The Best Interview Question For Devs

A classic Memcached interview challenge—adding a new atomic arithmetic command (multiply by K) when only increment/decrement exist—turns into a practical filter for how candidates navigate unfamiliar codebases under time pressure. The core idea is simple: Memcached already supports atomic add via the existing INC/DEC-style commands, but it lacks an atomic multiply opcode. The task is to extend the command set, wire it through both parsing and execution paths, and keep concurrency semantics correct.

The walkthrough begins with hands-on familiarity: Memcached speaks a plain-text protocol over port 11211, where values are stored as key/value pairs with string keys and length-delimited byte values. Commands like `set`, `get`, `append`, `prepend`, and atomic `increment` demonstrate why the challenge matters. Atomic increment is guaranteed to apply correctly even with multiple clients updating the same key concurrently, and the server returns the post-update value so clients can safely use it as a serial number or primary-key-like counter. That behavior becomes the benchmark for the new multiply command: it must be atomic, return the right result immediately, and behave consistently across clients.

The interview twist is that multiply must be implemented by extending the existing arithmetic machinery rather than inventing a new system. The transcript emphasizes how the problem is “cleanly partitioned”: candidates must touch parsing/command dispatch, modify the arithmetic execution path, and update stats/telemetry fields so tests and instrumentation remain consistent. This structure helps steer strong candidates toward the intended “happy path” while leaving others stuck earlier—especially those who are unfamiliar with the codebase, the protocol layers, or the concurrency/locking patterns.

The discussion then breaks candidates into three broad groups. Some get stuck early by failing to interact with the real code base effectively. Others jump to a naive solution—treating multiplication as repeated addition by reusing increment logic, or doing a mechanical search-and-replace of operators—only to hit deeper issues like locking and atomicity. The best candidates notice they have time left and polish: consistent formatting, unit tests, and updating design decisions so they can justify tradeoffs if questioned.

A personal implementation attempt shows what “good enough” looks like in practice: the fastest route is to mimic the existing increment/decrement implementation, add a new opcode for multiply, thread it through the command parser, and update stats counters (hits/misses) so the test suite remains aligned. Manual testing can confirm basic behavior (including edge cases like wraparound and syntax), but the transcript highlights that the real proof comes from running the repo’s automated tests—some of which target both plain-text and binary protocol paths.

By the end, the challenge is judged as effective but not perfect. It rewards speed and codebase mimicry—sometimes “copy/paste with correctness”—which can resemble a speedrun of changes rather than a deeply creative engineering exercise. Still, it’s praised as a calibrated interview problem: it has one clear intended extension point, forces candidates to demonstrate real fluency with production code structure, and surfaces whether someone can extend behavior safely without breaking concurrency guarantees. The conversation closes by contrasting this with other interview styles (like bounded concurrency or retry/backoff logic) that test broader product-minded engineering rather than protocol-level surgery.