Data structures and Algorithms

A critical first step in preparing for any programming-related job interview is ensuring you have command of fundamental computer science data structures and algorithms. While you won't need to have every detail memorized, being generally familiar with the most common options is essential.

Here are some of the key data structures and algorithms to review and practice implementing:

• Linked Lists - singly, doubly, circular
• Stacks
• Queues
• Trees - binary, binary search, AVL, red-black, segment
• Heaps - min-heap, max-heap
• Hash Tables
• Graphs - adjacency list, adjacency matrix, weighted
• Sorting Algorithms - quicksort, mergesort, heapsort, insertion sort
• Search Algorithms - binary search, DFS, BFS
• Dynamic Programming - memoization, tabulation

When studying these data structures and algorithms, focus on:

• Use cases - when is each most appropriate?
• Time and space complexity - Big O analysis
• Common operations - insertion, deletion, traversal, sorting, etc.
• Implementation tradeoffs
• Strengths and limitations
• Coding them from scratch in your chosen language

With strong grasp of these fundamental building blocks, you will have the core CS knowledge needed to analyze and solve problems efficiently in interviews. Be ready to walk through your code, explain your design choices, discuss complexity, and compare approaches.

Going beyond familiarity to deep expertise with data structures and algorithms will help you stand out and succeed in landing your ideal programming role.