## 1. Abridged Problem Statement

Given `N` and two different permutations `S1`, `S2` of the first `N` uppercase letters, output a shortest string that:

- contains both `S1` and `S2` as substrings;
- is **hyper almost permutative**: every substring of length `N + 1` can become a permutation of the first `N` uppercase letters after deleting exactly one character.

If multiple shortest answers exist, output any one.

Constraints: `2 <= N <= 26`.

---

## 2. Detailed Editorial

### Key observation: valid strings can be seen as paths between permutations

A length-`N` substring that is a permutation of the first `N` letters will be called a **stable window**.

Suppose the current suffix of the answer is a stable window

```text
W = w1 w2 ... wn
```

We want to append characters while keeping every length-`N+1` window almost permutative, until the suffix of length `N` again becomes a permutation.

If we append `wp`, then the length-`N+1` window has one duplicate letter `wp`, so it is almost permutative. After that, the next forced appended letters are:

```text
w1, w2, ..., w(p-1)
```

After appending these `p` characters total, the new stable window becomes:

```text
w(p+1) ... wn wp w1 ... w(p-1)
```

So one transition is determined by a split point `p`, costs `p` appended characters, and transforms the current permutation window.

Example:

```text
W = ABC, p = 2
append B A
new stable window = CBA
```

---

### Virtual zero model

Introduce a virtual symbol `0` before the current permutation:

```text
0 w1 w2 ... wn
```

Positions are considered on a cycle of length `N + 1`.

The transition with split `p` is equivalent to moving/swapping the virtual `0` with the element at distance `p` clockwise. The cost of the move is exactly that clockwise distance.

Therefore, the problem becomes:

> Transform the cyclic arrangement corresponding to `S1` into one corresponding to `S2`, using swaps with `0`, minimizing the total clockwise distance.

Because `S2` may appear with the virtual zero inserted at any place around it, we try all cyclic rotations of:

```text
0 + S2
```

Also, the final answer may start with `S1` and reach `S2`, or start with `S2` and reach `S1`, so both directions are tried.

---

### Permutation cycles

For a fixed initial arrangement `a` and target arrangement `b`, define:

```cpp
perm[i] = target position of value currently at position i
```

This is a permutation of positions `0..N`.

We decompose `perm` into cycles.

---

### Cycle containing zero

Suppose the cycle containing `0` is:

```text
0 -> p1 -> p2 -> ... -> pt -> 0
```

To fix this cycle using swaps with zero, we walk through it in reverse order:

```text
0, pt, p(t-1), ..., p1
```

Each step costs the clockwise distance between consecutive positions.

After this, zero ends at `perm[0]`.

---

### Cycles not containing zero

Let `z = perm[0]` be where zero currently sits after fixing the zero-cycle.

For a non-zero cycle:

```text
c0 -> c1 -> ... -> c(k-1) -> c0
```

zero must enter the cycle, traverse it in reverse order, then return to `z`.

For some starting index `s`, the walk is:

```text
z -> cs -> c(s-1) -> ... -> c(s+1) -> z
```

The algorithm chooses `s` so that this walk has minimum possible cost. Geometrically, this can be achieved by choosing an edge of the cycle whose clockwise arc does not contain `z`.

The implementation scans all edges and selects such a start.

---

### Reconstructing the answer

After finding the cheapest sequence of moves:

1. Output the starting permutation.
2. For every move of distance `p`, append the `p` forced characters:

```text
a[p], a[1], ..., a[p-1]
```

3. Update the current stable window.

The produced string is shortest because the chosen path has minimum total appended length.

Complexity is tiny:

```text
O(N^2)
```

with `N <= 26`.

---

## 3. Provided C++ Solution with Detailed Comments

```cpp
#include <bits/stdc++.h> // Includes almost all standard C++ headers.

using namespace std; // Avoid writing std:: before standard library names.

// Output operator for pairs. Not actually needed by this solution,
// but included in the original template.
template<typename T1, typename T2>
ostream& operator<<(ostream& out, const pair<T1, T2>& x) {
    return out << x.first << ' ' << x.second;
}

// Input operator for pairs. Also part of the author's template.
template<typename T1, typename T2>
istream& operator>>(istream& in, pair<T1, T2>& x) {
    return in >> x.first >> x.second;
}

// Input operator for vectors. Reads every element of the vector.
template<typename T>
istream& operator>>(istream& in, vector<T>& a) {
    for(auto& x: a) {
        in >> x;
    }
    return in;
};

// Output operator for vectors. Prints elements separated by spaces.
template<typename T>
ostream& operator<<(ostream& out, const vector<T>& a) {
    for(auto x: a) {
        out << x << ' ';
    }
    return out;
};

// Number of letters.
int n;

// Input permutations.
string s1, s2;

// Arrays representing cyclic arrangements.
// Position 0 stores the virtual symbol 0.
// Positions 1..n store actual letters encoded as 1..n.
array<int, 27> a{}, b{};

// The sequence of move lengths chosen by compute_cost().
vector<int> move_costs;

// Reads input.
void read() {
    cin >> n >> s1 >> s2;
}

// Records one move from position `from` to position `to` on a cycle
// of length n + 1, and returns its clockwise distance.
int push_step(int from, int to) {
    // Clockwise modular distance from `from` to `to`.
    int d = (to - from + n + 1) % (n + 1);

    // Save this move for later reconstruction.
    move_costs.push_back(d);

    // Return its cost.
    return d;
}

// Computes the minimum cost to transform current cyclic arrangement `a`
// into target cyclic arrangement `b`.
int compute_cost() {
    // Clear previously recorded moves.
    move_costs.clear();

    // Total cost of all moves.
    int total = 0;

    // pos_in_b[value] = position where this value must be in target b.
    array<int, 27> pos_in_b{}, perm{};

    // Build inverse map of b.
    for(int i = 0; i <= n; i++) {
        pos_in_b[b[i]] = i;
    }

    // perm[i] tells where the value currently at position i in a
    // must go in b.
    for(int i = 0; i <= n; i++) {
        perm[i] = pos_in_b[a[i]];
    }

    // Marks visited positions while decomposing perm into cycles.
    array<bool, 27> visited{};

    // Process every cycle of the permutation perm.
    for(int i = 0; i <= n; i++) {
        // Already processed this position.
        if(visited[i]) {
            continue;
        }

        // Mark current position visited.
        visited[i] = true;

        // Fixed point: value is already in the right position.
        if(perm[i] == i) {
            continue;
        }

        // Collect the current cycle.
        vector<int> cycle = {i};

        // Follow perm until returning to i.
        for(int x = perm[i]; x != i; x = perm[x]) {
            cycle.push_back(x);
            visited[x] = true;
        }

        // Length of this cycle.
        int cnt = (int)cycle.size();

        // Case 1: the cycle contains zero.
        // Since cycles are discovered starting from smallest unvisited i,
        // this happens exactly when i == 0.
        if(i == 0) {
            // We need to walk through the cycle in reverse order,
            // keeping 0 as the first element.
            reverse(cycle.begin() + 1, cycle.end());

            // Add moves along that reversed walk.
            for(int j = 1; j < cnt; j++) {
                total += push_step(cycle[j - 1], cycle[j]);
            }
        } else {
            // Case 2: a cycle not containing zero.
            // zero currently sits at position perm[0].
            int start = 0;

            // Choose the best place to enter this cycle.
            for(int j = 0; j < cnt; j++) {
                int x = cycle[j];
                int y = cycle[(j + 1) % cnt];

                // We want zero not to lie on the open clockwise arc x -> y.
                // If x < y, the arc is non-wrapping: (x, y).
                bool zero_outside = x < y && (perm[0] < x || perm[0] > y);

                // If x > y, the arc wraps around through 0.
                // Then zero is outside the arc exactly when y < zero < x.
                bool zero_inside_wrap = y < perm[0] && perm[0] < x;

                // This edge is suitable.
                if(zero_outside || zero_inside_wrap) {
                    start = j;
                }
            }

            // Rotate the cycle so that the chosen starting vertex is first.
            rotate(cycle.begin(), cycle.begin() + start, cycle.end());

            // Walk the rest of the cycle in reverse order.
            reverse(cycle.begin() + 1, cycle.end());

            // Enter the cycle from zero's current position.
            total += push_step(perm[0], cycle[0]);

            // Traverse the cycle.
            for(int j = 1; j < cnt; j++) {
                total += push_step(cycle[j - 1], cycle[j]);
            }

            // Return to zero's position.
            total += push_step(cycle.back(), perm[0]);
        }
    }

    // Return total movement cost.
    return total;
}

// Applies one real move of length p to the current stable window a[1..n].
// This corresponds to appending:
// a[p], a[1], ..., a[p-1]
void apply_move(int p) {
    // Temporary array for the next stable window.
    array<int, 27> next_a{};

    // Elements after p shift to the front.
    for(int i = p + 1; i <= n; i++) {
        next_a[i - p] = a[i];
    }

    // Element at p comes next.
    next_a[n - p + 1] = a[p];

    // Elements before p follow.
    for(int i = 1; i < p; i++) {
        next_a[n - p + 1 + i] = a[i];
    }

    // Copy the new stable window back into a.
    for(int i = 1; i <= n; i++) {
        a[i] = next_a[i];
    }
}

// Main solving function.
void solve() {
    // Initialize virtual cyclic arrangements.
    // 0 is the virtual separator.
    a[0] = b[0] = 0;

    // Encode S1 into a[1..n].
    // 'A' becomes 1, 'B' becomes 2, etc.
    for(int i = 0; i < n; i++) {
        a[i + 1] = s1[i] - 'A' + 1;
        b[i + 1] = s2[i] - 'A' + 1;
    }

    // Best direction:
    // 0 means output starts with S1 and reaches S2.
    // 1 means output starts with S2 and reaches S1.
    int best_dir = 0;

    // Best cyclic rotation of the target arrangement.
    int best_rot = 0;

    // Best total appended length found so far.
    int best_cost = INT_MAX;

    // Try both directions.
    for(int dir = 0; dir < 2; dir++) {
        // Try every possible position of the virtual zero in the target.
        for(int r = 0; r <= n; r++) {
            // Compute cost for current a and current rotation of b.
            int c = compute_cost();

            // Save the best option.
            if(c < best_cost) {
                best_cost = c;
                best_dir = dir;
                best_rot = r;
            }

            // Rotate target cyclic arrangement by one position.
            rotate(b.begin(), b.begin() + 1, b.begin() + n + 1);
        }

        // Swap start and target to try the opposite direction.
        swap(a, b);
    }

    // After the loop, a and b are back to original orientation.
    // If the best answer starts from S2, swap them.
    if(best_dir == 1) {
        swap(a, b);
    }

    // Apply the best rotation to the target.
    rotate(b.begin(), b.begin() + best_rot, b.begin() + n + 1);

    // Recompute cost to restore the corresponding move list.
    compute_cost();

    // The answer starts with the chosen starting permutation.
    string result;

    // Append current stable window to result.
    for(int i = 1; i <= n; i++) {
        result += (char)('A' + a[i] - 1);
    }

    // Replay every move and append the forced characters.
    for(int p: move_costs) {
        // Distance 0 means no actual character is appended.
        if(p == 0) {
            continue;
        }

        // First append a[p].
        result += (char)('A' + a[p] - 1);

        // Then append a[1], ..., a[p-1].
        for(int i = 1; i < p; i++) {
            result += (char)('A' + a[i] - 1);
        }

        // Update current stable window.
        apply_move(p);
    }

    // Print any shortest valid answer.
    cout << result << '\n';
}

// Program entry point.
int main() {
    // Fast input/output.
    ios_base::sync_with_stdio(false);
    cin.tie(nullptr);

    // Only one test case.
    int T = 1;

    // The original template supports multiple tests, but this problem has one.
    // cin >> T;

    // Solve all test cases.
    for(int test = 1; test <= T; test++) {
        read();
        solve();
    }

    return 0;
}
```

---

## 4. Python Solution with Detailed Comments

```python
import sys


def clockwise_distance(frm, to, n):
    """
    Clockwise distance from position frm to position to
    on a cycle of length n + 1.
    """
    return (to - frm + n + 1) % (n + 1)


def compute_cost(a, b, n):
    """
    Compute the minimum cost to transform cyclic arrangement a into b.

    a and b are lists of length n + 1.
    Position 0 is the virtual zero.
    Positions 1..n are letters encoded as integers 1..n.

    Returns:
        total_cost, moves
    where moves is the sequence of clockwise distances.
    """

    # Recorded move lengths.
    moves = []

    # Total cost.
    total = 0

    # pos_in_b[value] = position of value in target arrangement b.
    pos_in_b = [0] * (n + 1)

    for i in range(n + 1):
        pos_in_b[b[i]] = i

    # perm[i] = where the value currently at position i must go.
    perm = [0] * (n + 1)

    for i in range(n + 1):
        perm[i] = pos_in_b[a[i]]

    # Helper to add one move.
    def push_step(frm, to):
        nonlocal total

        # Compute clockwise distance.
        d = clockwise_distance(frm, to, n)

        # Store this move for reconstruction.
        moves.append(d)

        # Add to total cost.
        total += d

    # Used for cycle decomposition.
    visited = [False] * (n + 1)

    # Process all cycles of perm.
    for i in range(n + 1):
        if visited[i]:
            continue

        visited[i] = True

        # Fixed point, no operation needed.
        if perm[i] == i:
            continue

        # Build current cycle.
        cycle = [i]
        x = perm[i]

        while x != i:
            cycle.append(x)
            visited[x] = True
            x = perm[x]

        cnt = len(cycle)

        # Cycle containing zero.
        if i == 0:
            # Walk through the cycle in reverse order, keeping zero first.
            cycle = [cycle[0]] + list(reversed(cycle[1:]))

            # Add consecutive moves.
            for j in range(1, cnt):
                push_step(cycle[j - 1], cycle[j])

        else:
            # Non-zero cycle.
            # After the zero-cycle is fixed, zero sits at perm[0].
            z = perm[0]

            # Choose a good entry point into this cycle.
            start = 0

            for j in range(cnt):
                x = cycle[j]
                y = cycle[(j + 1) % cnt]

                # If x < y, arc x -> y does not wrap.
                # We need z outside the open arc.
                zero_outside = x < y and (z < x or z > y)

                # If x > y, arc x -> y wraps around.
                # Then z is outside iff y < z < x.
                zero_inside_wrap = y < z < x

                if zero_outside or zero_inside_wrap:
                    start = j

            # Rotate cycle so chosen start is first.
            cycle = cycle[start:] + cycle[:start]

            # Walk the rest in reverse order.
            cycle = [cycle[0]] + list(reversed(cycle[1:]))

            # Enter the cycle from z.
            push_step(z, cycle[0])

            # Traverse the cycle.
            for j in range(1, cnt):
                push_step(cycle[j - 1], cycle[j])

            # Return to z.
            push_step(cycle[-1], z)

    return total, moves


def apply_move(a, p, n):
    """
    Apply one real move of length p to current stable window a[1..n].

    This corresponds to appending:
        a[p], a[1], ..., a[p-1]

    The new stable window becomes:
        a[p+1], ..., a[n], a[p], a[1], ..., a[p-1]
    """

    # Temporary array.
    nxt = [0] * (n + 1)

    # Elements after p move to the front.
    for i in range(p + 1, n + 1):
        nxt[i - p] = a[i]

    # Element p follows.
    nxt[n - p + 1] = a[p]

    # Elements before p follow.
    for i in range(1, p):
        nxt[n - p + 1 + i] = a[i]

    # Keep virtual zero at position 0.
    nxt[0] = 0

    return nxt


def solve():
    data = sys.stdin.read().strip().split()

    n = int(data[0])
    s1 = data[1]
    s2 = data[2]

    # Encode S1 and S2.
    # 0 is the virtual separator.
    a = [0] + [ord(ch) - ord('A') + 1 for ch in s1]
    b = [0] + [ord(ch) - ord('A') + 1 for ch in s2]

    best_cost = 10**9
    best_dir = 0
    best_rot = 0

    # Try both directions:
    # dir = 0: start with S1, reach S2.
    # dir = 1: start with S2, reach S1.
    for direction in range(2):
        # Try all cyclic rotations of target.
        for r in range(n + 1):
            cost, _ = compute_cost(a, b, n)

            if cost < best_cost:
                best_cost = cost
                best_dir = direction
                best_rot = r

            # Rotate b left by one.
            b = b[1:] + b[:1]

        # Swap start and target.
        a, b = b, a

    # After two swaps, a and b are back to original.
    # If best direction starts from S2, swap once more.
    if best_dir == 1:
        a, b = b, a

    # Apply best target rotation.
    b = b[best_rot:] + b[:best_rot]

    # Recompute moves for the chosen optimal configuration.
    _, moves = compute_cost(a, b, n)

    # Build output starting from the chosen initial permutation.
    result = []

    for i in range(1, n + 1):
        result.append(chr(ord('A') + a[i] - 1))

    # Replay all moves.
    for p in moves:
        # No characters appended for zero-distance moves.
        if p == 0:
            continue

        # Append a[p].
        result.append(chr(ord('A') + a[p] - 1))

        # Append a[1], ..., a[p-1].
        for i in range(1, p):
            result.append(chr(ord('A') + a[i] - 1))

        # Update current stable window.
        a = apply_move(a, p, n)

    print(''.join(result))


if __name__ == "__main__":
    solve()
```

---

## 5. Compressed Editorial

Represent a current permutative substring `w1...wn` as a cycle:

```text
0 w1 w2 ... wn
```

where `0` is virtual. A valid extension from one permutation window to the next is determined by choosing a distance `p`: append

```text
wp w1 ... w(p-1)
```

and the new window becomes

```text
w(p+1) ... wn wp w1 ... w(p-1)
```

This is equivalent to moving/swapping `0` clockwise by distance `p`, with cost `p`.

Thus, minimize the cost to transform the cyclic permutation for `S1` into one for `S2`. Since the virtual zero may be placed anywhere relative to `S2`, try all `N+1` rotations of `0 + S2`. Also try both directions: `S1 -> S2` and `S2 -> S1`.

For a fixed start/target, define:

```text
perm[i] = target position of value currently at i
```

Decompose `perm` into cycles.

- For the cycle containing zero, walk it in reverse order.
- For every other cycle, let `z = perm[0]`; enter the cycle from `z`, traverse it in reverse order, and return to `z`. Choose the entry edge so that `z` is not on the open clockwise arc of that edge, giving minimum cost.

Record the move distances, choose the globally best rotation/direction, then replay the moves to construct the answer.

Complexity: `O(N^2)`, with `N <= 26`.