Autocomplete System with Trie in DSA Go - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a new Trie node.

DSA Go

func NewTrieNode() *TrieNode {
    return &TrieNode{
        children: make(map[rune]*TrieNode),
        isEnd:    [1],
    }
}

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

A0

Btrue

Cnil

Dfalse

Attempts:

3 left

💡 Hint

Common Mistakes

Setting isEnd to true for new nodes

Using nil instead of a boolean value

The new Trie node should start with isEnd set to false because it does not represent the end of a word yet.

2fill in blank

medium

Complete the code to insert a word into the Trie.

DSA Go

func (t *Trie) Insert(word string) {
    node := t.root
    for _, ch := range word {
        if node.children[ch] == nil {
            node.children[ch] = NewTrieNode()
        }
        node = node.children[[1]]
    }
    node.isEnd = true
}

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

Ach

Bword

Cnode

Dt

Attempts:

3 left

💡 Hint

Common Mistakes

Using the whole word instead of the character

Using the node variable instead of the character

We move to the child node corresponding to the current character ch in the word.

3fill in blank

hard

Fix the error in the search function to check if a word exists in the Trie.

DSA Go

func (t *Trie) Search(word string) bool {
    node := t.root
    for _, ch := range word {
        if node.children[ch] == nil {
            return false
        }
        node = node.children[ch]
    }
    return node.[1]
}

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

Achildren

Broot

CisEnd

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Returning children instead of isEnd

Returning root or word which are not boolean flags

After traversing all characters, we return isEnd to confirm the word ends here.

4fill in blank

hard

Fill both blanks to collect all words starting with a prefix using DFS.

DSA Go

func (t *Trie) collectWords(node *TrieNode, prefix string, results *[]string) {
    if node.[1] {
        *results = append(*results, prefix)
    }
    for ch, child := range node.[2] {
        t.collectWords(child, prefix+string(ch), results)
    }
}

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

AisEnd

Broot

Cchildren

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using root instead of children for traversal

Checking children instead of isEnd for word completion

Check isEnd to add words, and loop over children to explore next nodes.

5fill in blank

hard

Fill all three blanks to implement the Autocomplete function returning all words with a prefix.

DSA Go

func (t *Trie) Autocomplete(prefix string) []string {
    node := t.root
    for _, ch := range prefix {
        if node.children[[1]] == nil {
            return []string{}
        }
        node = node.children[ch]
    }
    results := []string{}
    t.collectWords(node, [2], &results)
    return [3]
}

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

Ach

Bprefix

Cresults

Dnode

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong variable to check children

Passing wrong string to collectWords

Returning node instead of results

Use ch to check children, pass prefix to collectWords, and return results array.

Practice

1. What is the main purpose of using a Trie in an autocomplete system?

easy

A. To encrypt the stored words

B. To sort words alphabetically

C. To efficiently store and search prefixes of words

D. To count the total number of words

Solution

1. Step 1: Understand the role of Trie in prefix search

   A Trie is a tree-like data structure that stores characters of words in a way that common prefixes share nodes.

2. Step 2: Connect Trie usage to autocomplete

   Autocomplete requires quick lookup of words starting with a given prefix, which Trie supports efficiently.

3. Final Answer:

   To efficiently store and search prefixes of words -> Option C

4. Quick Check:

   Trie = prefix search [OK]

Hint: Trie stores prefixes for fast autocomplete lookup [OK]

Common Mistakes:

• Thinking Trie sorts words alphabetically
• Confusing Trie with encryption methods
• Assuming Trie counts total words only

2. Which of the following is the correct way to declare a Trie node struct in Go?

easy

A. type TrieNode struct { children []int; isEnd int }

B. type TrieNode struct { children map[rune]*TrieNode; isEnd bool }

C. type TrieNode struct { children map[string]int; isEnd string }

D. type TrieNode struct { children []string; isEnd bool }

Solution

1. Step 1: Identify correct data types for TrieNode fields

   Children should map characters (rune) to child nodes (pointer to TrieNode). isEnd should be a boolean indicating word end.

2. Step 2: Match with given options

   type TrieNode struct { children map[rune]*TrieNode; isEnd bool } uses map[rune]*TrieNode and bool for isEnd, which is correct for Trie implementation in Go.

3. Final Answer:

   type TrieNode struct { children map[rune]*TrieNode; isEnd bool } -> Option B

4. Quick Check:

   Children map[rune]*TrieNode and bool isEnd [OK]

Hint: Children map keys are runes, values are pointers to TrieNode [OK]

Common Mistakes:

• Using slices instead of maps for children
• Using incorrect types like int or string for isEnd
• Mapping children with wrong key or value types

3. What will be the output of the following Go code snippet that inserts words into a Trie and searches for prefix "app"?

trie := NewTrie()
trie.Insert("apple")
trie.Insert("app")
trie.Insert("application")
results := trie.SearchPrefix("app")
fmt.Println(results)

Assuming SearchPrefix returns all words starting with the prefix.

medium

A. []

B. ["apple", "application"]

C. ["app"]

D. ["app", "apple", "application"]

Solution

1. Step 1: Insert words into Trie

   Words "apple", "app", and "application" are inserted, all sharing prefix "app".

2. Step 2: Search for prefix "app"

   SearchPrefix returns all words starting with "app", so it returns all three inserted words.

3. Final Answer:

   ["app", "apple", "application"] -> Option D

4. Quick Check:

   All words with prefix "app" returned [OK]

Hint: SearchPrefix returns all words starting with given prefix [OK]

Common Mistakes:

• Returning only exact prefix word
• Missing some words sharing prefix
• Returning empty list incorrectly

4. Identify the bug in this Go code snippet for inserting a word into a Trie:

func (t *Trie) Insert(word string) {
    node := t.root
    for _, ch := range word {
        if node.children[ch] == nil {
            node.children[ch] = &TrieNode{}
        }
        node = node.children[ch]
    }
    node.isEnd = false
}

medium

A. isEnd should be set to true after insertion

B. children map is not initialized

C. Loop variable ch should be int, not rune

D. Function should return a value

Solution

1. Step 1: Review isEnd assignment after insertion

   After inserting a word, isEnd should mark the node as end of a word, so it must be set to true.

2. Step 2: Check other parts of code

   children map initialization and loop variable type are correct; function does not need to return a value.

3. Final Answer:

   isEnd should be set to true after insertion -> Option A

4. Quick Check:

   isEnd = true after insert [OK]

Hint: Set isEnd true to mark word end [OK]

Common Mistakes:

• Setting isEnd to false instead of true
• Not initializing children map before use
• Expecting Insert to return a value

5. Given a Trie storing words, how can you modify the autocomplete system to return suggestions sorted by frequency of word usage?

hard

A. Store a frequency count at each end node and sort results by this count

B. Sort all words alphabetically before insertion

C. Use a separate array to store frequencies unrelated to Trie

D. Ignore frequency and return words in insertion order

Solution

1. Step 1: Add frequency tracking in Trie nodes

   Modify Trie nodes to store frequency count at nodes marking word ends to track usage.

2. Step 2: Sort autocomplete results by frequency

   When returning suggestions, sort collected words by their stored frequency counts to prioritize popular words.

3. Final Answer:

   Store a frequency count at each end node and sort results by this count -> Option A

4. Quick Check:

   Frequency count in Trie nodes enables sorted suggestions [OK]

Hint: Track frequency in nodes, sort suggestions by count [OK]

Common Mistakes:

• Sorting words before insertion does not help frequency
• Using unrelated arrays breaks Trie efficiency
• Ignoring frequency loses popular word priority