Which of these two algorithms has a better big-O run-time? For each, list the big-O run-time notation for each and how you determined it. def gnomesort(seq): i=0 while i1: l=mergesort(l) if len(r)>1: r=mergesort(r) res=[] while l and r: if l[-1] >= r[-1]: res.append(l.pop()) else: res.append(r.pop()) res.reverse() return (l or r) + res
Which of these two algorithms has a better big-O run-time? For each, list the big-O run-time notation for each and how you determined it. def gnomesort(seq): i=0 while i1: l=mergesort(l) if len(r)>1: r=mergesort(r) res=[] while l and r: if l[-1] >= r[-1]: res.append(l.pop()) else: res.append(r.pop()) res.reverse() return (l or r) + res
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Question
Which of these two
def gnomesort(seq):
i=0
while i<len(seq):
if i==0 or seq[i-1]<=seq[i]:
i+=1
else:
seq[i], seq[i-1] = seq[i-1], seq[i]
i-=1
and
def mergesort(seq):
mid=len(seq)//2
l,r=seq[:mid],seq[mid:]
if len(l)>1: l=mergesort(l)
if len(r)>1: r=mergesort(r)
res=[]
while l and r:
if l[-1] >= r[-1]:
res.append(l.pop())
else:
res.append(r.pop())
res.reverse()
return (l or r) + res
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