Solve problems that are commonly asked in C++ coding interviews related to common data structures.

Ace the C++ Coding Interview

Data structures are among the fundamentals of computer science and are often a core decision in developing efficient programs. They are categorized as a vital benchmark of computer science knowledge when it comes to industry interviews. This module contains a detailed review of common data structures in C++. We'll also become well-equipped with different data structures by implementing them.
By the end of this module, we'll have expertise in solving problems in data structures.

Data Structures


# Hashing

Until now, the overall time complexity accomplished by most of the data structures in **insertion**, **deletion**, and the **search** was up to *O(logn)*, which is pretty good. But for a significantly large amount of data, this complexity starts to affect the efficiency of an algorithm adversely. 

The ideal data structure is one that takes a constant amount of time to perform all three operations. And that is where **hashing** steps into the spotlight!


Hashing is a process used to store an object according to a unique key. This means that hashing always creates a **key-value pair**. A collection of such pairs forms a *dictionary* where every object or value can be looked up according to its key. Hence, the search operation can be performed in *O(1)*.

The concept of hashing has given birth to several new data structures, but the most prominent one is the **hash table**. 



# Hash Tables
If your algorithm prioritizes search operations, then a hash table is the best data structure for you. In C++, hash tables are generally implemented using arrays as they provide access to elements in constant time. Look at the figure below to see how *key* and *data* pairs are stored in a hash table.






This lesson is a brief introduction to the hash table data structure and the basic principle behind implementing it.

What is a Hash Table?

Hashing