March 2013
Intermediate to advanced
748 pages
21h 42m
English
book
Data Structures and Algorithms in Python
by Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser
Content preview from Data Structures and Algorithms in Python
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Chapter 12
Sorting and Selection
Contents
12.1 Why Study Sorting Algorithms?
12.2.2 Array-Based Implementation of Merge-Sort
12.2.3 The Running Time of Merge-Sort
12.2.4 Merge-Sort and Recurrence Equations 
12.2.5 Alternative Implementations of Merge-Sort
12.3.2 Additional Optimizations for Quick-Sort
12.4 Studying Sorting through an Algorithmic Lens
12.4.1 Lower Bound for Sorting
12.4.2 Linear-Time Sorting: Bucket-Sort and Radix-Sort
12.5 Comparing Sorting Algorithms
12.6 Python's Built-In Sorting Functions
12.6.1 Sorting According to a Key Function
12.7.2 Randomized Quick-Select
12.1 Why Study Sorting Algorithms?
Much of this chapter focuses on algorithms for sorting a collection of objects. Given a collection, the goal is to rearrange the elements so that they are ordered from smallest to largest (or to produce a new copy of the sequence with such an order). As we did when studying priority queues (see Section 9.4), we assume that such a consistent order exists. In Python, the natural order of objects is typically1 defined using the < operator having following properties:
- Irreflexive property: ...
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