diff --git a/d.html.markdown b/d.html.markdown
index 9ebba385..ecb9e3ac 100644
--- a/d.html.markdown
+++ b/d.html.markdown
@@ -218,7 +218,7 @@ void main() {
// from 1 to 100. Easy!
// Just pass lambda expressions as template parameters!
- // You can pass any old function you like, but lambdas are convenient here.
+ // You can pass any function you like, but lambdas are convenient here.
auto num = iota(1, 101).filter!(x => x % 2 == 0)
.map!(y => y ^^ 2)
.reduce!((a, b) => a + b);
@@ -228,7 +228,7 @@ void main() {
```
Notice how we got to build a nice Haskellian pipeline to compute num?
-That's thanks to a D innovation know as Uniform Function Call Syntax.
+That's thanks to a D innovation know as Uniform Function Call Syntax (UFCS).
With UFCS, we can choose whether to write a function call as a method
or free function call! Walter wrote a nice article on this
[here.](http://www.drdobbs.com/cpp/uniform-function-call-syntax/232700394)
@@ -238,21 +238,23 @@ is of some type A on any expression of type A as a method.
I like parallelism. Anyone else like parallelism? Sure you do. Let's do some!
```c
+// Let's say we want to populate a large array with the square root of all
+// consecutive integers starting from 1 (up until the size of the array), and we
+// want to do this concurrently taking advantage of as many cores as we have
+// available.
+
import std.stdio;
import std.parallelism : parallel;
import std.math : sqrt;
void main() {
- // We want take the square root every number in our array,
- // and take advantage of as many cores as we have available.
+ // Create your large array
auto arr = new double[1_000_000];
- // Use an index, and an array element by reference,
- // and just call parallel on the array!
+ // Use an index, access every array element by reference (because we're
+ // going to change each element) and just call parallel on the array!
foreach(i, ref elem; parallel(arr)) {
ref = sqrt(i + 1.0);
}
}
-
-
```