The formal approach to determining the big-O complexity of an algorithm is to set up recurrence relations and solve them. The recurrence relation for the Linear Search algorithm is defined by: I. T(n)=T(n-1)+1 II. T(n) = 2T(n/2)+1 II. T(n)=T(n-1)+Theta(n) IV. T(n)=2T(n/2)+Theta(n) V. None of the above Ov O II
The formal approach to determining the big-O complexity of an algorithm is to set up recurrence relations and solve them. The recurrence relation for the Linear Search algorithm is defined by: I. T(n)=T(n-1)+1 II. T(n) = 2T(n/2)+1 II. T(n)=T(n-1)+Theta(n) IV. T(n)=2T(n/2)+Theta(n) V. None of the above Ov O II
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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Transcribed Image Text:The formal approach to determining the big-O complexity of an algorithm is to set up recurrence relations and solve them.
The recurrence relation for the Linear Search algorithm is defined by:
I. T(n)=T(n-1)+1
II. T(n) = 2T(n/2)+1
II. T(n)=T(n-1)+Theta(n)
IV. T(n)=2T(n/2)+Theta(n)
V. None of the above
Ov
OII

Transcribed Image Text:Suppose we need to write an efficient program to store N employee records for ABC Inc where each employee record is identified by unique employee id. Consider the following ways to store the records.
1. An array list sorted by employee id
2. A linked list sorted by employee id
3. A linked list not sorted
4. A balanced binary search tree with employee id as key
For data structure above in 1-4, what is the average time to fınd an employee record given employee id as a key?
A. O(log N), O(log N), O(N), O(1)
B. O(log N), O(N), O(N), O(log N)
C. O(N), O(log N). O(N), O(1)
D. O(log N), O(log N), O(N), O(log N)
E. O(log N), O(log N), O(log N), O(1)
O A
O D
O E
O B
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