LeetCode #3280 — EASY

Convert Date to Binary

Build confidence with an intuition-first walkthrough focused on math fundamentals.

Solve on LeetCode
The Problem

Problem Statement

You are given a string date representing a Gregorian calendar date in the yyyy-mm-dd format.

date can be written in its binary representation obtained by converting year, month, and day to their binary representations without any leading zeroes and writing them down in year-month-day format.

Return the binary representation of date.

Example 1:

Input: date = "2080-02-29"

Output: "100000100000-10-11101"

Explanation:

100000100000, 10, and 11101 are the binary representations of 2080, 02, and 29 respectively.

Example 2:

Input: date = "1900-01-01"

Output: "11101101100-1-1"

Explanation:

11101101100, 1, and 1 are the binary representations of 1900, 1, and 1 respectively.

Constraints:

  • date.length == 10
  • date[4] == date[7] == '-', and all other date[i]'s are digits.
  • The input is generated such that date represents a valid Gregorian calendar date between Jan 1st, 1900 and Dec 31st, 2100 (both inclusive).

Roadmap

  1. Brute Force Baseline
  2. Core Insight
  3. Algorithm Walkthrough
  4. Edge Cases
  5. Full Annotated Code
  6. Interactive Study Demo
  7. Complexity Analysis
Step 01

Brute Force Baseline

Problem summary: You are given a string date representing a Gregorian calendar date in the yyyy-mm-dd format. date can be written in its binary representation obtained by converting year, month, and day to their binary representations without any leading zeroes and writing them down in year-month-day format. Return the binary representation of date.

Baseline thinking

Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.

Pattern signal: Math

Example 1

"2080-02-29"

Example 2

"1900-01-01"

Related Problems

  • Number of 1 Bits (number-of-1-bits)
  • Convert to Base -2 (convert-to-base-2)
Step 02

Core Insight

What unlocks the optimal approach

  • No official hints in dataset. Start from constraints and look for a monotonic or reusable state.
Interview move: turn each hint into an invariant you can check after every iteration/recursion step.
Step 03

Algorithm Walkthrough

Iteration Checklist

  1. Define state (indices, window, stack, map, DP cell, or recursion frame).
  2. Apply one transition step and update the invariant.
  3. Record answer candidate when condition is met.
  4. Continue until all input is consumed.
Use the first example testcase as your mental trace to verify each transition.
Step 04

Edge Cases

Minimum Input
Single element / shortest valid input
Validate boundary behavior before entering the main loop or recursion.
Duplicates & Repeats
Repeated values / repeated states
Decide whether duplicates should be merged, skipped, or counted explicitly.
Extreme Constraints
Upper-end input sizes
Re-check complexity target against constraints to avoid time-limit issues.
Invalid / Corner Shape
Empty collections, zeros, or disconnected structures
Handle special-case structure before the core algorithm path.
Step 05

Full Annotated Code

Source-backed implementations are provided below for direct study and interview prep.

// Accepted solution for LeetCode #3280: Convert Date to Binary
class Solution {
    public String convertDateToBinary(String date) {
        List<String> ans = new ArrayList<>();
        for (var s : date.split("-")) {
            int x = Integer.parseInt(s);
            ans.add(Integer.toBinaryString(x));
        }
        return String.join("-", ans);
    }
}
Step 06

Interactive Study Demo

Use this to step through a reusable interview workflow for this problem.

Press Step or Run All to begin.
Step 07

Complexity Analysis

Time
O(n)
Space
O(n)

Approach Breakdown

ITERATIVE
O(n) time
O(1) space

Simulate the process step by step — multiply n times, check each number up to n, or iterate through all possibilities. Each step is O(1), but doing it n times gives O(n). No extra space needed since we just track running state.

MATH INSIGHT
O(log n) time
O(1) space

Math problems often have a closed-form or O(log n) solution hidden behind an O(n) simulation. Modular arithmetic, fast exponentiation (repeated squaring), GCD (Euclidean algorithm), and number theory properties can dramatically reduce complexity.

Shortcut: Look for mathematical properties that eliminate iteration. Repeated squaring → O(log n). Modular arithmetic avoids overflow.
Coach Notes

Common Mistakes

Review these before coding to avoid predictable interview regressions.

Overflow in intermediate arithmetic

Wrong move: Temporary multiplications exceed integer bounds.

Usually fails on: Large inputs wrap around unexpectedly.

Fix: Use wider types, modular arithmetic, or rearranged operations.