LeetCode #3174 — EASY

Clear Digits

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

Solve on LeetCode
The Problem

Problem Statement

You are given a string s.

Your task is to remove all digits by doing this operation repeatedly:

  • Delete the first digit and the closest non-digit character to its left.

Return the resulting string after removing all digits.

Note that the operation cannot be performed on a digit that does not have any non-digit character to its left.

Example 1:

Input: s = "abc"

Output: "abc"

Explanation:

There is no digit in the string.

Example 2:

Input: s = "cb34"

Output: ""

Explanation:

First, we apply the operation on s[2], and s becomes "c4".

Then we apply the operation on s[1], and s becomes "".

Constraints:

  • 1 <= s.length <= 100
  • s consists only of lowercase English letters and digits.
  • The input is generated such that it is possible to delete all digits.
Patterns Used

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 s. Your task is to remove all digits by doing this operation repeatedly: Delete the first digit and the closest non-digit character to its left. Return the resulting string after removing all digits. Note that the operation cannot be performed on a digit that does not have any non-digit character to its left.

Baseline thinking

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

Pattern signal: Stack

Example 1

"abc"

Example 2

"cb34"
Step 02

Core Insight

What unlocks the optimal approach

  • Process string <code>s</code> from left to right, if <code>s[i]</code> is a digit, mark the nearest unmarked non-digit index to its left.
  • Delete all digits and all marked characters.
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 #3174: Clear Digits
class Solution {
    public String clearDigits(String s) {
        StringBuilder stk = new StringBuilder();
        for (char c : s.toCharArray()) {
            if (Character.isDigit(c)) {
                stk.deleteCharAt(stk.length() - 1);
            } else {
                stk.append(c);
            }
        }
        return stk.toString();
    }
}
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

BRUTE FORCE
O(n²) time
O(1) space

For each element, scan left (or right) to find the next greater/smaller element. The inner scan can visit up to n elements per outer iteration, giving O(n²) total comparisons. No extra space needed beyond loop variables.

MONOTONIC STACK
O(n) time
O(n) space

Each element is pushed onto the stack at most once and popped at most once, giving 2n total operations = O(n). The stack itself holds at most n elements in the worst case. The key insight: amortized O(1) per element despite the inner while-loop.

Shortcut: Each element pushed once + popped once → O(n) amortized. The inner while-loop does not make it O(n²).
Coach Notes

Common Mistakes

Review these before coding to avoid predictable interview regressions.

Breaking monotonic invariant

Wrong move: Pushing without popping stale elements invalidates next-greater/next-smaller logic.

Usually fails on: Indices point to blocked elements and outputs shift.

Fix: Pop while invariant is violated before pushing current element.