Top techniques to approach and solve coding interview questions | Tech Interview Handbook

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• These are the data structures to keep in mind and try, in order of frequency they appear in coding interview questions:

• Routines

• candidates should start by asking clarifying questions and discussing a few possible approaches with their interviewers.

• 1. Visualize the problem by drawing it out

• Whiteboards make it easy to draw diagrams which helps with problem solving!

• A huge part of coding is understanding how the internal state of a program changes and diagrams are super useful tools for representing the internal data structures state.

• 2. Think about how you would solve the problem by hand

• Solving the problem by hand is about solving the problem without writing any code, like how a non-programmer would

• If you can come up with a concrete set of rules around the approach that works for every example, you can write the code for it.

• Coming up with more examples

• It helps you to reinforce your understanding of the question, prevents you from prematurely jumping into coding, helps you to identify a pattern which can be generalized to any input, which is the solution!

• If the problem is large, start with a high-level function and break it down into smaller constituting functions, solving each one separately.

• Hash Maps: Useful for making lookup efficient. This is the most common data structure used in interviews and you are guaranteed to have to use it.

• Graphs: If the data is presented to you as associations between entities, you might be able to model the question as a graph and use some common graph algorithm to solve the problem.

• Stack and Queue: If you need to parse a string with nested properties (such as a mathematical equation), you will almost definitely need to use stacks. Heap: Question involves scheduling/ordering based on some priority. Also useful for finding the max K/min K/median elements in a set. Tree/Trie: Do you need to store strings in a space-efficient manner and look for the existence of strings (or at least part of them) very quickly?

• Sorting Binary search: Useful if the input array is sorted and you need to do faster than O(n) searches Sliding window Two pointers Union find BFS/DFS Traverse from the back Topological Sorting

• The Best Theoretical Time Complexity (BTTC) of a solution is a time complexity you know that you cannot beat.

• The fastest practical solution can only ever be as fast as the BTTC

• Choice of data structures is key to coding interviews

• It can help you to reach a solution for the problem, it can also help you to optimize your existing solution.