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Compute the number of "True" values in an OR-Pascal-triangle structure.

Programming language:
Spoken language:

On the sequence of logical values (`1` or `0`) we can build up an OR-Pascal-triangle structure. Instead of summing the values, as in a standard Pascal-triangle, we will combine them using the OR function. That means that the lowest row is simply the input sequence, and every entry in each subsequent row is the OR of the two elements below it. For example, the OR-Pascal-triangle built on the array [`1`, `0`, `0`, `1`, `0`] is as follows:

Your job is to count the number of nodes in the OR-Pascal-triangle that contain the value `1` (this number is 11 for the animation above).

Write a function:

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

that, given an array P of N Booleans, returns the number of fields in the OR-Pascal-triangle built on P that contain the value `1`. If the result is greater than 1,000,000,000, your function should return 1,000,000,000.

Given P = [`1`, `0`, `0`, `1`, `0`], the function should return 11, as explained above.

Given P = [`1`, `0`, `0`, `1`], the function should return 7, as can be seen in the animation below.

Write an ** efficient** algorithm for the following assumptions:

- N is an integer within the range [1..100,000].

Copyright 2009–2019 by Codility Limited. All Rights Reserved. Unauthorized copying, publication or disclosure prohibited.

On the sequence of logical values (`true` or `false`) we can build up an OR-Pascal-triangle structure. Instead of summing the values, as in a standard Pascal-triangle, we will combine them using the OR function. That means that the lowest row is simply the input sequence, and every entry in each subsequent row is the OR of the two elements below it. For example, the OR-Pascal-triangle built on the array [`true`, `false`, `false`, `true`, `false`] is as follows:

Your job is to count the number of nodes in the OR-Pascal-triangle that contain the value `true` (this number is 11 for the animation above).

Write a function:

int solution(vector<bool> &P);

that, given an array P of N Booleans, returns the number of fields in the OR-Pascal-triangle built on P that contain the value `true`. If the result is greater than 1,000,000,000, your function should return 1,000,000,000.

Given P = [`true`, `false`, `false`, `true`, `false`], the function should return 11, as explained above.

Given P = [`true`, `false`, `false`, `true`], the function should return 7, as can be seen in the animation below.

Write an ** efficient** algorithm for the following assumptions:

- N is an integer within the range [1..100,000].

Copyright 2009–2019 by Codility Limited. All Rights Reserved. Unauthorized copying, publication or disclosure prohibited.

On the sequence of logical values (`true` or `false`) we can build up an OR-Pascal-triangle structure. Instead of summing the values, as in a standard Pascal-triangle, we will combine them using the OR function. That means that the lowest row is simply the input sequence, and every entry in each subsequent row is the OR of the two elements below it. For example, the OR-Pascal-triangle built on the array [`true`, `false`, `false`, `true`, `false`] is as follows:

Your job is to count the number of nodes in the OR-Pascal-triangle that contain the value `true` (this number is 11 for the animation above).

Write a function:

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

that, given an array P of N Booleans, returns the number of fields in the OR-Pascal-triangle built on P that contain the value `true`. If the result is greater than 1,000,000,000, your function should return 1,000,000,000.

Given P = [`true`, `false`, `false`, `true`, `false`], the function should return 11, as explained above.

Given P = [`true`, `false`, `false`, `true`], the function should return 7, as can be seen in the animation below.

Write an ** efficient** algorithm for the following assumptions:

- N is an integer within the range [1..100,000].

Copyright 2009–2019 by Codility Limited. All Rights Reserved. Unauthorized copying, publication or disclosure prohibited.

On the sequence of logical values (`true` or `false`) we can build up an OR-Pascal-triangle structure. Instead of summing the values, as in a standard Pascal-triangle, we will combine them using the OR function. That means that the lowest row is simply the input sequence, and every entry in each subsequent row is the OR of the two elements below it. For example, the OR-Pascal-triangle built on the array [`true`, `false`, `false`, `true`, `false`] is as follows:

Your job is to count the number of nodes in the OR-Pascal-triangle that contain the value `true` (this number is 11 for the animation above).

Write a function:

func Solution(P []bool) int

that, given an array P of N Booleans, returns the number of fields in the OR-Pascal-triangle built on P that contain the value `true`. If the result is greater than 1,000,000,000, your function should return 1,000,000,000.

Given P = [`true`, `false`, `false`, `true`, `false`], the function should return 11, as explained above.

Given P = [`true`, `false`, `false`, `true`], the function should return 7, as can be seen in the animation below.

Write an ** efficient** algorithm for the following assumptions:

- N is an integer within the range [1..100,000].

`true` or `false`) we can build up an OR-Pascal-triangle structure. Instead of summing the values, as in a standard Pascal-triangle, we will combine them using the OR function. That means that the lowest row is simply the input sequence, and every entry in each subsequent row is the OR of the two elements below it. For example, the OR-Pascal-triangle built on the array [`true`, `false`, `false`, `true`, `false`] is as follows:

`true` (this number is 11 for the animation above).

Write a function:

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

`true`. If the result is greater than 1,000,000,000, your function should return 1,000,000,000.

`true`, `false`, `false`, `true`, `false`], the function should return 11, as explained above.

`true`, `false`, `false`, `true`], the function should return 7, as can be seen in the animation below.

Write an ** efficient** algorithm for the following assumptions:

- N is an integer within the range [1..100,000].

`true` or `false`) we can build up an OR-Pascal-triangle structure. Instead of summing the values, as in a standard Pascal-triangle, we will combine them using the OR function. That means that the lowest row is simply the input sequence, and every entry in each subsequent row is the OR of the two elements below it. For example, the OR-Pascal-triangle built on the array [`true`, `false`, `false`, `true`, `false`] is as follows:

`true` (this number is 11 for the animation above).

Write a function:

function solution(P);

`true`. If the result is greater than 1,000,000,000, your function should return 1,000,000,000.

`true`, `false`, `false`, `true`, `false`], the function should return 11, as explained above.

`true`, `false`, `false`, `true`], the function should return 7, as can be seen in the animation below.

Write an ** efficient** algorithm for the following assumptions:

- N is an integer within the range [1..100,000].

`true` or `false`) we can build up an OR-Pascal-triangle structure. Instead of summing the values, as in a standard Pascal-triangle, we will combine them using the OR function. That means that the lowest row is simply the input sequence, and every entry in each subsequent row is the OR of the two elements below it. For example, the OR-Pascal-triangle built on the array [`true`, `false`, `false`, `true`, `false`] is as follows:

`true` (this number is 11 for the animation above).

Write a function:

fun solution(P: Array<Boolean>): Int

`true`. If the result is greater than 1,000,000,000, your function should return 1,000,000,000.

`true`, `false`, `false`, `true`, `false`], the function should return 11, as explained above.

`true`, `false`, `false`, `true`], the function should return 7, as can be seen in the animation below.

Write an ** efficient** algorithm for the following assumptions:

- N is an integer within the range [1..100,000].

`true` or `false`) we can build up an OR-Pascal-triangle structure. Instead of summing the values, as in a standard Pascal-triangle, we will combine them using the OR function. That means that the lowest row is simply the input sequence, and every entry in each subsequent row is the OR of the two elements below it. For example, the OR-Pascal-triangle built on the array [`true`, `false`, `false`, `true`, `false`] is as follows:

`true` (this number is 11 for the animation above).

Write a function:

function solution(P)

`true`. If the result is greater than 1,000,000,000, your function should return 1,000,000,000.

`true`, `false`, `false`, `true`, `false`], the function should return 11, as explained above.

`true`, `false`, `false`, `true`], the function should return 7, as can be seen in the animation below.

Write an ** efficient** algorithm for the following assumptions:

- N is an integer within the range [1..100,000].

On the sequence of logical values (`1` or `0`) we can build up an OR-Pascal-triangle structure. Instead of summing the values, as in a standard Pascal-triangle, we will combine them using the OR function. That means that the lowest row is simply the input sequence, and every entry in each subsequent row is the OR of the two elements below it. For example, the OR-Pascal-triangle built on the array [`1`, `0`, `0`, `1`, `0`] is as follows:

Your job is to count the number of nodes in the OR-Pascal-triangle that contain the value `1` (this number is 11 for the animation above).

Write a function:

int solution(NSMutableArray *P);

that, given an array P of N Booleans, returns the number of fields in the OR-Pascal-triangle built on P that contain the value `1`. If the result is greater than 1,000,000,000, your function should return 1,000,000,000.

Given P = [`1`, `0`, `0`, `1`, `0`], the function should return 11, as explained above.

Given P = [`1`, `0`, `0`, `1`], the function should return 7, as can be seen in the animation below.

Write an ** efficient** algorithm for the following assumptions:

- N is an integer within the range [1..100,000].

On the sequence of logical values (`True` or `False`) we can build up an OR-Pascal-triangle structure. Instead of summing the values, as in a standard Pascal-triangle, we will combine them using the OR function. That means that the lowest row is simply the input sequence, and every entry in each subsequent row is the OR of the two elements below it. For example, the OR-Pascal-triangle built on the array [`True`, `False`, `False`, `True`, `False`] is as follows:

Your job is to count the number of nodes in the OR-Pascal-triangle that contain the value `True` (this number is 11 for the animation above).

Write a function:

function solution(P: array of boolean; N: longint): longint;

that, given an array P of N Booleans, returns the number of fields in the OR-Pascal-triangle built on P that contain the value `True`. If the result is greater than 1,000,000,000, your function should return 1,000,000,000.

Given P = [`True`, `False`, `False`, `True`, `False`], the function should return 11, as explained above.

Given P = [`True`, `False`, `False`, `True`], the function should return 7, as can be seen in the animation below.

Write an ** efficient** algorithm for the following assumptions:

- N is an integer within the range [1..100,000].

`true` or `false`) we can build up an OR-Pascal-triangle structure. Instead of summing the values, as in a standard Pascal-triangle, we will combine them using the OR function. That means that the lowest row is simply the input sequence, and every entry in each subsequent row is the OR of the two elements below it. For example, the OR-Pascal-triangle built on the array [`true`, `false`, `false`, `true`, `false`] is as follows:

`true` (this number is 11 for the animation above).

Write a function:

function solution($P);

`true`. If the result is greater than 1,000,000,000, your function should return 1,000,000,000.

`true`, `false`, `false`, `true`, `false`], the function should return 11, as explained above.

`true`, `false`, `false`, `true`], the function should return 7, as can be seen in the animation below.

Write an ** efficient** algorithm for the following assumptions:

- N is an integer within the range [1..100,000].

On the sequence of logical values (`1` or `0`) we can build up an OR-Pascal-triangle structure. Instead of summing the values, as in a standard Pascal-triangle, we will combine them using the OR function. That means that the lowest row is simply the input sequence, and every entry in each subsequent row is the OR of the two elements below it. For example, the OR-Pascal-triangle built on the array [`1`, `0`, `0`, `1`, `0`] is as follows:

Your job is to count the number of nodes in the OR-Pascal-triangle that contain the value `1` (this number is 11 for the animation above).

Write a function:

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

that, given an array P of N Booleans, returns the number of fields in the OR-Pascal-triangle built on P that contain the value `1`. If the result is greater than 1,000,000,000, your function should return 1,000,000,000.

Given P = [`1`, `0`, `0`, `1`, `0`], the function should return 11, as explained above.

Given P = [`1`, `0`, `0`, `1`], the function should return 7, as can be seen in the animation below.

Write an ** efficient** algorithm for the following assumptions:

- N is an integer within the range [1..100,000].

On the sequence of logical values (`True` or `False`) we can build up an OR-Pascal-triangle structure. Instead of summing the values, as in a standard Pascal-triangle, we will combine them using the OR function. That means that the lowest row is simply the input sequence, and every entry in each subsequent row is the OR of the two elements below it. For example, the OR-Pascal-triangle built on the array [`True`, `False`, `False`, `True`, `False`] is as follows:

Your job is to count the number of nodes in the OR-Pascal-triangle that contain the value `True` (this number is 11 for the animation above).

Write a function:

def solution(P)

that, given an array P of N Booleans, returns the number of fields in the OR-Pascal-triangle built on P that contain the value `True`. If the result is greater than 1,000,000,000, your function should return 1,000,000,000.

Given P = [`True`, `False`, `False`, `True`, `False`], the function should return 11, as explained above.

Given P = [`True`, `False`, `False`, `True`], the function should return 7, as can be seen in the animation below.

Write an ** efficient** algorithm for the following assumptions:

- N is an integer within the range [1..100,000].

`true` or `false`) we can build up an OR-Pascal-triangle structure. Instead of summing the values, as in a standard Pascal-triangle, we will combine them using the OR function. That means that the lowest row is simply the input sequence, and every entry in each subsequent row is the OR of the two elements below it. For example, the OR-Pascal-triangle built on the array [`true`, `false`, `false`, `true`, `false`] is as follows:

`true` (this number is 11 for the animation above).

Write a function:

def solution(p)

`true`. If the result is greater than 1,000,000,000, your function should return 1,000,000,000.

`true`, `false`, `false`, `true`, `false`], the function should return 11, as explained above.

`true`, `false`, `false`, `true`], the function should return 7, as can be seen in the animation below.

Write an ** efficient** algorithm for the following assumptions:

- N is an integer within the range [1..100,000].

`true` or `false`) we can build up an OR-Pascal-triangle structure. Instead of summing the values, as in a standard Pascal-triangle, we will combine them using the OR function. That means that the lowest row is simply the input sequence, and every entry in each subsequent row is the OR of the two elements below it. For example, the OR-Pascal-triangle built on the array [`true`, `false`, `false`, `true`, `false`] is as follows:

`true` (this number is 11 for the animation above).

Write a function:

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

`true`. If the result is greater than 1,000,000,000, your function should return 1,000,000,000.

`true`, `false`, `false`, `true`, `false`], the function should return 11, as explained above.

`true`, `false`, `false`, `true`], the function should return 7, as can be seen in the animation below.

Write an ** efficient** algorithm for the following assumptions:

- N is an integer within the range [1..100,000].

`true` or `false`) we can build up an OR-Pascal-triangle structure. Instead of summing the values, as in a standard Pascal-triangle, we will combine them using the OR function. That means that the lowest row is simply the input sequence, and every entry in each subsequent row is the OR of the two elements below it. For example, the OR-Pascal-triangle built on the array [`true`, `false`, `false`, `true`, `false`] is as follows:

`true` (this number is 11 for the animation above).

Write a function:

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

`true`. If the result is greater than 1,000,000,000, your function should return 1,000,000,000.

`true`, `false`, `false`, `true`, `false`], the function should return 11, as explained above.

`true`, `false`, `false`, `true`], the function should return 7, as can be seen in the animation below.

Write an ** efficient** algorithm for the following assumptions:

- N is an integer within the range [1..100,000].

On the sequence of logical values (`True` or `False`) we can build up an OR-Pascal-triangle structure. Instead of summing the values, as in a standard Pascal-triangle, we will combine them using the OR function. That means that the lowest row is simply the input sequence, and every entry in each subsequent row is the OR of the two elements below it. For example, the OR-Pascal-triangle built on the array [`True`, `False`, `False`, `True`, `False`] is as follows:

Your job is to count the number of nodes in the OR-Pascal-triangle that contain the value `True` (this number is 11 for the animation above).

Write a function:

Private Function solution(P As Boolean()) As Integer

that, given an array P of N Booleans, returns the number of fields in the OR-Pascal-triangle built on P that contain the value `True`. If the result is greater than 1,000,000,000, your function should return 1,000,000,000.

Given P = [`True`, `False`, `False`, `True`, `False`], the function should return 11, as explained above.

Given P = [`True`, `False`, `False`, `True`], the function should return 7, as can be seen in the animation below.

Write an ** efficient** algorithm for the following assumptions:

- N is an integer within the range [1..100,000].

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