Phone-screen staple at Citsec: start with the single-transaction max profit, ladder up through unlimited transactions, then bounded-k transactions, and on some loops add cooldown / transaction-fee variants. Interviewers grade as much on the generalization narrative (state definition, complexity, edge cases) as on the final code.

Requirements Three levels, usually in order. The interviewer escalates only after the previous level is clean. 1. Level 1 — Single transaction. Given prices[] where prices[i] is the stock price on day i, return the maximum profit from at most one buy / sell pair (buy must precede sell, hold time unbounded). 2. Level 2 — Unlimited transactions, no concurrent holdings. Same input. You may transact arbitrarily many times but may hold at most one share at any moment. Return the maximum total profit. 3. Level 3 — At most k transactions. Given prices[] and integer k, return the maximum profit from at most k complete buy / sell pairs. Examples Examples below are taken verbatim from candidate-reported sessions. - Level 1 — interviewer asked for the one-pass solution and explicitly probed why tracking min so far was sufficient instead of a full two-pointer sweep. - Level 2 — interviewer pushed for an O(1) space optimization after the initial DP solution. - Level 3 — interviewer accepted the dp[i][j][0/1] formulation and probed whether the j-dimension could be compressed, the time / space complexity at large k, and what happens when k = n / 2 (degenerates to Level 2). One Citsec onsite reportedly bolted on transaction fees and a one-day cooldown as follow-ups beyond Level 3, asking for the corresponding state-machine updates. Notes - Level 1 is the canonical one-pass minimum-tracking pattern. Time O(n), space O(1). - Level 2 has two equivalent framings: greedy summation of positive deltas, or two-state DP (hold / not-hold) compressible to two scalars. Most interviewers prefer the DP framing because it generalizes to Level 3 without rewriting. - Level 3 uses dp[j][0/1] where j is transactions used; space is O(k) after compressing the day axis with rolling updates. Watch the buy-side update ordering — not-hold must update before hold when iterating in-place to avoid double-counting. - The fee / cooldown variants add one term or one extra state to the transition; clean state-machine bookkeeping is the discriminator. - Common failure mode: when extending to Level 3, candidates re-derive the DP from scratch rather than naming the state explicitly. Verbalize the state (dp[day][txn count][holding]) before writing. Preparation - Drill the full LC 121 / 122 / 123 / 188 / 309 / 714 ladder in one sitting; the Citsec ask reproduces 3-5 rungs in 30 minutes. - Practice giving the generalization talk track in under 90 seconds: state, transition, base case, complexity, space optimization. Interviewers grade this explicitly. - Rehearse the k = n/2 collapse argument out loud — it is a frequent follow-up. - For Citsec specifically, prepare to switch language mid-round if the interviewer flips from Python to C++ after seeing your resume.

Best Time to Buy and Sell Stock — Full DP Ladder — Citadel / Citadel Securities Interview Question

Requirements

Three levels, usually in order. The interviewer escalates only after the previous level is clean.

Level 1 — Single transaction. Given prices[] where prices[i] is the stock price on day i, return the maximum profit from at most one buy / sell pair (buy must precede sell, hold time unbounded).
Level 2 — Unlimited transactions, no concurrent holdings. Same input. You may transact arbitrarily many times but may hold at most one share at any moment. Return the maximum total profit.
Level 3 — At most k transactions. Given prices[] and integer k, return the maximum profit from at most k complete buy / sell pairs.

Examples

Examples below are taken verbatim from candidate-reported sessions.

Level 1 — interviewer asked for the one-pass solution and explicitly probed why tracking min_so_far was sufficient instead of a full two-pointer sweep.
Level 2 — interviewer pushed for an O(1) space optimization after the initial DP solution.
Level 3 — interviewer accepted the dp[i][j][0/1] formulation and probed whether the j-dimension could be compressed, the time / space complexity at large k, and what happens when k >= n / 2 (degenerates to Level 2).

One Citsec onsite reportedly bolted on transaction fees and a one-day cooldown as follow-ups beyond Level 3, asking for the corresponding state-machine updates.

Notes

Level 1 is the canonical one-pass minimum-tracking pattern. Time O(n), space O(1).
Level 2 has two equivalent framings: greedy summation of positive deltas, or two-state DP (hold / not-hold) compressible to two scalars. Most interviewers prefer the DP framing because it generalizes to Level 3 without rewriting.
Level 3 uses dp[j][0/1] where j is transactions used; space is O(k) after compressing the day axis with rolling updates. Watch the buy-side update ordering — not-hold must update before hold when iterating in-place to avoid double-counting.
The fee / cooldown variants add one term or one extra state to the transition; clean state-machine bookkeeping is the discriminator.
Common failure mode: when extending to Level 3, candidates re-derive the DP from scratch rather than naming the state explicitly. Verbalize the state (dp[day][txn_count][holding]) before writing.

Preparation

Drill the full LC 121 / 122 / 123 / 188 / 309 / 714 ladder in one sitting; the Citsec ask reproduces 3-5 rungs in 30 minutes.
Practice giving the generalization talk track in under 90 seconds: state, transition, base case, complexity, space optimization. Interviewers grade this explicitly.
Rehearse the k >= n/2 collapse argument out loud — it is a frequent follow-up.
For Citsec specifically, prepare to switch language mid-round if the interviewer flips from Python to C++ after seeing your resume.

Requirements

Examples

Notes

Preparation

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