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
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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 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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