Binary tree terminology in Data Structures Theory - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the sentence: A node with no children is called a {{BLANK_1}}.

Data Structures Theory

A node with no children is called a [1].

Drag options to blanks, or click blank then click option'

Aroot

Bparent

Cleaf

Dsibling

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing leaf with root node.

Thinking a parent node has no children.

A node with no children is called a leaf node in a binary tree.

2fill in blank

medium

Complete the sentence: The topmost node of a binary tree is called the {{BLANK_1}}.

Data Structures Theory

The topmost node of a binary tree is called the [1].

Drag options to blanks, or click blank then click option'

Asibling

Broot

Cchild

Dleaf

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing root with leaf node.

Thinking root is a child node.

The root is the topmost node of a binary tree from which all other nodes descend.

3fill in blank

hard

Fix the error in the sentence: A node's {{BLANK_1}} is the node directly above it in the tree.

Data Structures Theory

A node's [1] is the node directly above it in the tree.

Drag options to blanks, or click blank then click option'

Aleaf

Bsibling

Cchild

Dparent

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing parent with child or sibling.

Using leaf instead of parent.

The node directly above a given node is called its parent.

4fill in blank

hard

Fill both blanks to complete the definition: Nodes that share the same {{BLANK_1}} are called {{BLANK_2}}.

Data Structures Theory

Nodes that share the same [1] are called [2].

Drag options to blanks, or click blank then click option'

Aparent

Bchildren

Csiblings

Dancestors

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing siblings with children or ancestors.

Mixing up parent and children.

Nodes that share the same parent are called siblings.

5fill in blank

hard

Fill all three blanks to complete the sentence: The {{BLANK_1}} of a node is the number of edges from the node to the {{BLANK_2}}, and the {{BLANK_3}} is the number of edges on the longest path from the node to a leaf.

Data Structures Theory

The [1] of a node is the number of edges from the node to the [2], and the [3] is the number of edges on the longest path from the node to a leaf.

Drag options to blanks, or click blank then click option'

Adepth

Broot

Cheight

Dleaf

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up depth and height definitions.

Confusing root with leaf in depth definition.

The depth of a node is the number of edges from the node to the root. The height is the number of edges on the longest path from the node to a leaf.