diff --git a/exercises/exercisesforhof/answers.ml b/exercises/exercisesforhof/answers.ml
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+
+(* 1. `filter_map` function: *)
+let filter_map f l =
+  List.fold_right
+    (fun x acc ->
+       match f x with
+       | Some y -> y :: acc
+       | None -> acc)
+    l []
+
+(* This function uses `fold_right` to iterate through the list `l` from right to left, and applies the function `f` to each element. If `f` returns a `Some` value, it is appended to the result list, otherwise it is skipped. *)
+
+(* 2. `compose` function: *)
+
+
+let compose f g x = f (g x)
+
+
+(* This function takes two functions `f` and `g`, and returns a new function that applies `g` to its argument, and then applies `f` to the result. *)
+
+(* 3. `exists` function: *)
+
+
+let exists p l =
+  List.fold_left
+    (fun acc x -> acc || p x)
+    false l
+
+
+(* This function uses `fold_left` to iterate through the list `l` from left to right, and applies the predicate function `p` to each element. If `p` returns `true` for any element, the function returns `true`, otherwise it returns `false`. *)
+
+(* 4. `iter2` function: *)
+
+
+let iter2 f l1 l2 =
+  List.iter2 f l1 l2
+
+
+(* This function uses the built-in `iter2` function from the `List` module, which iterates through two lists `l1` and `l2` in parallel, applying the function `f` to the corresponding elements of each list. *)
+
+(* 5. `flatten` function: *)
+
+
+let flatten l =
+  List.fold_left
+    (fun acc x -> acc @ x)
+    [] l
+
+
+(* This function uses `fold_left` to iterate through the list `l` from left to right, and appends each sub-list to the accumulator list. The resulting list is flattened, with all the elements of the sub-lists combined into a single list. Note that this implementation is not very efficient, as it performs many list concatenations, which can be slow for large lists. *)
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diff --git a/exercises/exercisesforhof/questions.md b/exercises/exercisesforhof/questions.md
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+Questions:
+These are a few questions that you can solve using higher-order functions in OCaml:
+
+1. Write a function `filter_map` that takes a list `l` and a function `f` that returns an optional value, and returns a new list containing only the non-`None` values returned by `f`.
+
+2. Write a function `compose` that takes two functions `f` and `g` and returns a new function that applies `f` to the result of applying `g` to its argument.
+
+3. Write a function `exists` that takes a list `l` and a predicate function `p`, and returns `true` if there exists an element in `l` for which `p` returns `true`, and `false` otherwise.
+
+4. Write a function `iter2` that takes two lists `l1` and `l2` and a function `f`, and applies `f` to the corresponding elements of `l1` and `l2`. The function `f` takes two arguments, one from `l1` and one from `l2`.
+
+5. Write a function `flatten` that takes a list of lists `l` and returns a flattened list containing all the elements of the sub-lists.
diff --git a/tutorials/basic-highorderfunctions.md b/tutorials/basic-highorderfunctions.md
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+                                            Higher-order functions
+
+-----------------------------------------------------------------------------------------------------------------------------------------
+
+Higher-order functions are functions that take other functions as arguments or return functions as their results. Here is an example of a higher-order function that takes a function `f` and applies it to each element of a list `l`:
+
+
+let rec map f l =
+  match l with
+  | [] -> []
+  | x :: xs -> f x :: map f xs
+
+
+The `map` function takes a function `f` as its first argument and a list `l` as its second argument. It applies `f` to each element of `l` and returns a new list containing the results. For example, if we define a function `square` that squares its argument:
+
+
+let square x = x * x
+
+
+We can use `map` to apply `square` to each element of a list:
+
+
+let l = [1; 2; 3]
+let l_squared = map square l  (* returns [1; 4; 9] *)
+
+-----------------------------------------------------------------------------------------------------------------------------------------
+
+Another example of a higher-order function in OCaml is the `fold_left` function, which takes a function `f`, an initial accumulator value `acc`, and a list `l`, and applies `f` to each element of `l` and the current accumulator value to produce a new accumulator value. Here's an example implementation of `fold_left`:
+
+
+let rec fold_left f acc l =
+  match l with
+  | [] -> acc
+  | x :: xs -> fold_left f (f acc x) xs
+
+
+We can use `fold_left` to compute the sum of a list of integers:
+
+
+let sum l = fold_left (+) 0 l
+
+
+The `sum` function takes a list `l` as its argument and uses `fold_left` with the `+` operator and an initial accumulator value of `0` to compute the sum of `l`. For example:
+
+
+let l = [1; 2; 3]
+let sum_l = sum l  (* returns 6 *)
+
+------------------------------------------------------------------------------------------------------------------------------------------
+
+`fold_right` is a higher-order function in OCaml that is similar to `fold_left`, but it processes the elements of a list from right to left instead of from left to right.
+
+Here's the signature of `fold_right`:
+
+
+val fold_right : ('a -> 'b -> 'b) -> 'a list -> 'b -> 'b
+
+
+The first argument is a function `f` that takes an element of the list and an accumulator value and returns a new accumulator value. The second argument is the list to be processed, and the third argument is the initial accumulator value.
+
+Here's an example implementation of `fold_right`:
+
+
+let rec fold_right f l acc =
+  match l with
+  | [] -> acc
+  | x :: xs -> f x (fold_right f xs acc)
+
+
+The implementation is similar to `fold_left`, except that it calls itself recursively on the tail of the list (`xs`) and passes the current accumulator value (`acc`) as the second argument to `f`.
+
+Here's an example of using `fold_right` to compute the product of a list of integers:
+
+
+let product l = fold_right (fun x acc -> x * acc) l 1
+
+
+The `product` function takes a list `l` as its argument and uses `fold_right` with a function that multiplies the current element by the accumulator and an initial accumulator value of `1` to compute the product of `l`. For example:
+
+
+let l = [1; 2; 3]
+let product_l = product l  (* returns 6 *)
+
+
+Note: `fold_right` is often less efficient than `fold_left` because it processes the list in reverse order. This leads to an excessive stack usage for large lists.
+
+_____________________________________________________________________________________________________________________________________________
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