Compare arrays, linked lists, hash tables, trees

Q: Compare arrays, linked lists, hash tables, trees

Evaluates understanding of foundational data structures and algorithmic complexity—arrays, linked lists, dynamic arrays, hash tables/maps, trees—and common sorting algorithms.

Q: How do I approach Software Engineering Fundamentals interview questions?

Software Engineering Fundamentals questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master software engineering fundamentals interviews.

Question

Answer the following computer-science fundamentals questions:

What are the time complexities (Big-O) of common sorting algorithms (e.g., bubble sort, insertion sort, selection sort, merge sort, quicksort, heap sort) in best/average/worst cases?
Compare arrays vs. linked lists. What are the time complexities of accessing an element, inserting at the head, and inserting in the middle?
Describe the full step-by-step process of inserting an element at the head of a dynamic array (e.g., vector/ArrayList), including what happens when the array needs to grow.
What is a hash table? Describe its underlying data structure and how collisions are handled.
What is the difference between a “hash table” and a “hash map” (conceptually and, if relevant, in common languages such as Java)?
What is the difference between a binary tree and a binary search tree (BST)?

Compare arrays, linked lists, hash tables, trees

Quick Overview

Solution

Comments (0)