5 articles
LC 70 Climbing Stairs is the canonical introduction to 1D dynamic programming. The recurrence dp[n] = dp[n-1] + dp[n-2] is pure Fibonacci, and mastering why it works — recursion to memoization to tabulation — unlocks the entire family of staircase DP problems asked at Google, Amazon, and Meta.
LC 746 Min Cost Climbing Stairs extends the Climbing Stairs Fibonacci DP with per-step costs. The recurrence dp[i] = cost[i] + min(dp[i-1], dp[i-2]) computes the minimum total cost to leave each step. Asked at Amazon and Google as a direct test of whether you can adapt a known recurrence pattern under new constraints.
LC 91 Decode Ways counts the number of ways to decode a digit string as letters A-Z. The recurrence combines one-digit and two-digit transitions — a conditional Fibonacci DP. Heavily tested at Amazon, Google, and Meta because it combines string parsing, edge case handling, and DP reasoning in a single problem.
Matrix exponentiation collapses any linear recurrence into O(log n) by raising a transition matrix to the n-th power. Master Fibonacci, k-th order recurrences, and DP optimization tricks that let you answer queries with n up to 10^18 in milliseconds.
Recognising classical number sequences — Fibonacci, Catalan, triangular, Pascal-derived — is the difference between a 30-minute brute force and a 5-minute closed form. Master the recurrences, generating functions, and combinatorial interpretations every interviewer expects you to know.