Count Words with Given Prefix in DSA Typescript - Execution Trace

Concept Flow - Count Words with Given Prefix

Start with empty Trie

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Insert each word

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For each character in word

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Create node if missing

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Increment prefix count

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After all words inserted

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Search prefix

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Traverse nodes for prefix chars

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If prefix node found

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Return count stored at prefix node

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Else return 0

Build a Trie by inserting words, counting prefixes at each node. Then traverse prefix nodes to get count.

Execution Sample

DSA Typescript

class TrieNode {
  children: Map<string, TrieNode> = new Map();
  count: number = 0;
}

// Insert words and count prefixes
// Query prefix count

Insert words into Trie, increment counts for prefixes, then query prefix count.

Execution Table

Step	Operation	Word/Prefix	Node Created	Prefix Count Updated	Visual State
1	Insert	"apple"	a, p, p, l, e nodes created	a:1, p:1, p:1, l:1, e:1	root -> a(1) -> p(1) -> p(1) -> l(1) -> e(1)
2	Insert	"app"	No new nodes	a:2, p:2, p:2	root -> a(2) -> p(2) -> p(2) -> l(1) -> e(1)
3	Insert	"ape"	e node created under p	a:3, p:3, e:1	root -> a(3) -> p(3) -> p(2) -> l(1) -> e(1) -> e(1)
4	Query	"ap"	No	No	Count at node 'p' after 'a' is 3
5	Query	"app"	No	No	Count at node 'p' after 'ap' is 2
6	Query	"apple"	No	No	Count at node 'e' after 'appl' is 1
7	Query	"bat"	No	No	Prefix not found, return 0

💡 All words inserted and prefix queries completed.

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	After Step 5	After Step 6	After Step 7
Trie Root	empty	a node with count 1	a node with count 2	a node with count 3	unchanged	unchanged	unchanged	unchanged
Node 'a' count	0	1	2	3	3	3	3	3
Node 'p' count (first p)	0	1	2	3	3	3	3	3
Node 'p' count (second p)	0	1	2	2	2	2	2	2
Node 'l' count	0	1	1	1	1	1	1	1
Node 'e' count (under l)	0	1	1	1	1	1	1	1
Node 'e' count (under p)	0	0	0	1	1	1	1	1

Key Moments - 3 Insights

Why do we increment the count at each node when inserting a word?

Because each node represents a prefix. Incrementing count tracks how many words share that prefix, as shown in steps 1-3 in the execution_table.

What happens if the prefix does not exist in the Trie during query?

We return 0 immediately because no words start with that prefix, as shown in step 7 where 'bat' is not found.

Why do some nodes get created and others don't during insertion?

Nodes are created only if the character path does not exist yet. For example, in step 2 inserting 'app' no new nodes are created because 'a' and 'p' nodes already exist.

Visual Quiz - 3 Questions

Look at the execution_table at step 3. What is the prefix count at node 'a' after inserting "ape"?

A 3

B 2

C 1

D 0

💡 Hint

Check the 'Prefix Count Updated' column at step 3 for node 'a'.

At which step does the prefix count at the second 'p' node become 2?

A Step 1

B Step 2

C Step 3

D Step 4

💡 Hint

Look at the variable_tracker row for 'Node p count (second p)' after each step.

If we query prefix "appl", what would be the count returned based on the execution_table?

A 3

B 2

C 1

D 0

💡 Hint

Check the count at node 'l' after 'app' in the visual state and prefix counts.

Concept Snapshot

Count Words with Given Prefix using Trie:
- Insert words char by char
- Create nodes if missing
- Increment count at each node for prefix tracking
- Query prefix by traversing nodes
- Return count at last prefix node or 0 if missing

Full Transcript

We build a Trie data structure to count how many words start with a given prefix. Each node in the Trie represents a character and stores how many words pass through it as a prefix. When inserting words like 'apple', 'app', and 'ape', we create nodes for characters if they don't exist and increment counts at each node. For example, after inserting 'apple', the nodes for 'a', 'p', 'p', 'l', 'e' each have count 1. Inserting 'app' increments counts on 'a', 'p', 'p' to 2. Inserting 'ape' increments counts on 'a', 'p', and creates a new 'e' node under 'p'. When querying a prefix like 'ap', we traverse nodes for 'a' and 'p' and return the count stored at 'p', which is 3, meaning 3 words start with 'ap'. If the prefix is not found, like 'bat', we return 0. This method efficiently counts words sharing prefixes by storing counts during insertion.