Recursion for Interviews: Think Before You Code

Mon, 06 Jul 2026 09:00:00 +0500

Recursion problems have a peculiar failure mode in interviews. Candidates don’t run out of knowledge — they run out of working memory. They start tracing calls: “so f(4) calls f(3), which calls f(2), which calls f(1)…” and three levels deep, the whiteboard is a spiderweb and the interviewer is checking the clock.

Here’s the uncomfortable truth: if you’re mentally simulating the call stack, you’re doing it wrong. The entire point of recursion is that you don’t trace it. This post gives you the mental model that makes tracing unnecessary, then applies it to five real interview problems in Python.

Backtracking Explained: N-Queens to Subsets

Sat, 04 Jul 2026 10:00:00 +0500

Backtracking Explained: N-Queens to Subsets

If dynamic programming is the interview topic people fear most, backtracking is the one they fumble most. It shows up constantly — subsets, permutations, combination sum, word search, N-Queens — and candidates who haven’t internalized the pattern end up improvising recursion under pressure, which rarely goes well.

Here’s the good news: almost every backtracking interview problem is the same problem wearing a different costume. Once you learn the template, you stop memorizing solutions and start generating them. This post walks through the template and applies it to the four problem types that cover the vast majority of backtracking questions you’ll actually be asked.

Recursion on Algorithms in 60 Days

Recursion for Interviews: Think Before You Code

Backtracking Explained: N-Queens to Subsets

Backtracking Explained: N-Queens to Subsets