Trie vs Hash Map for Prefix Matching in DSA C++ - Interactive Comparison Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to insert a word into the Trie.

DSA C++

void insert(string word) {
    TrieNode* node = root;
    for (char c : word) {
        if (!node->children.count(c)) {
            node->children[c] = new TrieNode();
        }
        node = node->[1];
    }
    node->isEnd = true;
}

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

Achildren[c]

Bchild[c]

Cchildren.get(c)

Dchild.get(c)

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'child' instead of 'children'.

Trying to call get() which is not a C++ map method.

In a Trie, each node has a map called 'children' that stores the next nodes for each character. We access the child node for character c using children[c].

2fill in blank

medium

Complete the code to check if a prefix exists in the Trie.

DSA C++

bool startsWith(string prefix) {
    TrieNode* node = root;
    for (char c : prefix) {
        if (!node->children.count(c)) {
            return false;
        }
        node = node->[1];
    }
    return true;
}

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

Achildren.get(c)

Bchild[c]

Cchild.get(c)

Dchildren[c]

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong map name 'child'.

Trying to use get() method which is not valid in C++ map.

To check if a prefix exists, we move down the Trie nodes using children[c] for each character c in the prefix.

3fill in blank

hard

Fix the error in the Hash Map prefix search function.

DSA C++

bool hasPrefix(unordered_map<string, bool>& map, string prefix) {
    for (auto& pair : map) {
        if (pair.first.[1](0, prefix.size()) == prefix) {
            return true;
        }
    }
    return false;
}

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

Asubstr

Bsubstring

Cslice

Dsub

Attempts:

3 left

💡 Hint

Common Mistakes

Using substring() which is a JavaScript or Java method.

Using slice() which is not a C++ string method.

In C++, the method to get a substring is substr(start_index, length). substring() or slice() are not valid methods.

4fill in blank

hard

Fill both blanks to create a Trie search function that returns true if a word exists.

DSA C++

bool search(string word) {
    TrieNode* node = root;
    for (char c : word) {
        if (!node->[1].count(c)) {
            return false;
        }
        node = node->[2];
    }
    return node->isEnd;
}

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

Achildren

Bchild

Cchildren[c]

Dchild[c]

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'child' instead of 'children'.

Trying to access child node without indexing by c.

We check if the current node's children map contains the character c using children.count(c). Then we move to the child node using children[c].

5fill in blank

hard

Fill all three blanks to build a Hash Map prefix search that returns true if any key starts with the prefix.

DSA C++

bool hasPrefix(unordered_map<string, bool>& map, string prefix) {
    for (auto& [1] : map) {
        if ([1].first.[2](0, prefix.size()) == prefix) {
            return [3];
        }
    }
    return false;
}

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

Apair

Bsubstr

Ctrue

Dkey

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'key' as loop variable which is not valid for map iteration.

Using substring or slice instead of substr.

Returning false instead of true when prefix matches.

We iterate over the map with 'pair'. Use substr to get the prefix of the key string. Return true if prefix matches.

Practice

1. Which data structure is generally more efficient for checking if a prefix exists in a large set of strings?

easy

A. Linked List, because it stores elements in order

B. Hash Map, because it stores keys with constant time lookup

C. Array, because it allows sequential search of prefixes

D. Trie, because it stores prefixes explicitly and allows fast prefix search

Solution

1. Step 1: Understand prefix search requirements

   Prefix search needs to quickly find if any string starts with a given prefix.

2. Step 2: Compare Trie and Hash Map for prefix search

   Trie stores prefixes explicitly, allowing fast traversal to check prefixes. Hash Map stores full keys, so prefix search requires checking many keys or extra processing.

3. Final Answer:

   Trie, because it stores prefixes explicitly and allows fast prefix search -> Option D

4. Quick Check:

   Prefix search = Trie [OK]

Hint: Prefix search is fastest with Trie due to explicit prefix nodes [OK]

Common Mistakes:

• Thinking hash map can do prefix search in constant time
• Confusing prefix search with exact key search
• Ignoring the need to check multiple keys in hash map

2. Which of the following is the correct way to declare a Trie node in C++ for lowercase English letters?

easy

A. struct TrieNode { TrieNode* children[26]; bool isEnd; };

B. struct TrieNode { map children; bool isEnd; };

C. struct TrieNode { vector<int> children; bool isEnd; };

D. struct TrieNode { unordered_map children; bool isEnd; };

Solution

1. Step 1: Identify correct children type for fixed alphabet

   For lowercase English letters, fixed size array of 26 pointers is efficient.

2. Step 2: Check each option's children type

   struct TrieNode { TrieNode* children[26]; bool isEnd; }; uses TrieNode* children[26], which is correct. struct TrieNode { map children; bool isEnd; }; uses map, which is valid but slower. Options A and C use incorrect types.

3. Final Answer:

   struct TrieNode { TrieNode* children[26]; bool isEnd; }; -> Option A

4. Quick Check:

   Fixed alphabet Trie node = array of 26 pointers [OK]

Hint: Use array of 26 pointers for fixed lowercase letters [OK]

Common Mistakes:

• Using vector<int> instead of pointers for children
• Using unordered_map with wrong key type
• Confusing map with array for fixed alphabets

3. What will be the output of the following C++ code snippet?

struct TrieNode {
  TrieNode* children[26] = {nullptr};
  bool isEnd = false;
};

TrieNode* root = new TrieNode();

// Insert "cat"
string word = "cat";
TrieNode* node = root;
for (char c : word) {
  int index = c - 'a';
  if (!node->children[index])
    node->children[index] = new TrieNode();
  node = node->children[index];
}
node->isEnd = true;

// Check prefix "ca"
node = root;
string prefix = "ca";
bool found = true;
for (char c : prefix) {
  int index = c - 'a';
  if (!node->children[index]) {
    found = false;
    break;
  }
  node = node->children[index];
}
cout << (found ? "Prefix exists" : "Prefix not found") << endl;

medium

A. Prefix exists

B. Prefix not found

C. Compilation error

D. Runtime error

Solution

1. Step 1: Insert "cat" into Trie

   Each character 'c', 'a', 't' creates nodes if missing. After insertion, path for "cat" exists.

2. Step 2: Check prefix "ca"

   Traverse nodes for 'c' and 'a'. Both nodes exist, so prefix is found.

3. Final Answer:

   Prefix exists -> Option A

4. Quick Check:

   Inserted "cat" contains prefix "ca" [OK]

Hint: Traverse nodes for prefix; if all exist, prefix exists [OK]

Common Mistakes:

• Assuming prefix must be a full word
• Forgetting to check each character node
• Confusing isEnd with prefix existence

4. Identify the bug in this C++ Trie prefix search code snippet:

bool startsWith(TrieNode* root, const string& prefix) {
  TrieNode* node = root;
  for (char c : prefix) {
    int idx = c - 'a';
    if (node->children[idx] == nullptr)
      return false;
    node = node->children[idx];
  }
  return node->isEnd;
}

medium

A. Index calculation is wrong, should be c - 'A'

B. Should return true after loop, not node->isEnd

C. Missing null check for root pointer

D. Loop should iterate over root->children, not prefix

Solution

1. Step 1: Understand prefix search logic

   Prefix search should return true if all prefix nodes exist, regardless of isEnd.

2. Step 2: Identify incorrect return statement

   Returning node->isEnd checks if prefix is a full word, not just a prefix. It should return true after loop.

3. Final Answer:

   Should return true after loop, not node->isEnd -> Option B

4. Quick Check:

   Prefix search returns true if prefix nodes exist [OK]

Hint: Prefix search returns true if path exists, ignore isEnd [OK]

Common Mistakes:

• Confusing prefix existence with full word existence
• Incorrect index calculation for characters
• Not checking for null root pointer

5. You need to implement a system that supports fast prefix matching for millions of strings with dynamic insertions and lookups. Which approach is best and why? Option A: Use a sorted array of strings and binary search for prefixes. Option B: Use a Hash Map storing all strings and check prefixes by scanning keys. Option C: Use a Trie for prefix matching. Option D: Use a linked list of strings and linear search for prefixes.

hard

A. Sorted array, because binary search is fast for prefix queries

B. Hash Map, because it has constant time lookup for exact keys

C. Trie, because it provides efficient prefix search and dynamic insertions

D. Linked list, because it is simple to implement

Solution

1. Step 1: Analyze requirements for millions of strings with dynamic insertions

   Dynamic insertions require efficient updates; prefix matching needs fast queries.

2. Step 2: Compare data structures for prefix matching and insertions

   Trie supports fast prefix search and efficient insertions. Hash Map is fast for exact keys but slow for prefix. Sorted array requires costly insertions. Linked list is slow for both.

3. Final Answer:

   Trie, because it provides efficient prefix search and dynamic insertions -> Option C

4. Quick Check:

   Dynamic prefix search = Trie [OK]

Hint: For dynamic prefix search, Trie beats hash map and arrays [OK]

Common Mistakes:

• Choosing hash map for prefix search without scanning keys
• Ignoring insertion cost in sorted arrays
• Underestimating linked list search time