Assume that you are given the following linear time algorithm: BSTNode *BuildBST(A, n): It takes an array and its size as arguments, builds a binary search tree, and returns a pointer to its root in θ(n) time. A BSTNode structure contains pointers LC, RC of type BSTNode* pointing to the left child and right child of that node respectively. Step 1: Use the above function to write pseudocode to output the array in ascending order in linear time. PrintAscending(A,n){   //Output elements of A in ascending order   //Write pseudocode below

In this question, you will find the maximum subarray of the array A = using the θ(nlog(n)) divide and conquer algorithm discussed in class. Step 2: Show how the algorithm computes the answer.

In this question, you will construct the max heap that results from using BUILD-MAX-HEAP to create a heap from the following array:  . Steps 1-2 were performed above.  Now perform step 3: Step 3.  Fill in the tree which results after the second exchange is performed.   / \ / \ / \ / \ / \  

In this question, you will find the maximum subarray of the array A = using the θ(nlog(n)) divide and conquer algorithm discussed in class. Step 5: Give the recurrence relation for the maximum subarray algorithm FIND-MAXIMUM-SUBARRAY.  That is fill in the right hand side of the following equation: T(n) =

In this question, you will construct the max heap that results from using BUILD-MAX-HEAP to create a heap from the following array:  . Steps 1-4 were performed above.  Now perform step 5: Step 5.  Fill in the tree which results after the fourth exchange is performed. The tree is the finished max heap in the pointer representation.   / \ / \ / \ / \ / \  

In this question, you will construct the max heap that results from using BUILD-MAX-HEAP to create a heap from the following array:  . Steps 1-3 were performed above.  Now perform step 4: Step 4.  Fill in the tree which results after the third exchange is performed.   / \ / \ / \ / \ / \  

In this question, you will use dynamic programming to determine the longest common subsequence of   and . Step 1. Provide the recursive equation for the recurrence.  That is, complete the right hand side: c =

In this question, you will use dynamic programming to determine the longest common subsequence of   and . Step 2. Use the LCS-Length algorithm to select the correct b-entry (arrow) and c-entry (number) for each entry in the table.   ____ j____ ____0____ 1 2 3 4 5 6 ____i____ ____yj____ A C G T T A ____0____ ____xi____ ____0____ 0 0 0 0 0 0 ____1____ ____C____ ____0____ ____2____   ____A____ ____0____ ____3____ ____G____ ____0____ ____4____ ____T____ ____0____ ____5____ ____A____ ____0____          

In this question, you will find the maximum subarray of the array A = using the θ(nlog(n)) divide and conquer algorithm discussed in class. Step 5: Give the recurrence relation for the maximum subarray algorithm FIND-MAXIMUM-SUBARRAY.  That is fill in the right hand side of the following equation: T(n) =

In this question, you will construct the max heap that results from using BUILD-MAX-HEAP to create a heap from the following array:  . Steps 1-5 were performed above, yielding the finished max heap in Step 5. Now fill in the array A to give the array representation of the max heap. A A A A A A A A A A A