Google India Engineers in a Mock Coding Interview

Recent questions

• How does a Google engineer approach engineering problems?

  A Google engineer approaches engineering problems by first understanding the requirements and constraints of the task at hand. They then analyze the problem, considering various solutions and their trade-offs. It is essential to prioritize clean and structured code, utilize the latest technical features wisely, and stick to one programming language consistently. Time management during interviews is crucial, as well as emphasizing testing and handling edge cases for solution validation.

• What is the initial solution for finding pairs in a number collection that sum up to a given target number?

  The initial solution involves a brute force method with two indices iterating through the array. This approach checks each pair of numbers in the collection to see if their sum matches the target number. While this method works, it may not be the most efficient solution, especially for large datasets.

• How can the complexity of finding pairs in a number collection be reduced to O(n log n)?

  A more efficient solution is proposed using the sorted array to perform binary search. By sorting the array first, the search for pairs that sum up to the target number becomes more optimized, reducing the complexity to O(n log n). This approach improves the efficiency of finding pairs in the collection.

• What optimization is suggested for finding pairs in a number collection with a linear solution?

  Further optimization is suggested by using two indices starting from the array's ends and moving towards each other. This linear solution involves checking for matching pairs and adjusting the indices accordingly. By iterating through the array in a specific manner, the algorithm can find pairs efficiently without the need for sorting.

• How can a hash set be utilized for a faster solution in finding pairs in a number collection?

  A hash set can be used to track seen values and their complements, allowing for a faster solution in finding pairs in a number collection. By storing values and their complements in a hash set, the algorithm can efficiently identify pairs that sum up to the target number. This approach improves the speed and performance of the solution, especially for larger datasets.