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© 2014 Goodrich, Tamassia, Goldwasser AVL Trees 1 AVL Trees 6 3 8 4 v z Presentation for use with the textbook Data Structures and Algorithms in Java, 6 th edition, by M. T. Goodrich, R. Tamassia, and M. H. Goldwasser, Wiley, 2014

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Page 1: Balanced Binary Search Trees - University of Iowahomepage.cs.uiowa.edu/~bmccune/021/AVL.pdfPresentation for use with the textbook Data Structures and Algorithms in Java, 6th edition,

© 2014 Goodrich, Tamassia, GoldwasserAVL Trees 1

AVL Trees6

3 8

4

v

z

Presentation for use with the textbook Data Structures and Algorithms in Java, 6th edition, by M. T. Goodrich, R. Tamassia, and M. H. Goldwasser, Wiley, 2014

Page 2: Balanced Binary Search Trees - University of Iowahomepage.cs.uiowa.edu/~bmccune/021/AVL.pdfPresentation for use with the textbook Data Structures and Algorithms in Java, 6th edition,

© 2014 Goodrich, Tamassia, GoldwasserAVL Trees 2

AVL Tree Definition

AVL trees are

balanced

An AVL Tree is a

binary search tree

such that for every

internal node v of T,

the heights of the

children of v can

differ by at most 1

88

44

17 78

32 50

48 62

2

4

1

1

2

3

1

1

An example of an AVL tree where the heights are shown next to the nodes

Page 3: Balanced Binary Search Trees - University of Iowahomepage.cs.uiowa.edu/~bmccune/021/AVL.pdfPresentation for use with the textbook Data Structures and Algorithms in Java, 6th edition,

© 2014 Goodrich, Tamassia, GoldwasserAVL Trees 3

Height of an AVL TreeFact: The height of an AVL tree storing n keys is O(log n).Proof (by induction): Let us bound n(h): the minimum number of internal nodes of an AVL tree of height h.

We easily see that n(1) = 1 and n(2) = 2For n > 2, an AVL tree of height h contains the root node, one AVL subtree of height h-1 and another of height h-2.That is, n(h) = 1 + n(h-1) + n(h-2)Knowing n(h-1) > n(h-2), we get n(h) > 2n(h-2). Son(h) > 2n(h-2), n(h) > 4n(h-4), n(h) > 8n(n-6), … (by induction),n(h) > 2in(h-2i)

3

4 n(1)

n(2)

Page 4: Balanced Binary Search Trees - University of Iowahomepage.cs.uiowa.edu/~bmccune/021/AVL.pdfPresentation for use with the textbook Data Structures and Algorithms in Java, 6th edition,

© 2014 Goodrich, Tamassia, GoldwasserAVL Trees 4

Height of an AVL TreeFact: The height of an AVL tree storing n keys is O(log n).Proof (by induction): Let us bound n(h): the minimum number of internal nodes of an AVL tree of height h.

.....Knowing n(h-1) > n(h-2), we get n(h) > 2n(h-2). Son(h) > 2n(h-2), n(h) > 4n(h-4), n(h) > 8n(n-6), … (by induction),n(h) > 2in(h-2i)

Choose i=h/2-1, then we have 2h/2-1n(h-2(h/2-1))=2h/2-1n(2)

Solving the base case we get: n(h) > 2 h/2-1

Taking logarithms: h < 2log n(h) +2Thus the height of an AVL tree is O(log n)

3

4 n(1)

n(2)

Page 5: Balanced Binary Search Trees - University of Iowahomepage.cs.uiowa.edu/~bmccune/021/AVL.pdfPresentation for use with the textbook Data Structures and Algorithms in Java, 6th edition,

© 2014 Goodrich, Tamassia, GoldwasserAVL Trees 5

InsertionInsertion is as in a binary search treeAlways done by expanding an external node.Example:

44

17

78

32

50

88

48

62

54w

b=x

a=y

c=z

44

17 78

32 50 88

48 62

before insertion

after insertion

Page 6: Balanced Binary Search Trees - University of Iowahomepage.cs.uiowa.edu/~bmccune/021/AVL.pdfPresentation for use with the textbook Data Structures and Algorithms in Java, 6th edition,

© 2014 Goodrich, Tamassia, GoldwasserAVL Trees 6

Trinode RestructuringLet (a,b,c) be the inorder listing of x, y, zPerform the rotations needed to make b the topmost node of the three

b=y

a=z

c=xT0

T1

T2 T3

b=y

a=z c=x

T0 T1 T2 T3

c=y

b=x

a=z

T0

T1 T2

T3b=x

c=ya=z

T0 T1 T2 T3

Double rotation around c and a

Single rotation around b

Page 7: Balanced Binary Search Trees - University of Iowahomepage.cs.uiowa.edu/~bmccune/021/AVL.pdfPresentation for use with the textbook Data Structures and Algorithms in Java, 6th edition,

© 2014 Goodrich, Tamassia, GoldwasserAVL Trees 7

Insertion Example, continued

88

44

17 78

32 50

48 62

2

5

1

1

3

4

2

1

54

1

T0T2

T3

x

y

z

2

3

4

5

67

1

88

44

17

7832 50

48

622

4

1

1

2 2

3

154

1

T0 T1

T2

T3

x

y z

unbalanced...

...balanced

12

3

4

5

6

7

T1

Page 8: Balanced Binary Search Trees - University of Iowahomepage.cs.uiowa.edu/~bmccune/021/AVL.pdfPresentation for use with the textbook Data Structures and Algorithms in Java, 6th edition,

© 2014 Goodrich, Tamassia, GoldwasserAVL Trees 8

Restructuring (as Single Rotations)Single Rotations:

T0T1

T2

T3

c = xb = y

a = z

T0 T1 T2

T3

c = xb = y

a = zsingle rotation

T3T2

T1

T0

a = xb = y

c = z

T0T1T2

T3

a = xb = y

c = zsingle rotation

Page 9: Balanced Binary Search Trees - University of Iowahomepage.cs.uiowa.edu/~bmccune/021/AVL.pdfPresentation for use with the textbook Data Structures and Algorithms in Java, 6th edition,

© 2014 Goodrich, Tamassia, GoldwasserAVL Trees 9

Restructuring (as Double Rotations)double rotations:

double rotationa = z

b = xc = y

T0T2

T1

T3 T0

T2T3T1

a = zb = x

c = y

double rotationc = z

b = xa = y

T0T2

T1

T3 T0

T2T3 T1

c = zb = x

a = y

Page 10: Balanced Binary Search Trees - University of Iowahomepage.cs.uiowa.edu/~bmccune/021/AVL.pdfPresentation for use with the textbook Data Structures and Algorithms in Java, 6th edition,

© 2014 Goodrich, Tamassia, GoldwasserAVL Trees 10

RemovalRemoval begins as in a binary search tree, which means the node removed will become an empty external node. Its parent, w, may cause an imbalance.Example:

44

17

7832 50

8848

62

54

44

17

7850

8848

62

54

before deletion of 32 after deletion

Page 11: Balanced Binary Search Trees - University of Iowahomepage.cs.uiowa.edu/~bmccune/021/AVL.pdfPresentation for use with the textbook Data Structures and Algorithms in Java, 6th edition,

© 2014 Goodrich, Tamassia, GoldwasserAVL Trees 11

Rebalancing after a RemovalLet z be the first unbalanced node encountered while travelling up the tree from w. Also, let y be the child of z with the larger height, and let x be the child of y with the larger height

We perform a trinode restructuring to restore balance at z

As this restructuring may upset the balance of another node higher in the tree, we must continue checking for balance until the root of T is reached

44

17

7850

8848

62

54

w

c=x

b=y

a=z

44

17

78

50 88

48

62

54

Page 12: Balanced Binary Search Trees - University of Iowahomepage.cs.uiowa.edu/~bmccune/021/AVL.pdfPresentation for use with the textbook Data Structures and Algorithms in Java, 6th edition,

© 2014 Goodrich, Tamassia, GoldwasserAVL Trees 12

AVL Tree PerformanceAVL tree storing n items

The data structure uses O(n) space A single restructuring takes O(1) time

using a linked-structure binary tree

Searching takes O(log n) time height of tree is O(log n), no restructures needed

Insertion takes O(log n) time initial find is O(log n) restructuring up the tree, maintaining heights is O(log n)

Removal takes O(log n) time initial find is O(log n) restructuring up the tree, maintaining heights is O(log n)

Page 13: Balanced Binary Search Trees - University of Iowahomepage.cs.uiowa.edu/~bmccune/021/AVL.pdfPresentation for use with the textbook Data Structures and Algorithms in Java, 6th edition,

© 2014 Goodrich, Tamassia, Goldwasser

Java Implementation

AVL Trees 13

Page 14: Balanced Binary Search Trees - University of Iowahomepage.cs.uiowa.edu/~bmccune/021/AVL.pdfPresentation for use with the textbook Data Structures and Algorithms in Java, 6th edition,

© 2014 Goodrich, Tamassia, Goldwasser

Java Implementation, 2

AVL Trees 14

Page 15: Balanced Binary Search Trees - University of Iowahomepage.cs.uiowa.edu/~bmccune/021/AVL.pdfPresentation for use with the textbook Data Structures and Algorithms in Java, 6th edition,

© 2014 Goodrich, Tamassia, Goldwasser

Java Implementation, 3

AVL Trees 15