CSE 2050 Exam 2 - Recursion, Sorting, and Hashing with Correct Verified Answers| Latest 2024
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Module
CSE 2050
Institution
CSE 2050
emoization - ANSWER Write the recursive function top-down.
Alter the function to check if we've already calculated the value.
If so, use the pre-calculated value,
If not, do the recursive call.
Fib - Memo - ANSWER def fib(n, fib_cache):
if n in fib_cache:
return fib_cache[n]
fib_cache[n] = f...
CSE 2050 Exam 2 - Recursion, Sorting, and Hashing with Correct Verified Answers | Latest 2024 Memoization - ANSWER Write the recursive function top -down. Alter the function to check if we've already calculated the value. If so, use the pre -calculated value, If not, do the recursive call. Fib - Memo - ANSWER def fib(n, f ib_cache): if n in fib_cache: return fib_cache[n] fib_cache[n] = fib(n -1, fib_cache) + fib(n -2, fib_cache) return fib_cache[n] Memoization Pros - ANSWER Can be more intuitive to code / understand. Can be memory saving if you don't need answers to all subproblems. Memoization Cons - ANSWER Depending on implementation, larger overhead due to recursion. Tabulation - ANSWER Bottom -Up. Solve smaller problems first. Then bigger problems. ... Then finally solve the real problem. Fib - Tab - ANSWER def fib(n): f = [] f.append(1) f.append(1) for i in range(2, n + 1): f.append(f[i -1] + f[i -2]) return f[n] Linear Search - ANSWER Look for an item x in a sorted list. Approach: Step through a n array of items one at a time. Look for the item x. Search stops when... Item x is found. Or when search has examined all items and x is not found. Running Time: O(n) Binary Search - ANSWER Classic, recursive algorithm. If you are looking for an item in a sorted list, you break the list in half and repeat the search on whichever side you could contain the missing element, which can be found by comparing the median element. Then, repeating on the smaller list is just a single recursive call. Binary Se arch Poor Implementation - ANSWER def bs(L, item): if len(L) == 0: return False
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