Question 9 10 pts Select all the answers below which are TRUE Solving the Longest Common Subsequnce problem using Dynamic Programming takes linear time. Longest Common Subsequnce problem has two values for the input size: m and n. To show that a greedy algorithm is an optimal solution, we need to show the subproblem overlapping property and the greedy choice property Solving the Longest Common Subsequence using Brute Force takes exponential time A greedy algorithm makes the choice that looks best at the moment. It makes a locally optimal choice in the hope of obtaining a global optimal solution. Let X- be a sequence. The number of subsequences of X is m! A greedy algorithm is a top-down approach