LeetCode #1625 — MEDIUM

Lexicographically Smallest String After Applying Operations

Move from brute-force thinking to an efficient approach using core interview patterns strategy.

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The Problem

Problem Statement

You are given a string s of even length consisting of digits from 0 to 9, and two integers a and b.

You can apply either of the following two operations any number of times and in any order on s:

  • Add a to all odd indices of s (0-indexed). Digits post 9 are cycled back to 0. For example, if s = "3456" and a = 5, s becomes "3951".
  • Rotate s to the right by b positions. For example, if s = "3456" and b = 1, s becomes "6345".

Return the lexicographically smallest string you can obtain by applying the above operations any number of times on s.

A string a is lexicographically smaller than a string b (of the same length) if in the first position where a and b differ, string a has a letter that appears earlier in the alphabet than the corresponding letter in b. For example, "0158" is lexicographically smaller than "0190" because the first position they differ is at the third letter, and '5' comes before '9'.

Example 1:

Input: s = "5525", a = 9, b = 2
Output: "2050"
Explanation: We can apply the following operations:
Start:  "5525"
Rotate: "2555"
Add:    "2454"
Add:    "2353"
Rotate: "5323"
Add:    "5222"
Add:    "5121"
Rotate: "2151"
Add:    "2050"​​​​​
There is no way to obtain a string that is lexicographically smaller than "2050".

Example 2:

Input: s = "74", a = 5, b = 1
Output: "24"
Explanation: We can apply the following operations:
Start:  "74"
Rotate: "47"
​​​​​​​Add:    "42"
​​​​​​​Rotate: "24"​​​​​​​​​​​​
There is no way to obtain a string that is lexicographically smaller than "24".

Example 3:

Input: s = "0011", a = 4, b = 2
Output: "0011"
Explanation: There are no sequence of operations that will give us a lexicographically smaller string than "0011".

Constraints:

  • 2 <= s.length <= 100
  • s.length is even.
  • s consists of digits from 0 to 9 only.
  • 1 <= a <= 9
  • 1 <= b <= s.length - 1

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 of even length consisting of digits from 0 to 9, and two integers a and b. You can apply either of the following two operations any number of times and in any order on s: Add a to all odd indices of s (0-indexed). Digits post 9 are cycled back to 0. For example, if s = "3456" and a = 5, s becomes "3951". Rotate s to the right by b positions. For example, if s = "3456" and b = 1, s becomes "6345". Return the lexicographically smallest string you can obtain by applying the above operations any number of times on s. A string a is lexicographically smaller than a string b (of the same length) if in the first position where a and b differ, string a has a letter that appears earlier in the alphabet than the corresponding letter in b. For example, "0158" is lexicographically smaller than "0190" because the first position they differ is at the third letter, and '5'

Baseline thinking

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

Pattern signal: General problem-solving

Example 1

"5525"
9
2

Example 2

"74"
5
1

Example 3

"0011"
4
2

Related Problems

  • Lexicographically Smallest String After Substring Operation (lexicographically-smallest-string-after-substring-operation)
  • Lexicographically Smallest String After a Swap (lexicographically-smallest-string-after-a-swap)
Step 02

Core Insight

What unlocks the optimal approach

  • Since the length of s is even, the total number of possible sequences is at most 10 * 10 * s.length.
  • You can generate all possible sequences and take their minimum.
  • Keep track of already generated sequences so they are not processed again.
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 #1625: Lexicographically Smallest String After Applying Operations
class Solution {
    public String findLexSmallestString(String s, int a, int b) {
        Deque<String> q = new ArrayDeque<>();
        q.offer(s);
        Set<String> vis = new HashSet<>();
        vis.add(s);
        String ans = s;
        int n = s.length();
        while (!q.isEmpty()) {
            s = q.poll();
            if (ans.compareTo(s) > 0) {
                ans = s;
            }
            char[] cs = s.toCharArray();
            for (int i = 1; i < n; i += 2) {
                cs[i] = (char) (((cs[i] - '0' + a) % 10) + '0');
            }
            String t1 = String.valueOf(cs);
            String t2 = s.substring(n - b) + s.substring(0, n - b);
            for (String t : List.of(t1, t2)) {
                if (vis.add(t)) {
                    q.offer(t);
                }
            }
        }
        return 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^2 × 10^2)
Space
O(n)

Approach Breakdown

BRUTE FORCE
O(n²) time
O(1) space

Two nested loops check every pair or subarray. The outer loop fixes a starting point, the inner loop extends or searches. For n elements this gives up to n²/2 operations. No extra space, but the quadratic time is prohibitive for large inputs.

OPTIMIZED
O(n) time
O(1) space

Most array problems have an O(n²) brute force (nested loops) and an O(n) optimal (single pass with clever state tracking). The key is identifying what information to maintain as you scan: a running max, a prefix sum, a hash map of seen values, or two pointers.

Shortcut: If you are using nested loops on an array, there is almost always an O(n) solution. Look for the right auxiliary state.
Coach Notes

Common Mistakes

Review these before coding to avoid predictable interview regressions.

Off-by-one on range boundaries

Wrong move: Loop endpoints miss first/last candidate.

Usually fails on: Fails on minimal arrays and exact-boundary answers.

Fix: Re-derive loops from inclusive/exclusive ranges before coding.