Finished editing "Functional Programming"

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Functional Programming/Building Maps/Exercise 1/task.md

@@ -2,4 +2,4 @@
 
 Implement a function named `demographic(people: List<Person>)` returning a
 `Map` where the key is age and the value is a list of names of people of that
-age.
+age.

Functional Programming/Building Maps/Exercise 2/task.md

@@ -1,3 +1,3 @@
 ## Building Maps (#2)
 
-Implement `groupBy()` using `getOrPut()`.
+Implement `groupBy()` using `getOrPut()`.

Functional Programming/Building Maps/Exercise 3/task.md

@@ -2,4 +2,4 @@
 
 Implement `associateBy(keySelector: (T) -> R)` using `groupBy()`. If two
 elements have the same key produced by `keySelector` then the last one should
-be added to the `Map`.
+be added to the `Map`.

Functional Programming/Folding Lists/Exercise 1/task.md

@@ -1,4 +1,4 @@
 ## Folding Lists (#1)
 
 Use `fold()` to finish the implementation of `size()` given in the starter
-code. `size()` returns the number of elements in a `List`.
+code. `size()` returns the number of elements in a `List`.

Functional Programming/Folding Lists/Exercise 2/task.md

@@ -1,3 +1,3 @@
 ## Folding Lists (#2)
 
-Finish implementing `count()`, given in the starter code, using `fold()`.
+Finish implementing `count()`, given in the starter code, using `fold()`.

Functional Programming/Folding Lists/Exercise 3/task.md

@@ -1,3 +1,3 @@
 ## Folding Lists (#3)
 
-Implement `any()` using `fold()`.
+Implement `any()` using `fold()`.

Functional Programming/Folding Lists/Exercise 4/task.md

@@ -3,5 +3,5 @@
 The starter code provides a `Condition` class and a function
 `Condition.combine()` that combines two conditions. There's also a skeleton
 for the `List<Condition>` extension function `combineAll()` that combines all
-the conditions in the `List`. Complete the implementation using `reduce()`,
-assuming the `List` is non-empty.
+conditions in the `List`. Complete the implementation using `reduce()`,
+assuming the `List` is non-empty.

Functional Programming/Higher-Order Functions/Exercise 1/task.md

@@ -1,3 +1,3 @@
 ## Higher-Order Functions (#1)
 
-Implement the `List<T>.map()` function from scratch.
+Implement the `List<T>.map()` function from scratch.

Functional Programming/Higher-Order Functions/Exercise 2/task.md

@@ -5,4 +5,4 @@ Rewrite the following function using a single call to `mapNotNull()`:
 ```kotlin
 fun List<Int>.transform(): List<Int> =
   filter { it % 2 == 0 }.map { it * it }
-```
+```

Functional Programming/Higher-Order Functions/Exercise 3/task.md

@@ -8,4 +8,4 @@ Note the generic types `R?` (in `(Int, T) -> R?`) and `List<R>`. The `?` in
 `R?` means the lambda's return type is nullable. `mapIndexedNotNull()` returns
 a list of non-nullable elements, so the function return type is `List<R>`. To
 express that `R` is a non-nullable type, we specify a *constraint* on the
-generic type parameter: `R: Any`.
+generic type parameter: `R: Any`.

Functional Programming/Higher-Order Functions/Exercise 4/task.md

@@ -3,4 +3,4 @@
 Implement `andThen()` to combine the actions of two functions. `f.andThen(g)`
 returns a new function that first applies `f` and then applies `g` to the
 result: `{arg -> g(f(arg))}`. Define `andThen()` as an extension function on a
-function type.
+function type.