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[Page 976 (continued)]

20.1. Introduction

Searching data involves determining whether a value (referred to as the search key) is present in the data and, if so, finding the value's location. Two popular search algorithms are the simple linear search (introduced in Section 7.7) and the faster but more complex binary search, which is introduced in this chapter.

Sorting places data in order, typically ascending or descending, based on one or more sort keys. A list of names could be sorted alphabetically, bank accounts could be sorted by account number, employee payroll records could be sorted by social security number, and so on. Previously, you learned about insertion sort (Section 7.8) and selection sort (Section 8.6). This chapter introduces the more efficient, but more complex merge sort. Figure 20.1 summarizes the searching and sorting algorithms discussed in the examples and exercises of this book. This chapter also introduces Big O notation, which is used to estimate the worst-case runtime for an algorithmthat is, how hard an algorithm may have to work to solve a problem.

Figure 20.1. Searching and sorting algorithms in this text.
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Searching Algorithms


Linear search

Section 7.7


Binary search

Section 20.2.2


Recursive linear search

Exercise 20.8


Recursive binary search

Exercise 20.9


Binary tree search

Section 21.7


Linear search of a linked list

Exercise 21.21


binary_search standard library function

Section 23.5.6

Sorting Algorithms


Insertion sort

Section 7.8


Selection sort

Section 8.6


Recursive merge sort

Section 20.3.3


Bubble sort

Exercises 20.5 and 20.6


Bucket sort

Exercise 20.7


Recursive quicksort

Exercise 20.10


Binary tree sort

Section 21.7


sort standard library function

Section 23.5.6


Heap sort

Section 23.5.12

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