What are the common string manipulation problems in interviews?

String manipulation is a fundamental aspect of programming and a common topic in technical interviews. Mastering string problems not only demonstrates your proficiency in handling data but also showcases your problem-solving and algorithmic thinking skills. Below is a comprehensive list of common string manipulation problems you may encounter in software engineering interviews, along with brief descriptions and key approaches to solving them.

1. Reverse a String

• Description: Reverse the characters of a given string.
• Approach:
  • Use two-pointer technique (start and end) to swap characters.
  • Utilize built-in functions (language-dependent) for reversing.
• Example:
  • Input: "hello"
  • Output: "olleh"

2. Check if a String is a Palindrome

• Description: Determine whether a string reads the same backward as forward.
• Approach:
  • Compare characters from both ends moving towards the center.
  • Ignore non-alphanumeric characters and case sensitivity if specified.
• Example:
  • Input: "A man, a plan, a canal: Panama"
  • Output: True

3. Anagram Check

• Description: Check if two strings are anagrams (contain the same characters in a different order).
• Approach:
  • Sort both strings and compare.
  • Use a frequency count (hash map) to tally character occurrences.
• Example:
  • Input: "listen", "silent"
  • Output: True

4. Longest Substring Without Repeating Characters

• Description: Find the length of the longest substring without repeating characters.
• Approach:
  • Use sliding window technique with a hash set or hash map to track characters.
  • Expand and shrink the window based on character repetition.
• Example:
  • Input: "abcabcbb"
  • Output: 3 ("abc")

5. Find All Anagrams in a String

• Description: Find all start indices of anagrams of a given pattern within a string.
• Approach:
  • Use sliding window with frequency count comparison.
  • Optimize by tracking the number of matching characters.
• Example:
  • Input: s = "cbaebabacd", p = "abc"
  • Output: [0, 6]

6. Longest Palindromic Substring

• Description: Find the longest palindromic substring within a given string.
• Approach:
  • Expand around potential centers (each character and between characters).
  • Dynamic programming to track palindromic substrings.
• Example:
  • Input: "babad"
  • Output: "bab" or "aba"

7. Valid Parentheses

• Description: Determine if the input string has valid parentheses (properly closed and nested).
• Approach:
  • Use a stack to track opening brackets and ensure they match corresponding closing brackets.
• Example:
  • Input: "()[]{}"
  • Output: True

8. Implement strstr (Find Substring)

• Description: Implement a function to find the first occurrence of a substring within a string.
• Approach:
  • Iterate through the main string and compare substrings.
  • Utilize efficient algorithms like KMP (Knuth-Morris-Pratt) for optimized searching.
• Example:
  • Input: haystack = "hello", needle = "ll"
  • Output: 2

9. Longest Common Prefix

• Description: Find the longest common prefix string among an array of strings.
• Approach:
  • Horizontal scanning by comparing prefixes one by one.
  • Vertical scanning by comparing characters column-wise.
• Example:
  • Input: ["flower","flow","flight"]
  • Output: "fl"

10. String to Integer (atoi)

• Description: Convert a string to a 32-bit signed integer (similar to C/C++'s atoi function).
• Approach:
  • Handle leading whitespaces, optional sign, digits, and overflow.
  • Iterate through the string character by character, building the integer.
• Example:
  • Input: "42"
  • Output: 42

11. Encode and Decode Strings (Run-Length Encoding)

• Description: Encode a string using run-length encoding and decode it back.
• Approach:
  • Iterate through the string, count consecutive characters, and build the encoded string.
  • Reverse the process for decoding.
• Example:
  • Input: "aaabbc"
  • Encoded: "3a2b1c"
  • Decoded: "aaabbc"

12. Group Anagrams

• Description: Group a list of strings into anagrams.
• Approach:
  • Sort each string and use it as a key in a hash map to group anagrams.
  • Alternatively, use character frequency counts as keys.
• Example:
  • Input: ["eat", "tea", "tan", "ate", "nat", "bat"]
  • Output: [["ate","eat","tea"], ["nat","tan"], ["bat"]]

13. Shortest Palindrome

• Description: Find the shortest palindrome you can make by adding characters in front of a string.
• Approach:
  • Find the longest palindromic prefix.
  • Append the reverse of the remaining suffix to the front.
• Example:
  • Input: "aacecaaa"
  • Output: "aaacecaaa"

14. ZigZag Conversion

• Description: Convert a string to a zigzag pattern on a given number of rows and then read it line by line.
• Approach:
  • Simulate the zigzag pattern by iterating through the string and assigning characters to the appropriate row.
• Example:
  • Input: "PAYPALISHIRING", 3
  • Output: "PAHNAPLSIIGYIR"

15. Implement Regular Expression Matching

• Description: Implement a regular expression matching with support for '.' and '*'.
• Approach:
  • Use dynamic programming to handle pattern matching with wildcard characters.
  • Consider recursion with memoization for breaking down the problem.
• Example:
  • Input: s = "aab", p = "c*a*b"
  • Output: True

16. Maximum Product of Word Lengths

• Description: Find the maximum value of length(word[i]) * length(word[j]) where the two words do not share common letters.
• Approach:
  • Use bitmasking to represent each word's characters and compare for common bits.
  • Iterate through all pairs to find the maximum product.
• Example:
  • Input: ["abcw","baz","foo","bar","xtfn","abcdef"]
  • Output: 16 ("abcw" and "xtfn")

17. Minimum Window Substring

• Description: Find the minimum window in string s which will contain all the characters in string t.
• Approach:
  • Use sliding window technique with two pointers to track the window.
  • Maintain a hash map to count character frequencies.
• Example:
  • Input: s = "ADOBECODEBANC", t = "ABC"
  • Output: "BANC"

18. Palindrome Permutation

• Description: Check if any permutation of a string can form a palindrome.
• Approach:
  • Count the frequency of each character.
  • Ensure that at most one character has an odd frequency.
• Example:
  • Input: "code"
  • Output: False

19. Unique Email Addresses

• Description: Determine how many unique email addresses there are after normalization.
• Approach:
  • Split email into local and domain parts.
  • Normalize the local part by removing dots and ignoring characters after a plus sign.
  • Use a hash set to store unique normalized emails.
• Example:
  • Input: ["test.email+alex@leetcode.com","test.e.mail+bob.cathy@leetcode.com","testemail+david@lee.tcode.com"]
  • Output: 2

20. Valid Palindrome II

• Description: Determine if a string can become a palindrome by removing at most one character.
• Approach:
  • Use two pointers to compare characters from both ends.
  • Allow skipping one mismatched character and check if the remaining substring is a palindrome.
• Example:
  • Input: "abca"
  • Output: True (Remove 'c' to make "aba")

Tips for Tackling String Manipulation Problems in Interviews

1. Understand the Problem Fully:

   • Clarify requirements, constraints, and edge cases before diving into coding.

2. Plan Your Approach:

   • Outline your logic and choose appropriate data structures (e.g., hash maps, sets, arrays).

3. Optimize for Time and Space:

   • Strive for efficient solutions, especially for problems with large input sizes.

4. Communicate Clearly:

   • Explain your thought process, choices, and trade-offs to the interviewer as you work through the problem.

5. Practice Regularly:

   • Use platforms like LeetCode, HackerRank, and CodeSignal to practice a variety of string problems.

6. Review Common Patterns:

   • Recognize recurring patterns such as sliding windows, two pointers, frequency counting, and dynamic programming.

7. Write Clean and Readable Code:

   • Use meaningful variable names, proper indentation, and comments where necessary to enhance readability.

8. Test Your Solutions:

   • Run through sample inputs and edge cases to ensure your code handles all scenarios correctly.

Recommended Resources for Practice

• Books:

  • "Cracking the Coding Interview" by Gayle Laakmann McDowell
  • "Elements of Programming Interviews" by Adnan Aziz, Tsung-Hsien Lee, and Amit Prakash

• Online Courses:

  • Grokking the Coding Interview: Patterns for Coding Questions
    • Focuses on identifying and applying common problem-solving patterns.
  • Grokking Data Structures & Algorithms for Coding Interviews
    • Comprehensive coverage of data structures and algorithms with practical examples.

• Websites:

  • LeetCode: Extensive collection of coding problems categorized by difficulty and topic.
  • HackerRank: Offers coding challenges and contests to test your skills.
  • GeeksforGeeks: Provides tutorials and practice problems on various programming topics.

Conclusion

String manipulation problems are a staple in coding interviews, testing your ability to handle data processing, algorithmic thinking, and optimization. By familiarizing yourself with common problems, understanding key approaches, and practicing regularly, you can enhance your proficiency and confidence in tackling these challenges. Utilize the resources and strategies outlined above to build a strong foundation, enabling you to perform effectively in your software engineering interviews.