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Chapter 1: Problem 8

Under what circumstances, when a searching operation is needed, would sequential Search (Algorithm 1.1) not be appropriate?

Short Answer

Expert verified
Sequential search wouldn't be appropriate when the list is large, sorted or frequent searches are conducted. In such cases, more efficient search algorithms like binary search may be a better choice.

Step by step solution

01

Understand Sequential Search Algorithm

To first determine under which circumstances sequential search wouldn't be appropriate, it's necessary to understand how the sequential search works. The sequential search, or linear search, operates by starting at the first item in the list and comparing it against the search key. It moves sequentially through the list, comparing each item, until either the match is found or the end of the list is reached.
02

Evaluate Efficiency of Sequential Search

The efficiency of sequential search algorithm depends on where the search key is located. If it's at the beginning of the list, it will be found quickly. However, if it's at the end of the list or not present in the list at all, every element in the list will need to be searched, which can be inefficient for large lists.
03

Identify When Sequential Search Is Not Appropriate

Considering the operating mechanism and efficiency of sequential search, it is clear that it would not be appropriate under the following circumstances: 1) When the list is large, as it may need to compare each element in the list until it finds a match; 2) When the list is sorted, as a more efficient algorithm like binary search can be used; 3) When frequent searches are conducted, as its inefficiency would compound over time.

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Most popular questions from this chapter

Using the Properties of Order in Section \(1.4 .2,\) show that $$5 n^{5}+4 n^{4}+6 n^{3}+2 n^{2}+n+7 \in \Theta\left(n^{5}\right)$$

Write an algorithm that finds the largest number in a list (an array) of \(n\) numbers.

Show directly that \(f(n)=n^{2}+3 n^{3} \in \Theta\left(n^{3}\right)\). That is, use the definitions of \(O\) and \(\Omega\) to show that \(f(n)\) is in both \(O\left(n^{3)} \text { and } \Omega\left(n^{3)}\right.\right.\)

Give an algorithm for the following problem, Given a list of \(n\) distinct positive integers, partition the list into two sublists, each of size \(n / 2,\) such that the difference between the sums of integers in the two sublists is minimized. Determine the time complexity of your algorithm. You may assume that \(n\) is a multiple of 2

Group the following function by complexity category. $$\begin{aligned}&n \ln n \quad(\lg n)^{2} \quad 5 n^{2}+7 n \quad n^{5 / 2}\\\&n ! \quad 2^{n !} \quad 4^{n} \quad n^{n} \quad n^{n}+\ln n\\\&5^{\lg n} \lg (n !) \quad(\lg n) ! \quad \sqrt{n} \quad e^{n} \quad 8 n+12 \quad 10^{n}+n^{20}\end{aligned}$$
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