pub use part05::BigInt;
-// With our new knowledge of lifetimes, we are now able to write down the desired type
-// of `min`: We want the function to take two borrows *of the same lifetime*, and then
-// return a borrow of that lifetime. If the two input lifetimes would be different, we
-// would not know which lifetime to use for the result.
+// With our new knowledge of lifetimes, we are now able to write down the desired type of `min`:
+//@ We want the function to take two borrows *of the same lifetime*, and then
+//@ return a borrow of that lifetime. If the two input lifetimes would be different, we
+//@ would not know which lifetime to use for the result.
pub trait Minimum {
fn min<'a>(&'a self, other: &'a Self) -> &'a Self;
}
-// Now we can implement a generic function `vec_min` that works on above trait.
-// The code is pretty much straight-forward, and Rust checks that all the
-// lifetimes actually work out.
+//@ Now we can implement a generic function `vec_min` that works on above trait.
+//@ The code is pretty much straight-forward, and Rust checks that all the
+//@ lifetimes actually work out. Observe that we don't have to make any copies!
pub fn vec_min<T: Minimum>(v: &Vec<T>) -> Option<&T> {
let mut min: Option<&T> = None;
for e in v {
- min = Some(match min {
- None => e,
- Some(n) => n.min(e)
- });
+ min = Some(match min { /*@*/
+ None => e, /*@*/
+ Some(n) => n.min(e) /*@*/
+ }); /*@*/
}
min
}
-// Notice that the return type `Option<&T>` is technically (leaving the borrowing story aside) a
-// pointer to a `T`, that could optionally be invalid. In other words, it's just like a pointer in
-// C(++) or Java that can be `NULL`! However, thanks to `Option` being an `enum`, we cannot forget
-// to check the pointer for validity, avoiding the safety issues of C(++).<br/>
-// Also, if you are worried about wasting space, notice that Rust knows that `&T` can never be
-// `NULL`, and hence optimizes `Option<&T>` to be no larger than `&T`. The `None` case is represented
-// as `NULL`. This is another great example of a zero-cost abstraction: `Option<&T>` is exactly like
-// a pointer in C(++), if you look at what happens during execution - but it's much safer to use.
-
-// For our `vec_min` to be usable with `BigInt`, we need to provide an implementation of
-// `Minimum`. You should be able to pretty much copy the code you wrote for exercise 06.1.
+//@ Notice that the return type `Option<&T>` is technically (leaving the borrowing story aside) a
+//@ pointer to a `T`, that could optionally be invalid. In other words, it's just like a pointer in
+//@ C(++) or Java that can be `NULL`! However, thanks to `Option` being an `enum`, we cannot forget
+//@ to check the pointer for validity, avoiding the safety issues of C(++). <br/>
+//@ Also, if you are worried about wasting space, notice that Rust knows that `&T` can never be
+//@ `NULL`, and hence optimizes `Option<&T>` to be no larger than `&T`. The `None` case is represented
+//@ as `NULL`. This is another great example of a zero-cost abstraction: `Option<&T>` is exactly like
+//@ a pointer in C(++), if you look at what happens during execution - but it's much safer to use.
+
+// **Exercise 07.1**: For our `vec_min` to be usable with `BigInt`, you will have to provide an implementation of
+// `Minimum`. You should be able to pretty much copy the code you wrote for exercise 06.1. You should *not*
+// make any copies of `BigInt`!
impl Minimum for BigInt {
fn min<'a>(&'a self, other: &'a Self) -> &'a Self {
unimplemented!()
}
// ## Operator Overloading
-// How can we know that our `min` function actually does what we want it to do? One possibility
-// here is to do *testing*. Rust comes with nice build-in support for both unit tests and integration
-// tests. However, before we go there, we need to have a way of checking whether the results of function calls are
-// correct. In other words, we need to define how to test equality of `BigInt`. Being able to
-// test equality is a property of a type, that - you guessed it - Rust expresses as a trait: `PartialEq`.
-
-// Doing this for `BigInt` is fairly easy, thanks to our requirement that there be no trailing zeros.
-// The `inline` attribute tells Rust that we will typically want this function to be inlined.
+//@ How can we know that our `min` function actually does what we want it to do? One possibility
+//@ here is to do *testing*. Rust comes with nice built-in support for both unit tests and integration
+//@ tests. However, before we go there, we need to have a way of checking whether the results of function calls are
+//@ correct. In other words, we need to define how to test equality of `BigInt`. Being able to
+//@ test equality is a property of a type, that - you guessed it - Rust expresses as a trait: `PartialEq`.
+
+//@ Doing this for `BigInt` is fairly easy, thanks to our requirement that there be no trailing zeros. We simply
+//@ re-use the equality test on vectors, which compares all the elements individually.
+//@ The `inline` attribute tells Rust that we will typically want this function to be inlined.
impl PartialEq for BigInt {
#[inline]
fn eq(&self, other: &BigInt) -> bool {
debug_assert!(self.test_invariant() && other.test_invariant());
- self.data == other.data
+ self.data == other.data /*@*/
}
}
-// Since implementing `PartialEq` is a fairly mechanical business, you can let Rust automate this
-// by adding the attribute `derive(PartialEq)` to the type definition. In case you wonder about
-// the "partial", I suggest you check out the documentation of [`PartialEq`](http://doc.rust-lang.org/std/cmp/trait.PartialEq.html)
-// and [`Eq`](http://doc.rust-lang.org/std/cmp/trait.Eq.html). `Eq` can be automatically derived as well.
-
-// Now we can compare `BigInt`s using `==`! Speaking in C++ terms, we just overloaded the `==` operator
-// for `BigInt`. Rust does not have function overloading (i.e., it will not dispatch to different
-// functions depending on the type of the argument). Instead, one typically finds (or defines) a
-// trait that catches the core characteristic common to all the overloads, and writes a single
-// function that's generic in the trait. For example, instead of overloading a function for all
-// the ways a string can be represented, one writes a generic functions over [ToString](http://doc.rust-lang.org/std/string/trait.ToString.html).
-// Usually, there is a trait like this that fits the purpose - and if there is, this has the great
-// advantage that any type *you* write, that can convert to a string, just has to implement
-// that trait to be immediately usable with all the functions out there that generalize over `ToString`.
-// Compare that to C++ or Java, where the only chance to add a new overloading variant is to
-// edit the class of the receiver.
+
+//@ Since implementing `PartialEq` is a fairly mechanical business, you can let Rust automate this
+//@ by adding the attribute `derive(PartialEq)` to the type definition. In case you wonder about
+//@ the "partial", I suggest you check out the documentation of [`PartialEq`](http://doc.rust-lang.org/std/cmp/trait.PartialEq.html)
+//@ and [`Eq`](http://doc.rust-lang.org/std/cmp/trait.Eq.html). `Eq` can be automatically derived as well.
+
+// Now we can compare `BigInt`s. Rust treats `PratialEq` special in that it is wired to the operator `==`:
+//@ That operator can not be used on our numbers! Speaking in C++ terms, we just overloaded the `==` operator
+//@ for `BigInt`. Rust does not have function overloading (i.e., it will not dispatch to different
+//@ functions depending on the type of the argument). Instead, one typically finds (or defines) a
+//@ trait that catches the core characteristic common to all the overloads, and writes a single
+//@ function that's generic in the trait. For example, instead of overloading a function for all
+//@ the ways a string can be represented, one writes a generic functions over [ToString](http://doc.rust-lang.org/std/string/trait.ToString.html).
+//@ Usually, there is a trait like this that fits the purpose - and if there is, this has the great
+//@ advantage that any type *you* write, that can convert to a string, just has to implement
+//@ that trait to be immediately usable with all the functions out there that generalize over `ToString`.
+//@ Compare that to C++ or Java, where the only chance to add a new overloading variant is to
+//@ edit the class of the receiver.
+//@
+//@ Why can we also use `!=`, even though we just overloaded `==`? The answer lies in what's called a *default implementation*.
+//@ If you check out the documentation of `PartialEq` I linked above, you will see that the trait actually provides
+//@ two methods: `eq` to test equality, and `ne` to test inequality. As you may have guessed, `!=` is wired to `ne`.
+//@ The trait *definition* also provides a default implementation of `ne` to be the negation of `eq`. Hence you can just
+//@ provide `eq`, and `!=` will work fine. Or, if you have a more efficient way of deciding inequality, you can provide
+//@ `ne` for your type yourself.
fn compare_big_ints() {
let b1 = BigInt::new(13);
let b2 = BigInt::new(37);
}
// ## Testing
-// With our equality test written, we are now ready to write our first testcase. It doesn't get much
-// simpler: You just write a function (with no arguments or return value), and give it the `test` attribute.
-// `assert!` is like `debug_assert!`, but does not get compiled away in a release build.
+// With our equality test written, we are now ready to write our first testcase.
+//@ It doesn't get much simpler: You just write a function (with no arguments or return value), and give it
+// the `test` attribute. `assert!` is like `debug_assert!`, but does not get compiled away in a release build.
#[test]
fn test_min() {
let b1 = BigInt::new(1);
let b2 = BigInt::new(42);
let b3 = BigInt::from_vec(vec![0, 1]);
- assert!(*b1.min(&b2) == b1);
- assert!(*b3.min(&b2) == b2);
+ assert!(*b1.min(&b2) == b1); /*@*/
+ assert!(*b3.min(&b2) == b2); /*@*/
}
// Now run `cargo test` to execute the test. If you implemented `min` correctly, it should all work!
// ## Formatting
-// There is also a macro `assert_eq!` that's specialized to test for equality, and that prints the two
-// values (left and right) if they differ. To be able to do that, the macro needs to know how to format
-// the value for printing. This means that we - guess what? - have to implement an appropriate trait.
-// Rust knows about two ways of formatting a value: `Display` is for pretty-printing something in a way
-// that users can understand, while `Debug` is meant to show the internal state of data and targeted at
-// the programmer. The latter is what we want for `assert_eq!`, so let's get started.
+//@ There is also a macro `assert_eq!` that's specialized to test for equality, and that prints the two
+//@ values (left and right) if they differ. To be able to do that, the macro needs to know how to format
+//@ the value for printing. This means that we - guess what? - have to implement an appropriate trait.
+//@ Rust knows about two ways of formatting a value: `Display` is for pretty-printing something in a way
+//@ that users can understand, while `Debug` is meant to show the internal state of data and targeted at
+//@ the programmer. The latter is what we want for `assert_eq!`, so let's get started.
// All formating is handled by [`std::fmt`](http://doc.rust-lang.org/std/fmt/index.html). I won't explain
// all the details, and refer you to the documentation instead.
use std::fmt;
-// In the case of `BigInt`, we'd like to just output our internal `data` array, so we
-// simply call the formating function of `Vec<u64>`.
+//@ In the case of `BigInt`, we'd like to just output our internal `data` array, so we
+//@ simply call the formating function of `Vec<u64>`.
impl fmt::Debug for BigInt {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
self.data.fmt(f)
}
}
-// `Debug` implementations can be automatically generated using the `derive(Debug)` attribute.
+//@ `Debug` implementations can be automatically generated using the `derive(Debug)` attribute.
// Now we are ready to use `assert_eq!` to test `vec_min`.
-#[test]
+/*#[test]*/
fn test_vec_min() {
let b1 = BigInt::new(1);
let b2 = BigInt::new(42);
let v1 = vec![b2.clone(), b1.clone(), b3.clone()];
let v2 = vec![b2.clone(), b3.clone()];
- assert_eq!(vec_min(&v1), Some(&b1));
- assert_eq!(vec_min(&v2), Some(&b2));
+ assert_eq!(vec_min(&v1), Some(&b1)); /*@*/
+ assert_eq!(vec_min(&v2), Some(&b2)); /*@*/
}
// **Exercise 07.1**: Add some more testcases. In particular, make sure you test the behavior of
// trailing zeros). Finally, break one of your functions in a subtle way and watch the test fail.
//
// **Exercise 07.2**: Go back to your good ol' `SomethingOrNothing`, and implement `Display` for it. (This will,
-// of course, need a `Display` bound on `T`.) Then you should be able to use them with `println!` just like you do with numbers.
+// of course, need a `Display` bound on `T`.) Then you should be able to use them with `println!` just like you do
+// with numbers, and get rid of the inherent functions to print `SomethingOrNothing<i32>` and `SomethingOrNothing<f32>`.
-// [index](main.html) | [previous](part06.html) | [next](main.html)
+//@ [index](main.html) | [previous](part06.html) | [next](part08.html)