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DSA Goprogramming~5 mins

Word Search in Grid Using Backtracking in DSA Go - Cheat Sheet & Quick Revision

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Recall & Review
beginner
What is the main idea behind backtracking in word search problems?
Backtracking tries to build a solution step-by-step, exploring all possible paths and undoing steps (backtracking) when a path does not lead to a solution.
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beginner
In a word search grid, how do you decide the next cell to explore during backtracking?
You explore adjacent cells (up, down, left, right) that match the next character in the word and have not been visited yet.
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beginner
Why do we mark cells as visited during backtracking in word search?
To avoid revisiting the same cell in the current path, which prevents cycles and incorrect matches.
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beginner
What is the base case for the recursive backtracking function in word search?
When all characters of the word have been matched successfully, meaning the word is found in the grid.
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intermediate
How does backtracking ensure all possible paths are checked in the grid?
By recursively exploring each valid adjacent cell and backtracking when a path fails, it systematically checks all paths.
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Which directions are typically checked when searching for the next character in a word search grid?
ADiagonal directions only
BOnly Up and Down
CUp, Down, Left, Right
DRandom cells in the grid
What should you do if the current cell does not match the expected character in the word?
ABacktrack and try another path
BContinue searching from the same cell
CMark the cell as visited and move on
DStop the entire search
Why is it important to mark cells as visited during the search?
ATo avoid revisiting the same cell in the current path
BTo speed up the search by skipping cells
CTo count how many times a cell is used
DTo permanently remove the cell from the grid
What happens when the entire word is matched in the grid?
AThe search marks the word as invalid
BThe search returns true indicating success
CThe search resets and starts over
DThe search continues to find more words
Which of these is NOT a characteristic of backtracking in word search?
AExplores all possible paths
BUses recursion to explore paths
CBacktracks when a path fails
DAlways moves forward without undoing steps
Explain how backtracking works to find a word in a grid.
Think about trying paths step-by-step and undoing when stuck.
You got /6 concepts.
    Describe why marking cells as visited is important in word search backtracking.
    Imagine walking in a maze without stepping on the same spot twice.
    You got /4 concepts.

      Practice

      (1/5)
      1. What is the main purpose of using backtracking in a word search grid problem?
      easy
      A. To count the number of words in the grid
      B. To sort the grid alphabetically
      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, or replacing characters are unrelated to the search process using backtracking.
      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 until word found [OK]
      Common Mistakes:
      • Thinking backtracking sorts or modifies the grid
      • Confusing backtracking with simple iteration
      • 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 in Go?
      easy
      A. if row > 0 && row <= len(grid) && col > 0 && col <= len(grid[0])
      B. if row > 0 && row < len(grid) && col > 0 && col < len(grid[0])
      C. if row >= 0 && row <= len(grid) && col >= 0 && col <= len(grid[0])
      D. if row >= 0 && row < len(grid) && col >= 0 && col < len(grid[0])

      Solution

      1. Step 1: Understand grid indexing in Go

        Grid indices start at 0 and go up to length-1, so valid indices satisfy 0 <= row < len(grid) and 0 <= col < len(grid[0]).
      2. Step 2: Check each option

        if row >= 0 && row < len(grid) && col >= 0 && col < len(grid[0]) correctly uses >= 0 and < length. Options A, C, D use incorrect bounds like > 0 or <= length which are off by one.
      3. Final Answer:

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

        Index check = if row >= 0 && row < len(grid) && col >= 0 && col < len(grid[0]) [OK]
      Hint: Use zero-based indexing with < length for bounds [OK]
      Common Mistakes:
      • Using > 0 instead of >= 0 excludes first row/column
      • Using <= length allows out-of-range index
      • Confusing row and column lengths
      3. What will be the output of the following Go code snippet for word search?
      grid := [][]byte{{'A','B','C','E'},{'S','F','C','S'},{'A','D','E','E'}}
      word := "ABCCED"
      found := exist(grid, word)
      fmt.Println(found)
      
      func exist(board [][]byte, word string) bool {
          for i := 0; i < len(board); i++ {
              for j := 0; j < len(board[0]); j++ {
                  if backtrack(board, word, i, j, 0) {
                      return true
                  }
              }
          }
          return false
      }
      
      func backtrack(board [][]byte, word string, row, col, index int) bool {
          if index == len(word) {
              return true
          }
          if row < 0 || row >= len(board) || col < 0 || col >= len(board[0]) || board[row][col] != word[index] {
              return false
          }
          temp := board[row][col]
          board[row][col] = '#'
          found := backtrack(board, word, row+1, col, index+1) ||
                   backtrack(board, word, row-1, col, index+1) ||
                   backtrack(board, word, row, col+1, index+1) ||
                   backtrack(board, word, row, col-1, index+1)
          board[row][col] = temp
          return found
      }
      medium
      A. true
      B. false
      C. Compilation error
      D. Runtime panic

      Solution

      1. Step 1: Understand the grid and word

        The grid contains the letters to form the word "ABCCED" starting at (0,0) moving right and down.
      2. Step 2: Trace backtracking calls

        Backtracking explores neighbors and marks visited cells with '#'. The word "ABCCED" can be found following the path A->B->C->C->E->D.
      3. Final Answer:

        true -> Option A
      4. Quick Check:

        Word found = true [OK]
      Hint: Trace path letter by letter with backtracking [OK]
      Common Mistakes:
      • Not marking visited cells causing revisits
      • Incorrect boundary checks causing false negatives
      • Assuming word is not found without tracing path
      4. The following Go code for word search returns false even when the word exists. What is the bug?
      func backtrack(board [][]byte, word string, row, col, index int) bool {
          if index == len(word) {
              return true
          }
          if row < 0 || row >= len(board) || col < 0 || col >= len(board[0]) || board[row][col] != word[index] {
              return false
          }
          // Missing marking visited cell
          found := backtrack(board, word, row+1, col, index+1) ||
                   backtrack(board, word, row-1, col, index+1) ||
                   backtrack(board, word, row, col+1, index+1) ||
                   backtrack(board, word, row, col-1, index+1)
          return found
      }
      medium
      A. The function does not mark visited cells, causing revisits
      B. The base case is incorrect and should return false
      C. The boundary checks are missing
      D. The word parameter is not passed correctly

      Solution

      1. Step 1: Analyze the backtrack function

        The function checks boundaries and matches characters but does not mark visited cells, so it can revisit the same cell multiple times.
      2. Step 2: Understand the impact of missing visited marking

        Without marking visited cells, the search may loop or fail to find the word correctly because it revisits cells already used in the current path.
      3. Final Answer:

        The function does not mark visited cells, causing revisits -> Option A
      4. Quick Check:

        Missing visited marking = The function does not mark visited cells, causing revisits [OK]
      Hint: Always mark visited cells to avoid revisiting [OK]
      Common Mistakes:
      • Ignoring visited marking causes infinite loops
      • Misunderstanding base case logic
      • Assuming boundary checks fix revisits
      5. Given a grid and a list of words, how can you efficiently find all words present in the grid using backtracking? Choose the best approach.
      hard
      A. Run backtracking separately for each word on the entire grid
      B. Build a Trie of words and use backtracking with pruning to find all words
      C. Sort the grid and words alphabetically before searching
      D. Replace all grid letters with '#' and then search

      Solution

      1. Step 1: Understand the problem of multiple words

        Searching each word separately is inefficient because it repeats similar searches multiple times.
      2. Step 2: Use Trie with backtracking

        Building a Trie (prefix tree) of all words allows pruning paths early if no word matches, improving efficiency significantly.
      3. Step 3: Eliminate incorrect options

        Sorting or replacing letters does not help search. Running backtracking separately is slow.
      4. Final Answer:

        Build a Trie of words and use backtracking with pruning to find all words -> Option B
      5. Quick Check:

        Trie + backtracking = efficient multi-word search [OK]
      Hint: Use Trie to prune backtracking paths for multiple words [OK]
      Common Mistakes:
      • Searching each word independently wastes time
      • Ignoring Trie data structure benefits
      • Trying to sort grid which doesn't help search
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