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DSA Javascriptprogramming~30 mins

Word Search in Grid Using Backtracking in DSA Javascript - Build from Scratch

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Word Search in Grid Using Backtracking
📖 Scenario: You are building a simple word search puzzle solver. You have a grid of letters and want to check if a given word can be found by moving horizontally or vertically from one letter to the next.This is like searching for a hidden word in a crossword puzzle where you can move up, down, left, or right but cannot reuse the same letter cell twice.
🎯 Goal: Build a program that checks if a given word exists in the letter grid using backtracking.You will create the grid, set the word to search, write the backtracking search logic, and finally print whether the word is found or not.
📋 What You'll Learn
Create a 2D array called board with the exact letters given.
Create a string variable called word with the exact value given.
Write a function called exist that uses backtracking to find the word in the board.
Print true if the word is found, otherwise false.
💡 Why This Matters
🌍 Real World
Word search puzzles and games use similar logic to find words hidden in grids. This technique is also useful in pattern matching and pathfinding problems.
💼 Career
Backtracking is a common algorithm technique used in interviews and real-world problems like puzzle solving, constraint satisfaction, and exploring decision trees.
Progress0 / 4 steps
1
Create the letter grid
Create a 2D array called board with these exact rows: ['A', 'B', 'C', 'E'], ['S', 'F', 'C', 'S'], ['A', 'D', 'E', 'E'].
DSA Javascript
Hint

Use square brackets to create arrays inside an array for rows.

2
Set the word to search
Create a string variable called word and set it to 'ABCCED'.
DSA Javascript
Hint

Use const word = 'ABCCED'; to create the word variable.

3
Write the backtracking search function
Write a function called exist that takes board and word as parameters and returns true if the word exists in the board by moving horizontally or vertically without reusing cells. Use backtracking with a helper function dfs inside exist.
DSA Javascript
Hint

Use a helper function dfs inside exist to explore neighbors recursively.

4
Print if the word exists in the board
Write a line to print the result of calling exist(board, word).
DSA Javascript
Hint

Use console.log(exist(board, word)); to print the result.

Practice

(1/5)
1. What is the main purpose of using backtracking in a word search grid problem?
easy
A. To sort the grid alphabetically
B. To count the number of words in the grid
C. To explore all possible paths to find the word
D. To replace characters in the grid

Solution

  1. Step 1: Understand backtracking in word search

    Backtracking tries all possible paths in the grid to find the target word by exploring neighbors recursively.
  2. Step 2: Eliminate other options

    Sorting, counting words, or replacing characters are not related to backtracking's purpose in this problem.
  3. Final Answer:

    To explore all possible paths to find the word -> Option C
  4. Quick Check:

    Backtracking = Explore paths [OK]
Hint: Backtracking means trying all paths step-by-step [OK]
Common Mistakes:
  • Thinking backtracking sorts or modifies the grid
  • Confusing backtracking with simple searching
  • Assuming backtracking counts words directly
2. Which of the following is the correct way to check if a position (row, col) is inside the grid boundaries in JavaScript?
easy
A. if (row > 0 && row <= grid.length && col > 0 && col <= grid[0].length)
B. if (row >= 0 && row < grid.length && col >= 0 && col < grid[0].length)
C. if (row >= 0 && row <= grid.length && col >= 0 && col <= grid[0].length)
D. if (row > 0 && row < grid.length && col > 0 && col < grid[0].length)

Solution

  1. Step 1: Understand grid indexing

    Grid rows and columns start at 0 and go up to length - 1, so valid indices satisfy 0 <= row < length.
  2. Step 2: Check each option

    if (row >= 0 && row < grid.length && col >= 0 && col < grid[0].length) correctly uses >= 0 and < length. Others use > 0 or <= length, which are incorrect for zero-based indexing.
  3. Final Answer:

    if (row >= 0 && row < grid.length && col >= 0 && col < grid[0].length) -> Option B
  4. Quick Check:

    Check boundaries with >=0 and < length [OK]
Hint: Use zero-based indexing: start at 0, less than length [OK]
Common Mistakes:
  • Using > 0 excludes first row/column
  • Using <= length allows out-of-bound index
  • Confusing inclusive and exclusive bounds
3. What will be the output of the following code snippet when searching for the word "CAT" in the given grid?
const grid = [
  ['C', 'A', 'T'],
  ['A', 'T', 'C'],
  ['T', 'C', 'A']
];

function exist(board, word) {
  const rows = board.length;
  const cols = board[0].length;
  const visited = Array.from({ length: rows }, () => Array(cols).fill(false));

  function backtrack(r, c, index) {
    if (index === word.length) return true;
    if (r < 0 || c < 0 || r >= rows || c >= cols) return false;
    if (visited[r][c] || board[r][c] !== word[index]) return false;

    visited[r][c] = true;
    const res = backtrack(r + 1, c, index + 1) || backtrack(r - 1, c, index + 1) || backtrack(r, c + 1, index + 1) || backtrack(r, c - 1, index + 1);
    visited[r][c] = false;
    return res;
  }

  for (let i = 0; i < rows; i++) {
    for (let j = 0; j < cols; j++) {
      if (backtrack(i, j, 0)) return true;
    }
  }
  return false;
}

console.log(exist(grid, "CAT"));
medium
A. true
B. false
C. SyntaxError
D. undefined

Solution

  1. Step 1: Trace the backtracking search for "CAT"

    The word "CAT" can be found starting at grid[0][0] = 'C', then right to 'A', then right to 'T'. The function returns true.
  2. Step 2: Confirm no errors and correct return

    The code correctly marks visited cells and explores neighbors. It returns true when the word is found.
  3. Final Answer:

    true -> Option A
  4. Quick Check:

    Word "CAT" found in grid = true [OK]
Hint: Check neighbors recursively for each letter [OK]
Common Mistakes:
  • Ignoring visited array causing infinite loops
  • Not checking all directions
  • Assuming word must be in a straight line only
4. Identify the bug in the following backtracking function for word search and select the fix.
function backtrack(r, c, index) {
  if (index === word.length) return true;
  if (r < 0 || c < 0 || r >= rows || c >= cols) return false;
  if (board[r][c] !== word[index]) return false;

  visited[r][c] = true;
  const res = backtrack(r + 1, c, index + 1) || backtrack(r - 1, c, index + 1) || backtrack(r, c + 1, index + 1) || backtrack(r, c - 1, index + 1);
  return res;
}
medium
A. Change the base case to index > word.length
B. Remove the boundary checks for r and c
C. Remove the visited array usage completely
D. Add visited[r][c] = false after recursive calls to unmark

Solution

  1. Step 1: Identify missing backtracking step

    The function marks visited[r][c] = true but never resets it to false after recursion, causing wrong results.
  2. Step 2: Fix by unmarking visited after recursion

    Adding visited[r][c] = false after recursive calls allows other paths to use this cell again.
  3. Final Answer:

    Add visited[r][c] = false after recursive calls to unmark -> Option D
  4. Quick Check:

    Unmark visited after recursion to backtrack [OK]
Hint: Always reset visited after recursion to explore other paths [OK]
Common Mistakes:
  • Forgetting to unmark visited cells
  • Removing boundary checks causing errors
  • Changing base case incorrectly
5. Given a grid and a list of words, how would you efficiently find all words present in the grid using backtracking? Choose the best approach.
hard
A. Use a Trie (prefix tree) to reduce repeated searches and backtrack once
B. Run backtracking separately for each word on the entire grid
C. Sort the words and grid alphabetically before searching
D. Replace all grid letters with the first letter of each word before searching

Solution

  1. Step 1: Understand inefficiency of separate searches

    Running backtracking for each word separately repeats many searches, wasting time.
  2. Step 2: Use Trie to optimize search

    Building a Trie of all words allows backtracking once, pruning paths that don't match any prefix, improving efficiency.
  3. Final Answer:

    Use a Trie (prefix tree) to reduce repeated searches and backtrack once -> Option A
  4. Quick Check:

    Trie + backtracking = efficient multi-word search [OK]
Hint: Use Trie to share prefixes and avoid repeated searches [OK]
Common Mistakes:
  • Searching each word independently causing slow performance
  • Sorting grid or words doesn't help search
  • Modifying grid letters breaks correctness
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10 questions~5 mineasy hard