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7.1.3 Comparison with Other Data Structures
Compared to arrays and linked lists, trees provide more flexibility in representing
hierarchical data. Arrays offer random access but lack hierarchy, while linked lists provide
dynamic memory but remain linear. Trees combine dynamic memory with hierarchical
organization, making them powerful for complex applications.
7.2 Binary Trees
Binary trees are one of the most fundamental and widely studied forms of trees in
computer science. A binary tree is defined as a hierarchical structure in which each node can
have at most two children, commonly referred to as the left child and the right child. This
restriction makes binary trees simpler to analyze and implement compared to general trees,
while still being powerful enough to serve as the foundation for many advanced data
structures such as binary search trees, heaps, and balanced trees. The binary tree structure
allows efficient organization of data, enabling faster searching, insertion, and deletion
operations compared to linear structures like arrays or linked lists.
7.2.1 Structure of Binary Trees
The structure of a binary tree is recursive in nature. Each node contains three
components: the data element, a pointer to the left child, and a pointer to the right child. If a
node does not have a left or right child, the corresponding pointer is set to NULL. The recursive
definition means that each child node itself can be considered the root of a smaller binary
tree. This property makes binary trees particularly suitable for recursive algorithms, as many
operations such as traversal or insertion can be expressed naturally in recursive terms.
Binary trees can vary in shape depending on how nodes are inserted. A tree may be
complete, where all levels are filled except possibly the last, or skewed, where all nodes lean
to one side, resembling a linked list. The shape of the tree directly affects its efficiency, as
balanced trees provide logarithmic performance, while skewed trees degrade to linear
performance.
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