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[canonicalization] fix result canonicalization example

This commit is contained in:
Alexey Shmalko 2019-04-20 23:00:13 +03:00
parent 52b2f710f8
commit 31c4046c5a
2 changed files with 6 additions and 6 deletions
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2
src/traits/canonical-queries.md
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@ -173,7 +173,7 @@ variables have unbound inference variables in their type: `?T`
represents the elements in the vector `t` and `?U` represents the represents the elements in the vector `t` and `?U` represents the
value stored in the option `u`. Next, we invoke `foo`; comparing the value stored in the option `u`. Next, we invoke `foo`; comparing the
signature of `foo` to its arguments, we wind up with `A = Vec<?T>` and signature of `foo` to its arguments, we wind up with `A = Vec<?T>` and
`B = ?U`.Therefore, the where clause on `foo` requires that `Vec<?T>: `B = ?U`. Therefore, the where clause on `foo` requires that `Vec<?T>:
Borrow<?U>`. This is thus our first example trait query. Borrow<?U>`. This is thus our first example trait query.
There are many possible solutions to the query `Vec<?T>: Borrow<?U>`; There are many possible solutions to the query `Vec<?T>: Borrow<?U>`;

10
src/traits/canonicalization.md
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@ -177,8 +177,8 @@ The result would be as follows:
```text ```text
Canonical(QR) = for<T, L> { Canonical(QR) = for<T, L> {
certainty: Proven, certainty: Proven,
var_values: [Vec<?0>, '?1, ?2] var_values: [Vec<?0>, '?1, ?0]
region_constraints: [?2: '?1], region_constraints: [?0: '?1],
value: (), value: (),
} }
``` ```
@ -213,8 +213,8 @@ and now we got back a canonical response:
```text ```text
for<T, L> { for<T, L> {
certainty: Proven, certainty: Proven,
var_values: [Vec<?0>, '?1, ?2] var_values: [Vec<?0>, '?1, ?0]
region_constraints: [?2: '?1], region_constraints: [?0: '?1],
value: (), value: (),
} }
``` ```
@ -250,7 +250,7 @@ for later verification.
than eagerly instantiating all of the canonical values in the result than eagerly instantiating all of the canonical values in the result
with variables, we instead walk the vector of values, looking for with variables, we instead walk the vector of values, looking for
cases where the value is just a canonical variable. In our example, cases where the value is just a canonical variable. In our example,
`values[2]` is `?C`, so that means we can deduce that `?C := ?B and `values[2]` is `?C`, so that means we can deduce that `?C := ?B` and
`'?D := 'static`. This gives us a partial set of values. Anything for `'?D := 'static`. This gives us a partial set of values. Anything for
which we do not find a value, we create an inference variable.) which we do not find a value, we create an inference variable.)