### Approach To effectively answer the question "How would you write a function to merge two sorted arrays into one sorted array?", follow this structured framework: 1. **Understand the Problem**: Clarify the requirements and constraints. 2. **Choose the Right Algorithm**: Consider the efficiency of your approach. 3. **Write the Code**: Implement your solution with clear logic. 4. **Test the Function**: Validate your code with sample inputs. ### Key Points - **Clarity**: Make sure your explanation is straightforward and easy to follow. - **Logic**: Show your reasoning and thought process behind the implementation. - **Efficiency**: Discuss the time and space complexity of your approach. - **Edge Cases**: Address potential edge cases that your function should handle. ### Standard Response Here’s a comprehensive answer demonstrating how to merge two sorted arrays into one sorted array: ```python def merge_sorted_arrays(arr1, arr2): # Create a new array to hold the merged result merged_array = [] i, j = 0, 0 # Loop until we reach the end of either array while i < len(arr1) and j < len(arr2): if arr1[i] < arr2[j]: merged_array.append(arr1[i]) i += 1 else: merged_array.append(arr2[j]) j += 1 # If there are remaining elements in arr1, add them while i < len(arr1): merged_array.append(arr1[i]) i += 1 # If there are remaining elements in arr2, add them while j < len(arr2): merged_array.append(arr2[j]) j += 1 return merged_array # Example usage array1 = [1, 3, 5] array2 = [2, 4, 6] result = merge_sorted_arrays(array1, array2) print(result) # Output: [1, 2, 3, 4, 5, 6] ``` **Explanation**: 1. **Initialization**: Two pointers, `i` and `j`, start at the beginning of `arr1` and `arr2`, respectively. 2. **Comparison**: Compare elements from both arrays and append the smaller one to `merged_array`. 3. **Remaining Elements**: After the loop, append any remaining elements from either array. 4. **Return the Result**: The function returns a single sorted array. ### Tips & Variations #### Common Mistakes to Avoid: - **Ignoring Edge Cases**: Make sure to handle cases where one or both arrays are empty. - **Inefficient Approaches**: Avoid nested loops, which can lead to higher time complexity (O(n^2)). #### Alternative Ways to Answer: - **Using Built-in Functions**: You could use Python's built-in `sorted()` function to combine and sort both arrays, but this would not be optimal in terms of efficiency. ```python def merge_sorted_arrays(arr1, arr2): return sorted(arr1 + arr2) ``` #### Role-Specific Variations: - **Technical Roles**: Focus on time complexity, memory usage, and edge cases. - **Creative Roles**: Emphasize problem-solving and the creativity behind the approach. - **Managerial Roles**: Discuss how this function could be useful in larger projects or systems. #### Follow-Up Questions: - How would you optimize this function for larger datasets? - Can you explain the time and space complexity of your solution? - How would you handle duplicate elements in the arrays? ### Conclusion By following this structured approach, you can effectively demonstrate your coding skills and problem-solving abilities during technical interviews. Remember to articulate your thought process clearly, handle edge cases, and discuss the efficiency of your solution to leave a positive impression on your interviewer. This comprehensive guide equips you with the tools needed to tackle similar coding questions in your job search and career growth