Sorting: Insertion Sort& Quick Sort - GitHub Pages
Department of General and Computational Linguistics
Sorting: Insertion Sort & Quick Sort
Data Structures and Algorithms for CL III, WS 2019-2020
Corina Dima
corina.dima@uni-tuebingen.de
Data Structures & Algorithms in Python
MICHAEL GOODRICH
ROBERTO TAMASSIA
MICHAEL GOLDWASSER
12. Sorting and Selection
v Why study sorting
algorithms?
v Insertion sort (S. 5.5.2)
v Quick-sort
v Optimizations for quick-sort
Sorting: Insertion Sort & Quick Sort | 2
Why Study Sorting Algorithms?
? Sorting is among the most important and well studied computing
problems
? Data is often stored in sorted order, to allow for efficient searching
(i.e. with binary search)
? Many algorithms rely on sorting as a subroutine
? Programming languages have highly optimized, built-in sorting
functions ¨C which should be used
-
Python: sorted(), sort() from the list class
-
Java: Arrays.sort()
Sorting: Insertion Sort & Quick Sort | 3
Why Study Sorting Algorithms? (cont¡¯d)
? Understand
-
what sorting algorithms do
-
what can be expected in terms of efficiency
-
how the efficiency of a sorting algorithm can depend on the
initial ordering of the data or the type of objects being sorted
Sorting: Insertion Sort & Quick Sort | 4
Sorting
? Given a collection, rearrange its elements such that they are
ordered from smallest to largest ¨C or produce a new copy of the
sequence with such an order
? We assume that such a consistent order exists
? In Python, natural order is typically defined using the < operator,
having two properties:
-
Irreflexive property: " ¡Ú "
-
Transitive property: if "% < "& and "& < "' then "% < "'
Sorting: Insertion Sort & Quick Sort | 5
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