Word Break Problem in DSA Python - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the Word Break Problem?

It is a problem where you check if a given string can be split into a sequence of one or more dictionary words.

beginner

What data structure is commonly used to store the dictionary words for the Word Break Problem?

A set is commonly used because it allows fast lookups to check if a substring is a valid word.

intermediate

How does dynamic programming help solve the Word Break Problem?

It stores results of smaller subproblems (whether substrings can be segmented) to avoid repeated work and build up the answer for the full string.

intermediate

What does the boolean array in the dynamic programming solution represent?

Each position in the array shows if the substring from the start up to that position can be segmented into dictionary words.

intermediate

Why do we check all possible prefixes of the string in the Word Break Problem?

To find if any prefix is a valid word and the remaining suffix can also be segmented, ensuring the whole string can be broken down correctly.

What is the main goal of the Word Break Problem?

A Check if a string can be segmented into dictionary words

B Find the longest word in a dictionary

C Count the number of words in a string

D Sort words in alphabetical order

The problem asks if the string can be split into valid dictionary words.

Which data structure is best for quick word lookups in the Word Break Problem?

A List

B Queue

C Set

D Stack

Sets provide fast membership checks, ideal for dictionary word lookups.

In dynamic programming for Word Break, what does dp[i] = True mean?

A Substring s[0:i] can be segmented into dictionary words

B Substring s[i:] is a dictionary word

C The whole string is a dictionary word

D No valid segmentation found

dp[i] being True means the substring from start to i can be broken into dictionary words.

Why do we check all prefixes in the Word Break Problem?

A To find the longest prefix

B To find if prefix is a word and suffix can be segmented

C To reverse the string

D To count vowels

Checking prefixes helps find valid splits where prefix is a word and suffix can also be segmented.

What is the time complexity of the dynamic programming solution for Word Break?

A O(n)

B O(1)

C O(n^3)

D O(n^2)

The solution checks all substrings, leading to O(n^2) time complexity.

Explain how dynamic programming solves the Word Break Problem step-by-step.

Think about how you remember if parts of the string can be split before checking the whole.

Describe why using a set for dictionary words improves the Word Break Problem solution.

Consider how quickly you can check if a word exists in a list versus a set.

Practice

1. What is the main goal of the Word Break Problem in algorithms?

easy

A. To check if a string can be segmented into a sequence of dictionary words

B. To find the longest word in a dictionary

C. To count the number of vowels in a string

D. To reverse the words in a sentence

Solution

1. Step 1: Understand the problem statement

   The Word Break Problem asks if a given string can be split into valid words from a dictionary.

2. Step 2: Match the goal with options

   To check if a string can be segmented into a sequence of dictionary words correctly describes this goal, while others describe unrelated tasks.

3. Final Answer:

   To check if a string can be segmented into a sequence of dictionary words -> Option A

4. Quick Check:

   Word Break Problem = Check segmentation [OK]

Hint: Remember: Word Break checks if string splits into dictionary words [OK]

Common Mistakes:

• Confusing Word Break with string reversal
• Thinking it counts vowels or finds longest word
• Assuming it modifies the string instead of checking segmentation

2. Which of the following is the correct Python syntax to check if a substring s[:i] is in a dictionary wordDict inside a loop?

easy

A. if s[:i] contains wordDict:

B. if s[:i] in wordDict:

C. if wordDict in s[:i]:

D. if s[:i] == wordDict:

Solution

1. Step 1: Understand Python membership syntax

   To check if an element is in a collection, use element in collection.

2. Step 2: Apply to substring and dictionary

   We want to check if substring s[:i] is in wordDict, so if s[:i] in wordDict: is correct.

3. Final Answer:

   if s[:i] in wordDict: -> Option B

4. Quick Check:

   Membership test uses 'in' keyword [OK]

Hint: Use 'in' keyword to check membership in Python [OK]

Common Mistakes:

• Using 'contains' instead of 'in'
• Reversing order of operands in membership test
• Using equality '==' instead of membership

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

def wordBreak(s, wordDict):
    dp = [False] * (len(s) + 1)
    dp[0] = True
    for i in range(1, len(s) + 1):
        for j in range(i):
            if dp[j] and s[j:i] in wordDict:
                dp[i] = True
                break
    return dp[-1]

print(wordBreak('applepenapple', {'apple', 'pen'}))

medium

A. False

B. null

C. SyntaxError

D. True

Solution

1. Step 1: Understand the dynamic programming approach

   The code uses a list dp where dp[i] is true if s[:i] can be segmented into dictionary words.

2. Step 2: Trace the input 'applepenapple'

   'apple' and 'pen' are in the dictionary. The string can be segmented as 'apple' + 'pen' + 'apple', so dp[-1] becomes True.

3. Final Answer:

   True -> Option D

4. Quick Check:

   String segments into dictionary words = True [OK]

Hint: Check if dp array ends with True for full string segmentation [OK]

Common Mistakes:

• Assuming false because of nested loops
• Confusing dp indices and substring slicing
• Ignoring the break statement after true found

4. Identify the error in the following code snippet for the Word Break Problem:

def wordBreak(s, wordDict):
    dp = [False] * len(s)
    dp[0] = True
    for i in range(1, len(s) + 1):
        for j in range(i):
            if dp[j] and s[j:i] in wordDict:
                dp[i] = True
    return dp[-1]

medium

A. dp list size is incorrect; should be len(s) + 1

B. Missing return statement

C. Using 'and' instead of '&' in condition

D. Loop ranges are reversed

Solution

1. Step 1: Check dp list initialization

   dp should have length len(s) + 1 to include dp[0] for empty string and dp[len(s)] for full string.

2. Step 2: Identify impact of incorrect dp size

   With dp size len(s), dp[i] access when i == len(s) causes index error or incorrect logic.

3. Final Answer:

   dp list size is incorrect; should be len(s) + 1 -> Option A

4. Quick Check:

   dp size = len(s)+1 needed for indexing [OK]

Hint: dp array must be length string+1 for indexing [OK]

Common Mistakes:

• Initializing dp with length len(s) only
• Forgetting dp[0] represents empty string
• Not breaking loop after setting dp[i] true

5. Given the string s = 'catsanddog' and dictionary wordDict = {'cat', 'cats', 'and', 'sand', 'dog'}, which of the following lists contains all possible valid segmentations of s?

hard

A. ['cat and dog', 'cats sand dog']

B. ['cat sanddog', 'catsand dog']

C. ['cats and dog', 'cat sand dog']

D. ['catsanddog']

Solution

1. Step 1: Identify valid dictionary words in the string

   Words 'cat', 'cats', 'and', 'sand', 'dog' are in the dictionary.

2. Step 2: Find segmentations matching dictionary words

   Possible splits: 'cats' + 'and' + 'dog' and 'cat' + 'sand' + 'dog' are valid segmentations.

3. Final Answer:

   ['cats and dog', 'cat sand dog'] -> Option C

4. Quick Check:

   All segments are dictionary words [OK]

Hint: Split string using all dictionary words to find valid sentences [OK]

Common Mistakes:

• Ignoring valid splits and choosing whole string
• Mixing invalid word splits
• Confusing word boundaries