The most common interview task related to sorting algorithms is the implementation of sorting itself. We wrote about them in the previous topic, where we analyzed all implementations of popular sorting algorithms.
Here we have collected the most popular problems, for which complete sorting algorithms or some techniques from those algorithms are used.
Each problem is presented in the form of a problem statement, which describes the task to be accomplished, and a dataset, which provides specific instances of the problem to be solved. The problem statement includes a description of the input and output data, as well as the optimal time complexity for the solution.
You will need to download the dataset, run the solution, and paste the answer into the box. Thanks to this, you can solve in any programming language you like. We specify the time complexity to be achieved in each problem in the solution.
Here's a brief overview of the structure of each problem:
Problem Statement: This describes what the problem is asking for. It outlines the task to be accomplished and provides any constraints or conditions that must be met.
Input: This section describes the format and constraints of the input data. This data is provided as a string, and it often needs to be converted into a more useful data structure, like a list or a dictionary, before it can be used.
Output: This section describes the format and constraints of the output data. This is the result that your solution should produce. It must be returned as a string, even if the actual result is a different data type, like a number or a list.
Time Complexity: This section provides a target time complexity for the solution. Achieving this time complexity often requires using specific algorithms or data structures, and it's a good way to gauge the efficiency of your solution.
By working through these problems, you'll get a chance to practice your problem-solving skills, deepen your understanding of algorithms and data structures, and prepare for the kinds of challenges you might face in a technical interview. Good luck!