Our understanding of data structures as programmers is mostly limited to using them at a higher level of abstraction with a programming language.
Our understanding of data structures as programmers is mostly limited to using them at a higher level of abstraction with a programming language. Though we know how to store and retrieve data from different data structures using a particular programming language, most of us don’t try to unravel what goes on in the lower level implementation of these data structures.
Surface level knowledge of data structures is enough to somehow get our work done in most cases. But understanding how different data structures behave at the lower levels is crucial when it comes to selecting the optimal data structure for a given task. In this article, we will look under the wraps of 8 different data structures and see how they handle data.
Array data structure stores a fixed number of data of a single data type. Elements (items) in an array are stored in a block of contiguous memory slots. Due to this, elements in an array are assigned consecutive numbers, starting from 0 or 1, as their “indexes”.
One can access a single element stored in an array at random using its unique index. Accessing an element using the index has a time complexity of Θ(1). Reading or updating array elements can be easily achieved in this manner. Because of the contiguous location of array elements, arrays traversal is faster compared to most of the other data structures.
Inserting to or deleting from an array is a rather complex and time-consuming task. When inserting, all the elements in the current array are copied to a newly created array with increased size, and the new element is added to the end of the new array. Deleting is also implemented in a similar manner to reduce the array size.
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