Many people believe that organizational recruiters pay too much importance to data structures and algorithms. While you might never use types like binary tree inversion, there are concepts that you need regularly. Even if you are not using them, they help figure out how you should design your data. In this article at the Pragmatic Engineer, find out if data structures and algorithms are optional or mandatory technical requirements for developers.
Data Structures and Algorithms
You do not need to use all the data structures and algorithms, especially the rare ones, even if you work for an IT company. You can come up with one when you have the core knowledge. Learn the basic data structures like hashtables, queues, and stacks. For algorithms, learn Dijkstra and A*. You can easily decipher exotic data structures such as Red-Black trees and AVL trees. Let’s find some examples:
Trees and Tree Traversing
You must work on DOM, a tree, or BFS or DFS for all nodes for web development. UI developers usually use tree structures for backend development. Skype and Uber apps use the same.
Weighed Graphs and Shortest Paths
Have you used Skyscanner to get airline tickets? It uses shortest path algorithms like Dijkstra or A* to provide answers for your multi-city travel searches.
Among the data structures and algorithms, you will use sorting the least. However, have knowledge about bubble sort, insertion sort, merge sort, selection sort, and quicksort.
You will be using hashtables and the hash function the most out of all the data structures and algorithms. From counting to sharding, they have multiple use cases.
Stacks and Queues
Have you debugged something with a stack trace? Developers that perform debugging and performance profiling use stack quite often. Use queues for codebases, code popping, and pushing values.
Only a few would know about rare data structures and algorithms. If recruiters use that as a benchmark, they have to reject the otherwise talented pool of candidates. The objective is to understand data structures and algorithms and solve issues proactively.
To view the original article in full, visit the following link: https://blog.pragmaticengineer.com/data-structures-and-algorithms-i-actually-used-day-to-day/
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