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Calculate the number of pairs (P, S) such that {A[0], ..., A[P]} = {A[S], ..., A[N-1]}.

Programming language:
Spoken language:

A non-empty zero-indexed array A consisting of N integers is given. A *prefix suffix set* is a pair of indices (P, S) such that 0 ≤ P, S < N and such that:

- every value that occurs in the sequence A[0], A[1], ..., A[P] also occurs in the sequence A[S], A[S + 1], ..., A[N − 1],
- every value that occurs in the sequence A[S], A[S + 1], ..., A[N − 1] also occurs in the sequence A[0], A[1], ..., A[P].

The goal is to calculate the number of prefix suffix sets in the array.

For example, consider array A such that:

There are exactly fourteen prefix suffix sets: (1, 4), (1, 3), (2, 2), (2, 1), (2, 0), (3, 2), (3, 1), (3, 0), (4, 2), (4, 1), (4, 0), (5, 2), (5, 1), (5, 0).

Write a function:

int solution(int A[], int N);

that, given a non-empty zero-indexed array A of N integers, returns the number of prefix suffix sets.

If the number of prefix suffix sets is greater than 1,000,000,000, the function should return 1,000,000,000.

For example, given:

the function should return 14, as explained above.

Assume that:

- N is an integer within the range [1..40,000];
- each element of array A is an integer within the range [−1,000,000,000..1,000,000,000].

Complexity:

- expected worst-case time complexity is O(N*log(N));
- expected worst-case space complexity is O(N), beyond input storage (not counting the storage required for input arguments).

Copyright 2009–2018 by Codility Limited. All Rights Reserved. Unauthorized copying, publication or disclosure prohibited.

A non-empty zero-indexed array A consisting of N integers is given. A *prefix suffix set* is a pair of indices (P, S) such that 0 ≤ P, S < N and such that:

- every value that occurs in the sequence A[0], A[1], ..., A[P] also occurs in the sequence A[S], A[S + 1], ..., A[N − 1],
- every value that occurs in the sequence A[S], A[S + 1], ..., A[N − 1] also occurs in the sequence A[0], A[1], ..., A[P].

The goal is to calculate the number of prefix suffix sets in the array.

For example, consider array A such that:

There are exactly fourteen prefix suffix sets: (1, 4), (1, 3), (2, 2), (2, 1), (2, 0), (3, 2), (3, 1), (3, 0), (4, 2), (4, 1), (4, 0), (5, 2), (5, 1), (5, 0).

Write a function:

int solution(vector<int> &A);

that, given a non-empty zero-indexed array A of N integers, returns the number of prefix suffix sets.

If the number of prefix suffix sets is greater than 1,000,000,000, the function should return 1,000,000,000.

For example, given:

the function should return 14, as explained above.

Assume that:

- N is an integer within the range [1..40,000];
- each element of array A is an integer within the range [−1,000,000,000..1,000,000,000].

Complexity:

- expected worst-case time complexity is O(N*log(N));
- expected worst-case space complexity is O(N), beyond input storage (not counting the storage required for input arguments).

Copyright 2009–2018 by Codility Limited. All Rights Reserved. Unauthorized copying, publication or disclosure prohibited.

A non-empty zero-indexed array A consisting of N integers is given. A *prefix suffix set* is a pair of indices (P, S) such that 0 ≤ P, S < N and such that:

- every value that occurs in the sequence A[0], A[1], ..., A[P] also occurs in the sequence A[S], A[S + 1], ..., A[N − 1],
- every value that occurs in the sequence A[S], A[S + 1], ..., A[N − 1] also occurs in the sequence A[0], A[1], ..., A[P].

The goal is to calculate the number of prefix suffix sets in the array.

For example, consider array A such that:

There are exactly fourteen prefix suffix sets: (1, 4), (1, 3), (2, 2), (2, 1), (2, 0), (3, 2), (3, 1), (3, 0), (4, 2), (4, 1), (4, 0), (5, 2), (5, 1), (5, 0).

Write a function:

class Solution { public int solution(int[] A); }

that, given a non-empty zero-indexed array A of N integers, returns the number of prefix suffix sets.

If the number of prefix suffix sets is greater than 1,000,000,000, the function should return 1,000,000,000.

For example, given:

the function should return 14, as explained above.

Assume that:

- N is an integer within the range [1..40,000];
- each element of array A is an integer within the range [−1,000,000,000..1,000,000,000].

Complexity:

- expected worst-case time complexity is O(N*log(N));
- expected worst-case space complexity is O(N), beyond input storage (not counting the storage required for input arguments).

Copyright 2009–2018 by Codility Limited. All Rights Reserved. Unauthorized copying, publication or disclosure prohibited.

*prefix suffix set* is a pair of indices (P, S) such that 0 ≤ P, S < N and such that:

The goal is to calculate the number of prefix suffix sets in the array.

For example, consider array A such that:

Write a function:

func Solution(A []int) int

For example, given:

the function should return 14, as explained above.

Assume that:

- N is an integer within the range [1..40,000];
- each element of array A is an integer within the range [−1,000,000,000..1,000,000,000].

Complexity:

- expected worst-case time complexity is O(N*log(N));

*prefix suffix set* is a pair of indices (P, S) such that 0 ≤ P, S < N and such that:

The goal is to calculate the number of prefix suffix sets in the array.

For example, consider array A such that:

Write a function:

class Solution { public int solution(int[] A); }

For example, given:

the function should return 14, as explained above.

Assume that:

- N is an integer within the range [1..40,000];
- each element of array A is an integer within the range [−1,000,000,000..1,000,000,000].

Complexity:

- expected worst-case time complexity is O(N*log(N));

*prefix suffix set* is a pair of indices (P, S) such that 0 ≤ P, S < N and such that:

The goal is to calculate the number of prefix suffix sets in the array.

For example, consider array A such that:

Write a function:

function solution(A);

For example, given:

the function should return 14, as explained above.

Assume that:

- N is an integer within the range [1..40,000];
- each element of array A is an integer within the range [−1,000,000,000..1,000,000,000].

Complexity:

- expected worst-case time complexity is O(N*log(N));

*prefix suffix set* is a pair of indices (P, S) such that 0 ≤ P, S < N and such that:

The goal is to calculate the number of prefix suffix sets in the array.

For example, consider array A such that:

Write a function:

function solution(A)

For example, given:

the function should return 14, as explained above.

Assume that:

- N is an integer within the range [1..40,000];
- each element of array A is an integer within the range [−1,000,000,000..1,000,000,000].

Complexity:

- expected worst-case time complexity is O(N*log(N));

*prefix suffix set* is a pair of indices (P, S) such that 0 ≤ P, S < N and such that:

The goal is to calculate the number of prefix suffix sets in the array.

For example, consider array A such that:

Write a function:

int solution(NSMutableArray *A);

For example, given:

the function should return 14, as explained above.

Assume that:

- N is an integer within the range [1..40,000];
- each element of array A is an integer within the range [−1,000,000,000..1,000,000,000].

Complexity:

- expected worst-case time complexity is O(N*log(N));

*prefix suffix set* is a pair of indices (P, S) such that 0 ≤ P, S < N and such that:

The goal is to calculate the number of prefix suffix sets in the array.

For example, consider array A such that:

Write a function:

function solution(A: array of longint; N: longint): longint;

For example, given:

the function should return 14, as explained above.

Assume that:

- N is an integer within the range [1..40,000];
- each element of array A is an integer within the range [−1,000,000,000..1,000,000,000].

Complexity:

- expected worst-case time complexity is O(N*log(N));

*prefix suffix set* is a pair of indices (P, S) such that 0 ≤ P, S < N and such that:

The goal is to calculate the number of prefix suffix sets in the array.

For example, consider array A such that:

Write a function:

function solution($A);

For example, given:

the function should return 14, as explained above.

Assume that:

- N is an integer within the range [1..40,000];
- each element of array A is an integer within the range [−1,000,000,000..1,000,000,000].

Complexity:

- expected worst-case time complexity is O(N*log(N));

*prefix suffix set* is a pair of indices (P, S) such that 0 ≤ P, S < N and such that:

The goal is to calculate the number of prefix suffix sets in the array.

For example, consider array A such that:

Write a function:

sub solution { my (@A)=@_; ... }

For example, given:

the function should return 14, as explained above.

Assume that:

- N is an integer within the range [1..40,000];
- each element of array A is an integer within the range [−1,000,000,000..1,000,000,000].

Complexity:

- expected worst-case time complexity is O(N*log(N));

*prefix suffix set* is a pair of indices (P, S) such that 0 ≤ P, S < N and such that:

The goal is to calculate the number of prefix suffix sets in the array.

For example, consider array A such that:

Write a function:

def solution(A)

For example, given:

the function should return 14, as explained above.

Assume that:

- N is an integer within the range [1..40,000];
- each element of array A is an integer within the range [−1,000,000,000..1,000,000,000].

Complexity:

- expected worst-case time complexity is O(N*log(N));

*prefix suffix set* is a pair of indices (P, S) such that 0 ≤ P, S < N and such that:

The goal is to calculate the number of prefix suffix sets in the array.

For example, consider array A such that:

Write a function:

def solution(a)

For example, given:

the function should return 14, as explained above.

Assume that:

- N is an integer within the range [1..40,000];
- each element of array A is an integer within the range [−1,000,000,000..1,000,000,000].

Complexity:

- expected worst-case time complexity is O(N*log(N));

*prefix suffix set* is a pair of indices (P, S) such that 0 ≤ P, S < N and such that:

The goal is to calculate the number of prefix suffix sets in the array.

For example, consider array A such that:

Write a function:

object Solution { def solution(a: Array[Int]): Int }

For example, given:

the function should return 14, as explained above.

Assume that:

- N is an integer within the range [1..40,000];
- each element of array A is an integer within the range [−1,000,000,000..1,000,000,000].

Complexity:

- expected worst-case time complexity is O(N*log(N));

*prefix suffix set* is a pair of indices (P, S) such that 0 ≤ P, S < N and such that:

The goal is to calculate the number of prefix suffix sets in the array.

For example, consider array A such that:

Write a function:

public func solution(inout A : [Int]) -> Int

For example, given:

the function should return 14, as explained above.

Assume that:

- N is an integer within the range [1..40,000];
- each element of array A is an integer within the range [−1,000,000,000..1,000,000,000].

Complexity:

- expected worst-case time complexity is O(N*log(N));

*prefix suffix set* is a pair of indices (P, S) such that 0 ≤ P, S < N and such that:

The goal is to calculate the number of prefix suffix sets in the array.

For example, consider array A such that:

Write a function:

public func solution(_ A : inout [Int]) -> Int

For example, given:

the function should return 14, as explained above.

Assume that:

- N is an integer within the range [1..40,000];
- each element of array A is an integer within the range [−1,000,000,000..1,000,000,000].

Complexity:

- expected worst-case time complexity is O(N*log(N));

*prefix suffix set* is a pair of indices (P, S) such that 0 ≤ P, S < N and such that:

The goal is to calculate the number of prefix suffix sets in the array.

For example, consider array A such that:

Write a function:

Private Function solution(A As Integer()) As Integer

For example, given:

the function should return 14, as explained above.

Assume that:

- N is an integer within the range [1..40,000];
- each element of array A is an integer within the range [−1,000,000,000..1,000,000,000].

Complexity:

- expected worst-case time complexity is O(N*log(N));

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