def before (k, A) which takes an integer k and an array A of integers as inputs and returns a new array consisting of all the integers in A which come before the last occurrence of k in A, in the same order they are in A. For example, if A İS [1,2,3,6,7,2,3,4] then before (3,A) will return [1,2,3,6,7,2].Ifk does not occur in A, the function should return None.

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Write a function that takes in an array of integers and returns the integers that are either palindromes or almost-palindromes. An almost-palindrome is any integer that can be rearranged to form a palindrome. For example, the numbers 677 and 338 are both almost-palindromes, since they can be rearranged to form 767 and 383, respectively. Examples palindromeSieve ([443, 12, 639, 121, 3232]) [443, 121, 3232] // Since 443 => 434; 121 is a palindrome; 3232 => 2332 or 3223 palindromeSieve([5, 55, 6655, 8787]) → [5, 55, 6655, 8787] // Single-digit numbers are automatically palindromes. palindromeSieve ([897, 89, 23, 54, 6197, 53342]) - []

Write a function lis_rec(arr) that outputs the length of the longest increasing sequence and the actual longest increasing sequence. This function should use divide and conquer strategy to the solve the problem, by using an auxiliary function that is recursive. For example, one possibility is to define a recursive function, lis_rec(arr, i, prev), that takes the array arr, an index i, and the previous element index prev of LIS (which is part of the array arr before index i), and returns the length of the LIS that can be obtained by considering the subarray arr[i:]. Write a dynamic programming version ofthe function, lis_dp(arr), that outputs the length of the longest increasing sequence and the actual longest increasing sequence by using a table to store the results of subproblems in a bottom-up manner. Test the performance of the two functions on arrays of length n = 100, 500, 1000, 5000, 10000. Compare the running times and memory usage of the two functions.

Below is the recursive implementation of binary search from lab with one change (in red): the print statement at the top of the function which prints "BOO" There is also a main function which calls bsearchR on the sorted array data[] with 7 elements and searching for 10. QUESTION: How many BOOS will be printed by this program? // Recursive Binary Search Routine that does the "Real" Work int bsearchR(int a[], int lo, int hi, int x) { int m; printf("BO0\n"); // <<<<==== NEW STATEMENT if(hi < lo) return -1; m = (lo + hi) / 2; if(a[m] == x) return m; else if(x < a[m]) return bsearchR(a, lo, m-1, x); else return bsearchR(a, m+1, hi, x); } int main() { int data[] = {5, 8, 12, 15, 20, 25, 30}; int idx = bsearchR(data, e, 6, 10); return 0; }