rc<T>` allowed you to have multiple
+mutable references too, you might violate one of the borrowing rules discussed
+in Chapter 4: multiple mutable borrows to the same place can cause data races
+and inconsistencies. But being able to mutate data is very useful! In the next
+section, we’ll discuss the interior mutability pattern and the `RefCell<T>`
+type that you can use in conjunction with an `Rc<T>` to work with this
+immutability restriction.
+
+## `RefCell<T>` and the Interior Mutability Pattern
+
+*Interior mutability* is a design pattern in Rust that allows you to mutate
+data even when there are immutable references to that data; normally, this
+action is disallowed by the borrowing rules. To mutate data, the pattern uses
+`unsafe` code inside a data structure to bend Rust’s usual rules that govern
+mutation and borrowing. Unsafe code indicates to the compiler that we’re
+checking the rules manually instead of relying on the compiler to check them
+for us; we will discuss unsafe code more in Chapter 19.
+
+We can use types that use the interior mutability pattern only when we can
+ensure that the borrowing rules will be followed at runtime, even though the
+compiler can’t guarantee that. The `unsafe` code involved is then wrapped in a
+safe API, and the outer type is still immutable.
+
+Let’s explore this concept by looking at the `RefCell<T>` type that follows the
+interior mutability pattern.
+
+### Enforcing Borrowing Rules at Runtime with `RefCell<T>`
+
+Unlike `Rc<T>`, the `RefCell<T>` type represents single ownership over the data
+it holds. So, what makes `RefCell<T>` different from a type like `Box<T>`?
+Recall the borrowing rules you learned in Chapter 4:
+
+* At any given time, you can have *either* (but not both) one mutable reference
+  or any number of immutable references.
+* References must always be valid.
+
+With references and `Box<T>`, the borrowing rules’ invariants are enforced at
+compile time. With `RefCell<T>`, these invariants are enforced *at runtime*.
+With references, if you break these rules, you’ll get a compiler error. With
+`RefCell<T>`, if you break these rules, your program will panic and exit.
+
+The advantages of checking the borrowing rules at compile time are that errors
+will be caught sooner in the development process, and there is no impact on
+runtime performance because all the analysis is completed beforehand. For those
+reasons, checking the borrowing rules at compile time is the best choice in the
+majority of cases, which is why this is Rust’s default.
+
+The advantage of checking the borrowing rules at runtime instead is that
+certain memory-safe scenarios are then allowed, where they would’ve been
+disallowed by the compile-time checks. Static analysis, like the Rust compiler,
+is inherently conservative. Some properties of code are impossible to detect by
+analyzing the code: the most famous example is the Halting Problem, which is
+beyond the scope of this book but is an interesting topic to research.
+
+Because some analysis is impossible, if the Rust compiler can’t be sure the
+code complies with the ownership rules, it might reject a correct program; in
+this way, it’s conservative. If Rust accepted an incorrect program, users
+wouldn’t be able to trust in the guarantees Rust makes. However, if Rust
+rejects a correct program, the programmer will be inconvenienced, but nothing
+catastrophic can occur. The `RefCell<T>` type is useful when you’re sure your
+code follows the borrowing rules but the compiler is unable to understand and
+guarantee that.
+
+Similar to `Rc<T>`, `RefCell<T>` is only for use in single-threaded scenarios
+and will give you a compile-time error if you try using it in a multithreaded
+context. We’ll talk about how to get the functionality of `RefCell<T>` in a
+multithreaded program in Chapter 16.
+
+Here is a recap of the reasons to choose `Box<T>`, `Rc<T>`, or `RefCell<T>`:
+
+* `Rc<T>` enables multiple owners of the same data; `Box<T>` and `RefCell<T>`
+  have single owners.
+* `Box<T>` allows immutable or mutable borrows checked at compile time; `Rc<T>`
+  allows only immutable borrows checked at compile time; `RefCell<T>` allows
+  immutable or mutable borrows checked at runtime.
+* Because `RefCell<T>` allows mutable borrows checked at runtime, you can
+  mutate the value inside the `RefCell<T>` even when the `RefCell<T>` is
+  immutable.
+
+Mutating the value inside an immutable value is the *interior mutability*
+pattern. Let’s look at a situation in which interior mutability is useful and
+examine how it’s possible.
+
+### Interior Mutability: A Mutable Borrow to an Immutable Value
+
+A consequence of the borrowing rules is that when you have an immutable value,
+you can’t borrow it mutably. For example, this code won’t compile:
+
+```
+fn main() {
+    let x = 5;
+    let y = &mut x;
+}
+```
+
+If you tried to compile this code, you’d get the following error:
+
+```
+error[E0596]: cannot borrow `x` as mutable, as it is not declared as mutable
+ --> src/main.rs:3:13
+  |
+2 |     let x = 5;
+  |         - help: consider changing this to be mutable: `mut x`
+3 |     let y = &mut x;
+  |             ^^^^^^ cannot borrow as mutable
+```
+
+However, there are situations in which it would be useful for a value to mutate
+itself in its methods but appear immutable to other code. Code outside the
+value’s methods would not be able to mutate the value. Using `RefCell<T>` is
+one way to get the ability to have interior mutability, but `RefCell<T>`
+doesn’t get around the borrowing rules completely: the borrow checker in the
+compiler allows this interior mutability, and the borrowing rules are checked
+at runtime instead. If you violate the rules, you’ll get a `panic!` instead of
+a compiler error.
+
+Let’s work through a practical example where we can use `RefCell<T>` to mutate
+an immutable value and see why that is useful.
+
+#### A Use Case for Interior Mutability: Mock Objects
+
+Sometimes during testing a programmer will use a type in place of another type,
+in order to observe particular behavior and assert it's implemented correctly.
+This placeholder type is called a *test double*. Think of it in the sense of a
+"stunt double" in filmmaking, where a person steps in and substitutes for an
+actor to do a particular tricky scene. Test doubles stand in for other types
+when we're running tests. *Mock objects* are specific types of test doubles
+that record what happens during a test so you can assert that the correct
+actions took place.
+
+Rust doesn’t have objects in the same sense as other languages have objects,
+and Rust doesn’t have mock object functionality built into the standard library
+as some other languages do. However, you can definitely create a struct that
+will serve the same purposes as a mock object.
+
+Here’s the scenario we’ll test: we’ll create a library that tracks a value
+against a maximum value and sends messages based on how close to the maximum
+value the current value is. This library could be used to keep track of a
+user’s quota for the number of API calls they’re allowed to make, for example.
+
+Our library will only provide the functionality of tracking how close to the
+maximum a value is and what the messages should be at what times. Applications
+that use our library will be expected to provide the mechanism for sending the
+messages: the application could put a message in the application, send an
+email, send a text message, or something else. The library doesn’t need to know
+that detail. All it needs is something that implements a trait we’ll provide
+called `Messenger`. Listing 15-20 shows the library code:
+
+Filename: src/lib.rs
+
+```
+pub trait Messenger {
+[1]    fn send(&self, msg: &str);
+}
+
+pub struct LimitTracker<'a, T: Messenger> {
+    messenger: &'a T,
+    value: usize,
+    max: usize,
+}
+
+impl<'a, T> LimitTracker<'a, T>
+where
+    T: Messenger,
+{
+    pub fn new(messenger: &'a T, max: usize) -> LimitTracker<'a, T> {
+        LimitTracker {
+            messenger,
+            value: 0,
+            max,
+        }
+    }
+
+[2]    pub fn set_value(&mut self, value: usize) {
+        self.value = value;
+
+        let percentage_of_max = self.value as f64 / self.max as f64;
+
+        if percentage_of_max >= 1.0 {
+            self.messenger.send("Error: You are over your quota!");
+        } else if percentage_of_max >= 0.9 {
+            self.messenger
+                .send("Urgent warning: You've used up over 90% of your quota!");
+        } else if percentage_of_max >= 0.75 {
+            self.messenger
+                .send("Warning: You've used up over 75% of your quota!");
+        }
+    }
+}
+```
+
+Listing 15-20: A library to keep track of how close a value is to a maximum
+value and warn when the value is at certain levels
+
+One important part of this code is that the `Messenger` trait has one method
+called `send` that takes an immutable reference to `self` and the text of the
+message [1]. This trait is the interface our mock object needs to implement so
+that the mock can be used in the same way a real object is. The other important
+part is that we want to test the behavior of the `set_value` method on the
+`LimitTracker` [2]. We can change what we pass in for the `value` parameter,
+but `set_value` doesn’t return anything for us to make assertions on. We want
+to be able to say that if we create a `LimitTracker` with something that
+implements the `Messenger` trait and a particular value for `max`, when we pass
+different numbers for `value`, the messenger is told to send the appropriate
+messages.
+
+We need a mock object that, instead of sending an email or text message when we
+call `send`, will only keep track of the messages it’s told to send. We can
+create a new instance of the mock object, create a `LimitTracker` that uses the
+mock object, call the `set_value` method on `LimitTracker`, and then check that
+the mock object has the messages we expect. Listing 15-21 shows an attempt to
+implement a mock object to do just that, but the borrow checker won’t allow it:
+
+Filename: src/lib.rs
+
+```
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    [1] struct MockMessenger {
+        [2] sent_messages: Vec<String>,
+    }
+
+    impl MockMessenger {
+        [3] fn new() -> MockMessenger {
+            MockMessenger {
+                sent_messages: vec![],
+            }
+        }
+    }
+
+    [4] impl Messenger for MockMessenger {
+        fn send(&self, message: &str) {
+            [5] self.sent_messages.push(String::from(message));
+        }
+    }
+
+    #[test]
+    [6] fn it_sends_an_over_75_percent_warning_message() {
+        let mock_messenger = MockMessenger::new();
+        let mut limit_tracker = LimitTracker::new(&mock_messenger, 100);
+
+        limit_tracker.set_value(80);
+
+        assert_eq!(mock_messenger.sent_messages.len(), 1);
+    }
+}
+```
+
+Listing 15-21: An attempt to implement a `MockMessenger` that isn’t allowed by
+the borrow checker
+
+This test code defines a `MockMessenger` struct [1] that has a `sent_messages`
+field with a `Vec` of `String` values [2] to keep track of the messages it’s
+told to send. We also define an associated function `new` [3] to make it
+convenient to create new `MockMessenger` values that start with an empty list
+of messages. We then implement the `Messenger` trait for `MockMessenger` [4] so
+we can give a `MockMessenger` to a `LimitTracker`. In the definition of the
+`send` method [5], we take the message passed in as a parameter and store it in
+the `MockMessenger` list of `sent_messages`.
+
+In the test, we’re testing what happens when the `LimitTracker` is told to set
+`value` to something that is more than 75 percent of the `max` value [6].
+First, we create a new `MockMessenger`, which will start with an empty list of
+messages. Then we create a new `LimitTracker` and give it a reference to the
+new `MockMessenger` and a `max` value of 100. We call the `set_value` method on
+the `LimitTracker` with a value of 80, which is more than 75 percent of 100.
+Then we assert that the list of messages that the `MockMessenger` is keeping
+track of should now have one message in it.
+
+However, there’s one problem with this test, as shown here:
+
+```
+error[E0596]: cannot borrow `self.sent_messages` as mutable, as it is behind a `&` reference
+  --> src/lib.rs:58:13
+   |
+2  |     fn send(&self, msg: &str);
+   |             ----- help: consider changing that to be a mutable reference: `&mut self`
+...
+58 |             self.sent_messages.push(String::from(message));
+   |             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ `self` is a `&` reference, so the data it refers to cannot be borrowed as mutable
+```
+
+We can’t modify the `MockMessenger` to keep track of the messages, because the
+`send` method takes an immutable reference to `self`. We also can’t take the
+suggestion from the error text to use `&mut self` instead, because then the
+signature of `send` wouldn’t match the signature in the `Messenger` trait
+definition (feel free to try and see what error message you get).
+
+This is a situation in which interior mutability can help! We’ll store the
+`sent_messages` within a `RefCell<T>`, and then the `send` method will be
+able to modify `sent_messages` to store the messages we’ve seen. Listing 15-22
+shows what that looks like:
+
+Filename: src/lib.rs
+
+```
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use std::cell::RefCell;
+
+    struct MockMessenger {
+        [1] sent_messages: RefCell<Vec<String>>,
+    }
+
+    impl MockMessenger {
+        fn new() -> MockMessenger {
+            MockMessenger {
+                sent_messages: RefCell::new(vec![]) [2],
+            }
+        }
+    }
+
+    impl Messenger for MockMessenger {
+        fn send(&self, message: &str) {
+            [3] self.sent_messages.borrow_mut().push(String::from(message));
+        }
+    }
+
+    #[test]
+    fn it_sends_an_over_75_percent_warning_message() {
+        // --snip--
+
+        [4] assert_eq!(mock_messenger.sent_messages.borrow().len(), 1);
+    }
+}
+```
+
+Listing 15-22: Using `RefCell<T>` to mutate an inner value while the outer
+value is considered immutable
+
+The `sent_messages` field is now of type `RefCell<Vec<String>>` [1] instead of
+`Vec<String>`. In the `new` function, we create a new `RefCell<Vec<String>>`
+instance around the empty vector [2].
+
+For the implementation of the `send` method, the first parameter is still an
+immutable borrow of `self`, which matches the trait definition. We call
+`borrow_mut` on the `RefCell<Vec<String>>` in `self.sent_messages` [3] to get a
+mutable reference to the value inside the `RefCell<Vec<String>>`, which is
+the vector. Then we can call `push` on the mutable reference to the vector to
+keep track of the messages sent during the test.
+
+The last change we have to make is in the assertion: to see how many items are
+in the inner vector, we call `borrow` on the `RefCell<Vec<String>>` to get an
+immutable reference to the vector [4].
+
+Now that you’ve seen how to use `RefCell<T>`, let’s dig into how it works!
+
+#### Keeping Track of Borrows at Runtime with `RefCell<T>`
+
+When creating immutable and mutable references, we use the `&` and `&mut`
+syntax, respectively. With `RefCell<T>`, we use the `borrow` and `borrow_mut`
+methods, which are part of the safe API that belongs to `RefCell<T>`. The
+`borrow` method returns the smart pointer type `Ref<T>`, and `borrow_mut`
+returns the smart pointer type `RefMut<T>`. Both types implement `Deref`, so we
+can treat them like regular references.
+
+The `RefCell<T>` keeps track of how many `Ref<T>` and `RefMut<T>` smart
+pointers are currently active. Every time we call `borrow`, the `RefCell<T>`
+increases its count of how many immutable borrows are active. When a `Ref<T>`
+value goes out of scope, the count of immutable borrows goes down by one. Just
+like the compile-time borrowing rules, `RefCell<T>` lets us have many immutable
+borrows or one mutable borrow at any point in time.
+
+If we try to violate these rules, rather than getting a compiler error as we
+would with references, the implementation of `RefCell<T>` will panic at
+runtime. Listing 15-23 shows a modification of the implementation of `send` in
+Listing 15-22. We’re deliberately trying to create two mutable borrows active
+for the same scope to illustrate that `RefCell<T>` prevents us from doing this
+at runtime.
+
+Filename: src/lib.rs
+
+```
+    impl Messenger for MockMessenger {
+        fn send(&self, message: &str) {
+            let mut one_borrow = self.sent_messages.borrow_mut();
+            let mut two_borrow = self.sent_messages.borrow_mut();
+
+            one_borrow.push(String::from(message));
+            two_borrow.push(String::from(message));
+        }
+    }
+```
+
+Listing 15-23: Creating two mutable references in the same scope to see that
+`RefCell<T>` will panic
+
+We create a variable `one_borrow` for the `RefMut<T>` smart pointer returned
+from `borrow_mut`. Then we create another mutable borrow in the same way in the
+variable `two_borrow`. This makes two mutable references in the same scope,
+which isn’t allowed. When we run the tests for our library, the code in Listing
+15-23 will compile without any errors, but the test will fail:
+
+```
+---- tests::it_sends_an_over_75_percent_warning_message stdout ----
+thread 'main' panicked at 'already borrowed: BorrowMutError', src/lib.rs:60:53
+note: run with `RUST_BACKTRACE=1` environment variable to display a backtrace
+```
+
+Notice that the code panicked with the message `already borrowed:
+BorrowMutError`. This is how `RefCell<T>` handles violations of the borrowing
+rules at runtime.
+
+Choosing to catch borrowing errors at runtime rather than compile time, as
+we've done here, means you'd potentially be finding mistakes in your code later
+in the development process: possibly not until your code was deployed to
+production. Also, your code would incur a small runtime performance penalty as
+a result of keeping track of the borrows at runtime rather than compile time.
+However, using `RefCell<T>` makes it possible to write a mock object that can
+modify itself to keep track of the messages it has seen while you’re using it
+in a context where only immutable values are allowed. You can use `RefCell<T>`
+despite its trade-offs to get more functionality than regular references
+provide.
+
+### Having Multiple Owners of Mutable Data by Combining `Rc<T>` and `RefCell<T>`
+
+A common way to use `RefCell<T>` is in combination with `Rc<T>`. Recall that
+`Rc<T>` lets you have multiple owners of some data, but it only gives immutable
+access to that data. If you have an `Rc<T>` that holds a `RefCell<T>`, you can
+get a value that can have multiple owners *and* that you can mutate!
+
+For example, recall the cons list example in Listing 15-18 where we used
+`Rc<T>` to allow multiple lists to share ownership of another list. Because
+`Rc<T>` holds only immutable values, we can’t change any of the values in the
+list once we’ve created them. Let’s add in `RefCell<T>` to gain the ability to
+change the values in the lists. Listing 15-24 shows that by using a
+`RefCell<T>` in the `Cons` definition, we can modify the value stored in all
+the lists:
+
+Filename: src/main.rs
+
+```
+#[derive(Debug)]
+enum List {
+    Cons(Rc<RefCell<i32>>, Rc<List>),
+    Nil,
+}
+
+use crate::List::{Cons, Nil};
+use std::cell::RefCell;
+use std::rc::Rc;
+
+fn main() {
+    [1] let value = Rc::new(RefCell::new(5));
+
+    [2] let a = Rc::new(Cons(Rc::clone(&value), Rc::new(Nil)));
+
+    let b = Cons(Rc::new(RefCell::new(3)), Rc::clone(&a));
+    let c = Cons(Rc::new(RefCell::new(4)), Rc::clone(&a));
+
+    [3] *value.borrow_mut() += 10;
+
+    println!("a after = {:?}", a);
+    println!("b after = {:?}", b);
+    println!("c after = {:?}", c);
+}
+```
+
+Listing 15-24: Using `Rc<RefCell<i32>>` to create a `List` that we can mutate
+
+We create a value that is an instance of `Rc<RefCell<i32>>` and store it in a
+variable named `value` [1] so we can access it directly later. Then we create a
+`List` in `a` with a `Cons` variant that holds `value` [2]. We need to clone
+`value` so both `a` and `value` have ownership of the inner `5` value rather
+than transferring ownership from `value` to `a` or having `a` borrow from
+`value`.
+
+We wrap the list `a` in an `Rc<T>` so when we create lists `b` and `c`, they
+can both refer to `a`, which is what we did in Listing 15-18.
+
+After we’ve created the lists in `a`, `b`, and `c`, we want to add 10 to the
+value in `value` [3]. We do this by calling `borrow_mut` on `value`, which uses
+the automatic dereferencing feature we discussed in Chapter 5 (see the section
+“Where’s the `->` Operator?”) to dereference the `Rc<T>` to the inner
+`RefCell<T>` value. The `borrow_mut` method returns a `RefMut<T>` smart
+pointer, and we use the dereference operator on it and change the inner value.
+
+When we print `a`, `b`, and `c`, we can see that they all have the modified
+value of 15 rather than 5:
+
+```
+a after = Cons(RefCell { value: 15 }, Nil)
+b after = Cons(RefCell { value: 3 }, Cons(RefCell { value: 15 }, Nil))
+c after = Cons(RefCell { value: 4 }, Cons(RefCell { value: 15 }, Nil))
+```
+
+This technique is pretty neat! By using `RefCell<T>`, we have an outwardly
+immutable `List` value. But we can use the methods on `RefCell<T>` that provide
+access to its interior mutability so we can modify our data when we need to.
+The runtime checks of the borrowing rules protect us from data races, and it’s
+sometimes worth trading a bit of speed for this flexibility in our data
+structures. Note that `RefCell<T>` does not work for multithreaded code!
+`Mutex<T>` is the thread-safe version of `RefCell<T>` and we’ll discuss
+`Mutex<T>` in Chapter 16.
+
+## Reference Cycles Can Leak Memory
+
+Rust’s memory safety guarantees make it difficult, but not impossible, to
+accidentally create memory that is never cleaned up (known as a *memory leak*).
+Preventing memory leaks entirely is not one of Rust’s guarantees, meaning
+memory leaks are memory safe in Rust. We can see that Rust allows memory leaks
+by using `Rc<T>` and `RefCell<T>`: it’s possible to create references where
+items refer to each other in a cycle. This creates memory leaks because the
+reference count of each item in the cycle will never reach 0, and the values
+will never be dropped.
+
+### Creating a Reference Cycle
+
+Let’s look at how a reference cycle might happen and how to prevent it,
+starting with the definition of the `List` enum and a `tail` method in Listing
+15-25:
+
+Filename: src/main.rs
+
+```
+use crate::List::{Cons, Nil};
+use std::cell::RefCell;
+use std::rc::Rc;
+
+#[derive(Debug)]
+enum List {
+    [1] Cons(i32, RefCell<Rc<List>>),
+    Nil,
+}
+
+impl List {
+    [2] fn tail(&self) -> Option<&RefCell<Rc<List>>> {
+        match self {
+            Cons(_, item) => Some(item),
+            Nil => None,
+        }
+    }
+}
+```
+
+Listing 15-25: A cons list definition that holds a `RefCell<T>` so we can
+modify what a `Cons` variant is referring to
+
+We’re using another variation of the `List` definition from Listing 15-5. The
+second element in the `Cons` variant is now `RefCell<Rc<List>>` [1], meaning
+that instead of having the ability to modify the `i32` value as we did in
+Listing 15-24, we want to modify the `List` value a `Cons` variant is
+pointing to. We’re also adding a `tail` method [2] to make it convenient for us
+to access the second item if we have a `Cons` variant.
+
+In Listing 15-26, we’re adding a `main` function that uses the definitions in
+Listing 15-25. This code creates a list in `a` and a list in `b` that points to
+the list in `a`. Then it modifies the list in `a` to point to `b`, creating a
+reference cycle. There are `println!` statements along the way to show what the
+reference counts are at various points in this process.
+
+Filename: src/main.rs
+
+```
+fn main() {
+    [1] let a = Rc::new(Cons(5, RefCell::new(Rc::new(Nil))));
+
+    println!("a initial rc count = {}", Rc::strong_count(&a));
+    println!("a next item = {:?}", a.tail());
+
+    [2] let b = Rc::new(Cons(10, RefCell::new(Rc::clone(&a))));
+
+    println!("a rc count after b creation = {}", Rc::strong_count(&a));
+    println!("b initial rc count = {}", Rc::strong_count(&b));
+    println!("b next item = {:?}", b.tail());
+
+    [3] if let Some(link) = a.tail() {
+        [4] *link.borrow_mut() = Rc::clone(&b);
+    }
+
+    println!("b rc count after changing a = {}", Rc::strong_count(&b));
+    println!("a rc count after changing a = {}", Rc::strong_count(&a));
+
+    // Uncomment the next line to see that we have a cycle;
+    // it will overflow the stack
+    // println!("a next item = {:?}", a.tail());
+}
+```
+
+Listing 15-26: Creating a reference cycle of two `List` values pointing to each
+other
+
+We create an `Rc<List>` instance holding a `List` value in the variable `a`
+with an initial list of `5, Nil` [1]. We then create an `Rc<List>` instance
+holding another `List` value in the variable `b` that contains the value 10 and
+points to the list in `a` [2].
+
+We modify `a` so it points to `b` instead of `Nil`, creating a cycle. We do
+that by using the `tail` method to get a reference to the `RefCell<Rc<List>>`
+in `a`, which we put in the variable `link` [3]. Then we use the `borrow_mut`
+method on the `RefCell<Rc<List>>` to change the value inside from an `Rc<List>`
+that holds a `Nil` value to the `Rc<List>` in `b` [4].
+
+When we run this code, keeping the last `println!` commented out for the
+moment, we’ll get this output:
+
+```
+a initial rc count = 1
+a next item = Some(RefCell { value: Nil })
+a rc count after b creation = 2
+b initial rc count = 1
+b next item = Some(RefCell { value: Cons(5, RefCell { value: Nil }) })
+b rc count after changing a = 2
+a rc count after changing a = 2
+```
+
+The reference count of the `Rc<List>` instances in both `a` and `b` are 2 after
+we change the list in `a` to point to `b`. At the end of `main`, Rust drops the
+variable `b`, which decreases the reference count of the `b` `Rc<List>` instance
+from 2 to 1. The memory that `Rc<List>` has on the heap won’t be dropped at
+this point, because its reference count is 1, not 0. Then Rust drops `a`, which
+decreases the reference count of the `a` `Rc<List>` instance from 2 to 1 as
+well. This instance’s memory can’t be dropped either, because the other
+`Rc<List>` instance still refers to it. The memory allocated to the list will
+remain uncollected forever. To visualize this reference cycle, we’ve created a
+diagram in Figure 15-4.
+
+<img alt="Reference cycle of lists" src="img/trpl15-04.svg" class="center" />
+
+Figure 15-4: A reference cycle of lists `a` and `b` pointing to each other
+
+If you uncomment the last `println!` and run the program, Rust will try to
+print this cycle with `a` pointing to `b` pointing to `a` and so forth until it
+overflows the stack.
+
+Compared to a real-world program, the consequences creating a reference cycle
+in this example aren’t very dire: right after we create the reference cycle,
+the program ends. However, if a more complex program allocated lots of memory
+in a cycle and held onto it for a long time, the program would use more memory
+than it needed and might overwhelm the system, causing it to run out of
+available memory.
+
+Creating reference cycles is not easily done, but it’s not impossible either.
+If you have `RefCell<T>` values that contain `Rc<T>` values or similar nested
+combinations of types with interior mutability and reference counting, you must
+ensure that you don’t create cycles; you can’t rely on Rust to catch them.
+Creating a reference cycle would be a logic bug in your program that you should
+use automated tests, code reviews, and other software development practices to
+minimize.
+
+Another solution for avoiding reference cycles is reorganizing your data
+structures so that some references express ownership and some references don’t.
+As a result, you can have cycles made up of some ownership relationships and
+some non-ownership relationships, and only the ownership relationships affect
+whether or not a value can be dropped. In Listing 15-25, we always want `Cons`
+variants to own their list, so reorganizing the data structure isn’t possible.
+Let’s look at an example using graphs made up of parent nodes and child nodes
+to see when non-ownership relationships are an appropriate way to prevent
+reference cycles.
+
+### Preventing Reference Cycles: Turning an `Rc<T>` into a `Weak<T>`
+
+So far, we’ve demonstrated that calling `Rc::clone` increases the
+`strong_count` of an `Rc<T>` instance, and an `Rc<T>` instance is only cleaned
+up if its `strong_count` is 0. You can also create a *weak reference* to the
+value within an `Rc<T>` instance by calling `Rc::downgrade` and passing a
+reference to the `Rc<T>`. Strong references are how you can share ownership of
+an `Rc<T>` instance. Weak references don’t express an ownership relationship,
+and their count doesn't affect when an `Rc<T>` instance is cleaned up. They
+won’t cause a reference cycle because any cycle involving some weak references
+will be broken once the strong reference count of values involved is 0.
+
+When you call `Rc::downgrade`, you get a smart pointer of type `Weak<T>`.
+Instead of increasing the `strong_count` in the `Rc<T>` instance by 1, calling
+`Rc::downgrade` increases the `weak_count` by 1. The `Rc<T>` type uses
+`weak_count` to keep track of how many `Weak<T>` references exist, similar to
+`strong_count`. The difference is the `weak_count` doesn’t need to be 0 for the
+`Rc<T>` instance to be cleaned up.
+
+Because the value that `Weak<T>` references might have been dropped, to do
+anything with the value that a `Weak<T>` is pointing to, you must make sure the
+value still exists. Do this by calling the `upgrade` method on a `Weak<T>`
+instance, which will return an `Option<Rc<T>>`. You’ll get a result of `Some`
+if the `Rc<T>` value has not been dropped yet and a result of `None` if the
+`Rc<T>` value has been dropped. Because `upgrade` returns an `Option<Rc<T>>`,
+Rust will ensure that the `Some` case and the `None` case are handled, and
+there won’t be an invalid pointer.
+
+As an example, rather than using a list whose items know only about the next
+item, we’ll create a tree whose items know about their children items *and*
+their parent items.
+
+#### Creating a Tree Data Structure: a `Node` with Child Nodes
+
+To start, we’ll build a tree with nodes that know about their child nodes.
+We’ll create a struct named `Node` that holds its own `i32` value as well as
+references to its children `Node` values:
+
+Filename: src/main.rs
+
+```
+use std::cell::RefCell;
+use std::rc::Rc;
+
+#[derive(Debug)]
+struct Node {
+    value: i32,
+    children: RefCell<Vec<Rc<Node>>>,
+}
+```
+
+We want a `Node` to own its children, and we want to share that ownership with
+variables so we can access each `Node` in the tree directly. To do this, we
+define the `Vec<T>` items to be values of type `Rc<Node>`. We also want to
+modify which nodes are children of another node, so we have a `RefCell<T>` in
+`children` around the `Vec<Rc<Node>>`.
+
+Next, we’ll use our struct definition and create one `Node` instance named
+`leaf` with the value 3 and no children, and another instance named `branch`
+with the value 5 and `leaf` as one of its children, as shown in Listing 15-27:
+
+Filename: src/main.rs
+
+```
+fn main() {
+    let leaf = Rc::new(Node {
+        value: 3,
+        children: RefCell::new(vec![]),
+    });
+
+    let branch = Rc::new(Node {
+        value: 5,
+        children: RefCell::new(vec![Rc::clone(&leaf)]),
+    });
+}
+```
+
+Listing 15-27: Creating a `leaf` node with no children and a `branch` node with
+`leaf` as one of its children
+
+We clone the `Rc<Node>` in `leaf` and store that in `branch`, meaning the
+`Node` in `leaf` now has two owners: `leaf` and `branch`. We can get from
+`branch` to `leaf` through `branch.children`, but there’s no way to get from
+`leaf` to `branch`. The reason is that `leaf` has no reference to `branch` and
+doesn’t know they’re related. We want `leaf` to know that `branch` is its
+parent. We’ll do that next.
+
+#### Adding a Reference from a Child to Its Parent
+
+To make the child node aware of its parent, we need to add a `parent` field to
+our `Node` struct definition. The trouble is in deciding what the type of
+`parent` should be. We know it can’t contain an `Rc<T>`, because that would
+create a reference cycle with `leaf.parent` pointing to `branch` and
+`branch.children` pointing to `leaf`, which would cause their `strong_count`
+values to never be 0.
+
+Thinking about the relationships another way, a parent node should own its
+children: if a parent node is dropped, its child nodes should be dropped as
+well. However, a child should not own its parent: if we drop a child node, the
+parent should still exist. This is a case for weak references!
+
+So instead of `Rc<T>`, we’ll make the type of `parent` use `Weak<T>`,
+specifically a `RefCell<Weak<Node>>`. Now our `Node` struct definition looks
+like this:
+
+Filename: src/main.rs
+
+```
+use std::cell::RefCell;
+use std::rc::{Rc, Weak};
+
+#[derive(Debug)]
+struct Node {
+    value: i32,
+    parent: RefCell<Weak<Node>>,
+    children: RefCell<Vec<Rc<Node>>>,
+}
+```
+
+A node will be able to refer to its parent node but doesn’t own its parent.
+In Listing 15-28, we update `main` to use this new definition so the `leaf`
+node will have a way to refer to its parent, `branch`:
+
+Filename: src/main.rs
+
+```
+fn main() {
+    let leaf = Rc::new(Node {
+        value: 3,
+        [1] parent: RefCell::new(Weak::new()),
+        children: RefCell::new(vec![]),
+    });
+
+    [2] println!("leaf parent = {:?}", leaf.parent.borrow().upgrade());
+
+    let branch = Rc::new(Node {
+        value: 5,
+        [3] parent: RefCell::new(Weak::new()),
+        children: RefCell::new(vec![Rc::clone(&leaf)]),
+    });
+
+    [4] *leaf.parent.borrow_mut() = Rc::downgrade(&branch);
+
+    [5] println!("leaf parent = {:?}", leaf.parent.borrow().upgrade());
+}
+```
+
+Listing 15-28: A `leaf` node with a weak reference to its parent node `branch`
+
+Creating the `leaf` node looks similar to Listing 15-27 with the exception of
+the `parent` field: `leaf` starts out without a parent, so we create a new,
+empty `Weak<Node>` reference instance [1].
+
+At this point, when we try to get a reference to the parent of `leaf` by using
+the `upgrade` method, we get a `None` value. We see this in the output from the
+first `println!` statement [2]:
+
+```
+leaf parent = None
+```
+
+When we create the `branch` node, it will also have a new `Weak<Node>`
+reference in the `parent` field [3], because `branch` doesn’t have a parent
+node. We still have `leaf` as one of the children of `branch`. Once we have the
+`Node` instance in `branch`, we can modify `leaf` to give it a `Weak<Node>`
+reference to its parent [4]. We use the `borrow_mut` method on the
+`RefCell<Weak<Node>>` in the `parent` field of `leaf`, and then we use the
+`Rc::downgrade` function to create a `Weak<Node>` reference to `branch` from
+the `Rc<Node>` in `branch.`
+
+When we print the parent of `leaf` again [5], this time we’ll get a `Some`
+variant holding `branch`: now `leaf` can access its parent! When we print
+`leaf`, we also avoid the cycle that eventually ended in a stack overflow like
+we had in Listing 15-26; the `Weak<Node>` references are printed as `(Weak)`:
+
+```
+leaf parent = Some(Node { value: 5, parent: RefCell { value: (Weak) },
+children: RefCell { value: [Node { value: 3, parent: RefCell { value: (Weak) },
+children: RefCell { value: [] } }] } })
+```
+
+The lack of infinite output indicates that this code didn’t create a reference
+cycle. We can also tell this by looking at the values we get from calling
+`Rc::strong_count` and `Rc::weak_count`.
+
+#### Visualizing Changes to `strong_count` and `weak_count`
+
+Let’s look at how the `strong_count` and `weak_count` values of the `Rc<Node>`
+instances change by creating a new inner scope and moving the creation of
+`branch` into that scope. By doing so, we can see what happens when `branch` is
+created and then dropped when it goes out of scope. The modifications are shown
+in Listing 15-29:
+
+Filename: src/main.rs
+
+```
+fn main() {
+    let leaf = Rc::new(Node {
+        value: 3,
+        parent: RefCell::new(Weak::new()),
+        children: RefCell::new(vec![]),
+    });
+
+    [1] println!(
+        "leaf strong = {}, weak = {}",
+        Rc::strong_count(&leaf),
+        Rc::weak_count(&leaf),
+    );
+
+    [2] {
+        let branch = Rc::new(Node {
+            value: 5,
+            parent: RefCell::new(Weak::new()),
+            children: RefCell::new(vec![Rc::clone(&leaf)]),
+        });
+
+        *leaf.parent.borrow_mut() = Rc::downgrade(&branch);
+
+        [3] println!(
+            "branch strong = {}, weak = {}",
+            Rc::strong_count(&branch),
+            Rc::weak_count(&branch),
+        );
+
+        [4] println!(
+            "leaf strong = {}, weak = {}",
+            Rc::strong_count(&leaf),
+            Rc::weak_count(&leaf),
+        );
+    [5] }
+
+    [6] println!("leaf parent = {:?}", leaf.parent.borrow().upgrade());
+    [7] println!(
+        "leaf strong = {}, weak = {}",
+        Rc::strong_count(&leaf),
+        Rc::weak_count(&leaf),
+    );
+}
+```
+
+Listing 15-29: Creating `branch` in an inner scope and examining strong and
+weak reference counts
+
+After `leaf` is created, its `Rc<Node>` has a strong count of 1 and a weak
+count of 0 [1]. In the inner scope [2], we create `branch` and associate it
+with `leaf`, at which point when we print the counts [3], the `Rc<Node>` in
+`branch` will have a strong count of 1 and a weak count of 1 (for `leaf.parent`
+pointing to `branch` with a `Weak<Node>`). When we print the counts in `leaf`
+[4], we’ll see it will have a strong count of 2, because `branch` now has a
+clone of the `Rc<Node>` of `leaf` stored in `branch.children`, but will still
+have a weak count of 0.
+
+When the inner scope ends [5], `branch` goes out of scope and the strong count
+of the `Rc<Node>` decreases to 0, so its `Node` is dropped. The weak count of 1
+from `leaf.parent` has no bearing on whether or not `Node` is dropped, so we
+don’t get any memory leaks!
+
+If we try to access the parent of `leaf` after the end of the scope, we’ll get
+`None` again [6]. At the end of the program [7], the `Rc<Node>` in `leaf` has a
+strong count of 1 and a weak count of 0, because the variable `leaf` is now the
+only reference to the `Rc<Node>` again.
+
+All of the logic that manages the counts and value dropping is built into
+`Rc<T>` and `Weak<T>` and their implementations of the `Drop` trait. By
+specifying that the relationship from a child to its parent should be a
+`Weak<T>` reference in the definition of `Node`, you’re able to have parent
+nodes point to child nodes and vice versa without creating a reference cycle
+and memory leaks.
+
+## Summary
+
+This chapter covered how to use smart pointers to make different guarantees and
+trade-offs from those Rust makes by default with regular references. The
+`Box<T>` type has a known size and points to data allocated on the heap. The
+`Rc<T>` type keeps track of the number of references to data on the heap so
+that data can have multiple owners. The `RefCell<T>` type with its interior
+mutability gives us a type that we can use when we need an immutable type but
+need to change an inner value of that type; it also enforces the borrowing
+rules at runtime instead of at compile time.
+
+Also discussed were the `Deref` and `Drop` traits, which enable a lot of the
+functionality of smart pointers. We explored reference cycles that can cause
+memory leaks and how to prevent them using `Weak<T>`.
+
+If this chapter has piqued your interest and you want to implement your own
+smart pointers, check out “The Rustonomicon” at
+*https://doc.rust-lang.org/stable/nomicon/* for more useful information.
+
+Next, we’ll talk about concurrency in Rust. You’ll even learn about a few new
+smart pointers.