Impact of Time Complexity Using Array and Linked List in Data Structure - Jigar Pandya; Poonam Chakravarty (International Journal of Data Structure Studies, 2024)
Data structures are techniques for maintaining, manipulating, and storing data on a computer, enabling efficient access and modification. They support various operations, such as insertion, deletion, updating, and sorting. Examples of data structure include arrays, linked lists, graphs, heaps, stacks, and queues. Each data structure is designed to meet specific needs and solve particular problems. Typically, we identify the problem, devise a solution as an algorithm, and then write an efficient program. The program should be optimized for both time and space efficiency, which is why understanding 'time complexity' is essential. Time complexity measures the total execution time a program takes to complete and is expressed using Big O notation. Efficient data handling is crucial in modern computing applications, making it essential to understand the concept of time complexity in data structures. Time complexity measures the computational resources required by algorithms in relation to the size of their input. This abstract explores the fundamental time complexities of common data structures, offering insights into their operational efficiencies.
Keywords: Algorithm; array and linked list; data structure; time complexity