Approach

To effectively sort an array of strings and group anagrams together, follow this structured framework:

1. Understand Anagrams: Recognize that anagrams are words formed by rearranging the letters of another, using all the original letters exactly once.

2. Use a Hash Map: Utilize a hash map (or dictionary) to group words that are anagrams of each other.

3. Sort Each String: For each string, sort the characters to create a unique key for the anagram group.

4. Store in Groups: Use the sorted string as a key in the hash map, appending the original string to the corresponding list.

5. Return Results: Extract the values from the hash map to get the final grouped anagrams.

Key Points

• Clarity on Anagram Grouping: Interviewers expect candidates to clearly understand the definition of anagrams and their properties.

• Efficiency: Consider the time complexity of your approach. Sorting each string has a time complexity of O(N log N), where N is the length of the string.

• Use of Data Structures: Show your knowledge of using hash maps for efficient data storage and retrieval.

Standard Response

def group_anagrams(strs):
 anagrams = {}
 
 for s in strs:
 # Sort the string to create a key
 key = ''.join(sorted(s))
 
 # Add the original string to the corresponding anagram group
 if key not in anagrams:
 anagrams[key] = []
 anagrams[key].append(s)
 
 # Return the grouped anagrams as a list of lists
 return list(anagrams.values())

• Input: An array of strings strs.

• Process:

• Iterate through each string in the array.

• Sort the string and use it as a key in the dictionary.

• Append each string to its corresponding list based on the key.

• Output: A list of lists, where each inner list contains grouped anagrams.

• Explanation:

Tips & Variations

Common Mistakes to Avoid

• Ignoring Edge Cases: Don’t forget to handle empty strings or single-character strings.

• Misunderstanding Sorting: Ensure you understand how sorting affects performance; for larger datasets, this can become a bottleneck.

• Not Using Appropriate Data Structures: A common pitfall is to use lists instead of hash maps for grouping, leading to inefficient searches.

Alternative Ways to Answer

• Using Python's Built-in Functions: You can leverage Python’s collections.defaultdict for cleaner code.

Role-Specific Variations

• Technical Roles: Emphasize algorithm efficiency and discuss time complexity.

• Managerial Roles: Focus on team collaboration and how you would facilitate a discussion around problem-solving.

• Creative Roles: Highlight innovative approaches to grouping or categorizing similar ideas or concepts.

Follow-Up Questions

• Can you explain how this method handles large datasets?

• What would you do if the input strings came from a database instead of a list?

• How would you modify the algorithm to include case sensitivity, or ignore it?

By following this structured approach, job seekers can confidently tackle interview questions about sorting and grouping data, showcasing their problem-solving abilities and technical skills in a clear and organized manner