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DSA Goprogramming~3 mins

Why Word Break Problem in DSA Go?

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The Big Idea

What if you could instantly find hidden words in a jumble of letters without guessing?

The Scenario

Imagine you have a long sentence without spaces, like a secret code, and you want to find out if it can be split into real words from a dictionary.

The Problem

Trying every possible way to split the sentence by hand is slow and confusing. You might miss some splits or repeat the same checks many times, making it very tiring and error-prone.

The Solution

The Word Break Problem uses a smart way to check if the sentence can be split into dictionary words by remembering past results. This saves time and avoids repeated work.

Before vs After
✗ Before
func canSplitManually(s string, dict []string) bool {
    // Try all splits manually, very slow
    for i := 1; i < len(s); i++ {
        left := s[:i]
        right := s[i:]
        // Check if left and right are in dict
    }
    return false
}
✓ After
func wordBreak(s string, dict map[string]bool) bool {
    dp := make([]bool, len(s)+1)
    dp[0] = true
    for i := 1; i <= len(s); i++ {
        for j := 0; j < i; j++ {
            if dp[j] && dict[s[j:i]] {
                dp[i] = true
                break
            }
        }
    }
    return dp[len(s)]
}
What It Enables

This concept lets us quickly decide if a long string can be split into valid words, enabling fast text processing and language understanding.

Real Life Example

When you type without spaces on your phone, the system can guess where to put spaces to form real words, making typing easier and faster.

Key Takeaways

Manual splitting is slow and repeats work.

Word Break uses memory to avoid repeated checks.

It helps in fast text and language processing.

Practice

(1/5)
1. What does the Word Break Problem ask you to determine about a given string s and a dictionary of words wordDict?
easy
A. If s can be segmented into a space-separated sequence of one or more dictionary words
B. If s contains any substring from wordDict
C. If s is exactly equal to any word in wordDict
D. If s can be reversed to form a word in wordDict

Solution

  1. Step 1: Understand the problem statement

    The Word Break Problem asks if the entire string s can be split into valid words from the dictionary without leftover characters.
  2. Step 2: Differentiate from similar concepts

    It is not enough for s to contain a substring or be equal to a dictionary word; the whole string must be fully segmented.
  3. Final Answer:

    If s can be segmented into a sequence of dictionary words -> Option A
  4. Quick Check:

    Word Break = Full segmentation check [OK]
Hint: Check if full string splits into dictionary words [OK]
Common Mistakes:
  • Thinking partial substring match is enough
  • Confusing equality with segmentation
  • Ignoring leftover characters after segmentation
2. Which of the following Go function signatures correctly represents a function to solve the Word Break Problem?
easy
A. func wordBreak(wordDict []string, s string) string
B. func wordBreak(s string, wordDict []string) bool
C. func wordBreak(s []string, wordDict string) int
D. func wordBreak(s string, wordDict map[string]int) []string

Solution

  1. Step 1: Identify correct parameter types

    The input string s should be a string, and the dictionary wordDict should be a slice of strings.
  2. Step 2: Identify correct return type

    The function returns a boolean indicating if segmentation is possible.
  3. Final Answer:

    func wordBreak(s string, wordDict []string) bool -> Option B
  4. Quick Check:

    Input: string + []string, Output: bool [OK]
Hint: Input string and word list, output bool [OK]
Common Mistakes:
  • Swapping parameter types
  • Returning wrong data type
  • Using map instead of slice without reason
3. What is the output of the following Go code snippet?
func main() {
    s := "leetcode"
    wordDict := []string{"leet", "code"}
    fmt.Println(wordBreak(s, wordDict))
}

func wordBreak(s string, wordDict []string) bool {
    dp := make([]bool, len(s)+1)
    dp[0] = true
    for i := 1; i <= len(s); i++ {
        for j := 0; j < i; j++ {
            if dp[j] && contains(wordDict, s[j:i]) {
                dp[i] = true
                break
            }
        }
    }
    return dp[len(s)]
}

func contains(dict []string, word string) bool {
    for _, w := range dict {
        if w == word {
            return true
        }
    }
    return false
}
medium
A. true
B. false
C. Compilation error
D. Runtime panic

Solution

  1. Step 1: Understand the dynamic programming approach

    The code uses a boolean slice dp where dp[i] is true if s[:i] can be segmented into dictionary words.
  2. Step 2: Trace the example string "leetcode"

    "leet" and "code" are in the dictionary, so dp[len(s)] becomes true.
  3. Final Answer:

    true -> Option A
  4. Quick Check:

    DP segmentation = true [OK]
Hint: Check dp array for full string length [OK]
Common Mistakes:
  • Forgetting to break inner loop after true
  • Incorrect substring slicing
  • Not initializing dp[0] to true
4. Identify the bug in this Go code for the Word Break Problem:
func wordBreak(s string, wordDict []string) bool {
    dp := make([]bool, len(s))
    dp[0] = true
    for i := 1; i <= len(s); i++ {
        for j := 0; j < i; j++ {
            if dp[j] && contains(wordDict, s[j:i]) {
                dp[i] = true
                break
            }
        }
    }
    return dp[len(s)]
}
medium
A. contains function is missing
B. dp slice length is correct but dp[0] should be false
C. dp slice length should be len(s)+1 and dp[0] initialization is correct
D. Loop indices i and j are reversed

Solution

  1. Step 1: Check dp slice size and initialization

    The dp slice must be of size len(s)+1 to include empty substring at index 0, and dp[0] should be true.
  2. Step 2: Verify loop bounds and dp usage

    Loops use indices up to len(s), so dp must have length len(s)+1 to avoid index out of range.
  3. Final Answer:

    dp slice length should be len(s)+1 and dp[0] initialization is correct -> Option C
  4. Quick Check:

    dp size = len(s)+1 [OK]
Hint: dp length = string length + 1 [OK]
Common Mistakes:
  • Using dp length as len(s) causes index errors
  • Not initializing dp[0] to true
  • Incorrect loop ranges causing panic
5. Given the string s = "applepenapple" and dictionary wordDict = ["apple", "pen"], which of the following modifications to the Word Break algorithm will correctly handle repeated words without extra space complexity?
hard
A. Replace dp array with a single boolean variable updated each iteration
B. Use a queue to store all possible segmentations and check each fully
C. Sort the dictionary and use binary search for substring checks
D. Use a memoization map to store results of substring checks to avoid recomputation

Solution

  1. Step 1: Understand repeated word handling

    Repeated words cause repeated substring checks; memoization stores results to avoid recomputation.
  2. Step 2: Analyze options for efficiency

    Memoization reduces time without increasing space beyond needed; queue or sorting do not directly optimize repeated checks; single boolean loses needed state.
  3. Final Answer:

    Use a memoization map to store results of substring checks to avoid recomputation -> Option D
  4. Quick Check:

    Memoization = efficient repeated checks [OK]
Hint: Memoize substring results to avoid repeated work [OK]
Common Mistakes:
  • Ignoring repeated substring computations
  • Using single boolean loses segmentation info
  • Assuming sorting dictionary helps substring checks
Recommended

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