I’ve interviewed with Google, Apple, Amazon, MongoDB, Capital One, and countless others. Every one of them put me through a coding interview, with wildly varying degrees of difficulty. I could say a lot more about that — but it’s the kind of topic that almost demands pushback, so you’ll have to drag the unfiltered version out of me on the discussion boards. ;)
The languages varied as much as the difficulty did. I once had an interview where every line had to be delivered in Python — and another where I was offered the choice of literally any language, except Python.
A Little History
I’m genuinely happy to be working in an era where remote work for software engineers is normalized. Mind you, this isn’t new to me. I worked remotely, full-time, as far back as 2004–2005 — for Sun Microsystems. Sun was a company ahead of its time in some ways, and out of time in others (LOL). It was eventually acquired by Oracle, and a lot of what made it special got absorbed and rearranged.
There’s no shortage of interview prep material online these days. In my time, I leaned on Cracking the Coding Interview by Gayle Laakmann McDowell — the book this whole repository is named after. Its companion site, HackerRank, is a lot of fun. I’m not a competitive-coding person, but I enjoy taking a swing at the challenges there now and then.
Back in 2019 I was job hunting, and I wanted to be prepared. The exercises below are some of the practice problems I worked through, collected in my Cracking-the-Coding-Interview-in-Java repository. They contain a combination of puzzles, like what you might see in a job interview, and deep dives into complex algorithms using source material - just to get my brain working on following detailed instructions.
One heads-up if you click into the code: the variable names are short and the style is deliberately terse. I wrote these in a whiteboard-coding frame of mind, where spelling out long, descriptive names costs you time you don’t have. It’s not how I write production code — it’s how you write code with a marker in your hand and an interviewer watching the clock.
The Puzzles
Add Without Arithmetic — Add two integers without using + or any arithmetic operator at all — only bitwise logic, propagating the carry one bit at a time across all 32 bits. A classic test of whether you really understand two’s complement.
Unique Characters — Determine whether every character in a string is unique, with the twist that you’re not allowed any additional data structures. The repo solves it recursively in O(n²) to honor that constraint, then adds a bonus O(n) version for when a lookup table is allowed.
Compound Words — Decide whether a word can be assembled entirely from a dictionary of smaller words — “houseboat” from “house” plus “boat”. There are two implementations: a straightforward slow recursion, and a faster one backed by a sorted set.
Word Ladder — Given two equal-length words and a dictionary, transform one into the other one letter at a time, where every intermediate step is itself a real word: DAMP → LAMP → LIMP → LIME → LIKE. It’s a word ladder puzzle, and under the hood it’s a breadth-first search.
Rabin–Karp String Search — Find a pattern inside a larger string using a rolling hash, so most non-matching positions can be rejected with a single cheap comparison instead of a full character-by-character scan. (Rabin–Karp)
Remove Duplicates from a Linked List — Walk an unsorted singly-linked list and splice out repeated values, using a hash set to remember what’s already been seen.
Reverse a Tree’s Siblings — Take a tree stored in child/sibling representation and reverse every sibling list, from the root all the way down. Easy to describe, and genuinely fiddly to get right with pointers.
Select Random — Pick m integers at random from an array of n, with no repeats — a partial Fisher–Yates that does just enough shuffling to fill the result.
Shuffle — Shuffle a deck in place with the full Fisher–Yates algorithm — every ordering equally likely, no bias.
Bomberman — On a 2D grid of walls, badguys, and empty space, find the single spot where dropping a bomb takes out the most badguys. The blast travels down its row and column until a wall stops it. The whole grid is solved in one O(N) sweep.
Minimum Spanning Trees: Kruskal & Prim — Two classic graph algorithms aimed at the same target — finding the minimum spanning tree of a weighted graph. Kruskal’s sorts the edges and leans on a disjoint-set (“union-find”) structure to avoid cycles; Prim’s grows the tree outward from a starting node. The union-find itself is implemented here as weighted quick-union with path compression — an intereting data structure that’s a complex piece of engineering in its own right.
Closing
If any of these bring back your own interview war stories or classroom nostalgia — triumphant or traumatic — let us know on the message boards! ;)