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13. Roman to Integer
14. Longest Common Prefix
20. Valid Parentheses
26. Remove Duplicates from Sorted Array
35. Search Insert Position
69. Sqrt(x)
70. Climbing Stairs
88. Merge Sorted Array (In-Place)
104. Maximum Depth of Binary Tree
118. Pascal's Triangle
121. Best Time to Buy and Sell Stock
205. Isomorphic Strings
242. Valid Anagram
283. Move Zeroes
345. Reverse Vowels of a String
605. Can Place Flowers
704. Binary Search
796. Rotate String
1071. Greatest Common Divisor of Strings
1299. Replace Elements with Greatest Element on Right Side
1431. Kids With the Greatest Number of Candies
1614. Maximum Nesting Depth of the Parentheses
1752. Check if Array Is Sorted and Rotated
1768. Merge Strings Alternately
1903. Largest Odd Number in String
2965. Find Missing and Repeated Values
hard
25. Reverse Nodes in k-Group
26. Remove Duplicates from Sorted Array
27. Remove Element
42. Trapping Rain Water
51. N-Queens
55. Jump Game
80. Remove Duplicates from Sorted Array II
88. Merge Sorted Array
121. Best Time to Buy and Sell Stock
122. Best Time to Buy and Sell Stock II
189. Rotate Array
274. H-Index
medium
2. Add Two Numbers
3. Longest Substring Without Repeating Characters
5. Longest Palindromic Substring
8. String to Integer (atoi)
11. Container With Most Water
15. 3Sum
17. Letter Combinations of a Phone Number
19. Remove Nth Node From End of List
22. Generate Parentheses
33. Search in Rotated Sorted Array
34. Find First and Last Position of Element in Sorted Array
48. Rotate Image
49. Group Anagrams
50. Pow(x, n)
53. Maximum Subarray
54. Spiral Matrix
56. Merge Intervals
61. Rotate List
73. Set Matrix Zeroes
74. Search a 2D Matrix
75. Sort Colors
78. Subsets
137. Single Number II
138. Copy List with Random Pointer
150. Evaluate Reverse Polish Notation
151. Reverse Words in a String
153. Find Minimum in Rotated Sorted Array
155. Min Stack
162. Find Peak Element
169. Majority Element
198. House Robber
207. Course Schedule
215. Kth Largest Element in an Array
227. Basic Calculator II
236. Lowest Common Ancestor of a Binary Tree
237. Delete Node in a Linked List
238. Product of Array Except Self
451. Sort Characters By Frequency
540. Single Element in a Sorted Array
560. Subarray Sum Equals K
636. Exclusive Time of Functions
875. Koko Eating Bananas
1011. Capacity To Ship Packages Within D Days
1101. The Earliest Moment When Everyone Become Friends
1283. Find the Smallest Divisor Given a Threshold
2140. Solving Questions With Brainpower
3169. Count Days Without Meetings
3481. Apply Substitutions
rotate-array-approach-1
189. Rotate Array (Approach 2 )
189. Rotate Array (Approach 1 )
number-of-islands-approach-1
200. Number of Islands (Approach 2)
200. Number of Islands (Approach 1)
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253. Approach Using Priority Queue
253. Meeting Rooms II
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Calculate Floor & Ceiling
Find Nth Root Of M
Flatten A Linked List
Implement Lower Bound
Implement Upper Bound
Number of occurrence
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The Ultimate Array Pattern Playbook
faqs-hard
Count Inversions in an Array
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Reverse Pairs
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3. 3Sum
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Maximum Subarray
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Majority Element
Next Permutation
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Pascal's Triangle II (Row Generation)
Generate Pascal's Triangle (Full)
Spiral Matrix Traversal
Rearrange Array Elements by Sign
Rotate Image
Sort Colors (Dutch National Flag)
Two Sum
fundamentals
Check if Array is Sorted
Largest Element in an Array
Array Rotation (Left and Right)
Left Rotate Array by One
Linear Search
Max Consecutive Ones
Second Largest Element in an Array
Single Number
logic-building
Missing Number
Intersection of Two Sorted Arrays (with Duplicates)
Move Zeros to End
Remove Duplicates from Sorted Array
Union of Two Sorted Arrays
binary-search
About
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Find Row With Maximum 1'S
Search In A 2D Matrix
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Aggressive Cows
Allocate Books
Find Peak Element
Kth Element Of 2 Sorted Arrays
Minimise Max Distance to Gas Stations
Split Array - Largest Sum
fundamentals
Lower Bound
Binary Search
Upper Bound
logic-building
Count Occurrences in a Sorted Array
Find Minimum in Rotated Sorted Array
Find out how many times the array is rotated
Find First and Last Position of Element in Sorted Array
Floor and Ceil in Sorted Array
Kth Missing Positive Number
Search in Rotated Sorted Array
Search in Rotated Sorted Array II (With Duplicates)
Search Insert Position
Single Element in a Sorted Array
on-answers
Capacity To Ship Packages Within D Days
Find Nth Root of M
Find Square Root of a Number
Smallest Divisor Given a Threshold
Koko Eating Bananas (Minimum Rate)
Minimum Days to Make M Bouquets
Painter's Partition Problem
Split Array Largest Sum
hashing
Theory
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Subarray Sum Equals K
Count Subarrays with Given XOR K
Largest Subarray with 0 Sum
Longest Consecutive Sequence
Longest Subarray with Sum K
recursion
faqs-medium
Combination Sum II (Unique Combinations)
Combination Sum (Unbounded)
Subset Sums
hard
Letter Combinations of a Phone Number
implementation-problems
Generate Parentheses
Power Function: pow(x, n)
Subsets (The Power Set)
subsequence-pattern-problems
Subsequence Sum Existence
Count All Subsequences With Sum K
sorting
Bubble Sort
Insertion Sort
Merge Sort
Quick Sort
Selection Sort
string
Isomorphic Strings
Largest Odd Number in String
Longest Common Prefix
Reverse Words in a String
Code Scratch›leetcode›medium

137. Single Number II

# Question

Given an integer array nums where every element appears exactly three times except for one unique element, which appears exactly once, find and return that single element.

You must implement a solution with a linear runtime complexity (O(n)O(n)O(n)) and use only constant extra space (O(1)O(1)O(1)).

# Solution

# Pattern

Bitwise State Machine (Parallel Bit Counting) Simulating a digital logic circuit using bitwise operations (XOR, AND, NOT) to count bit frequencies modulo kkk across all elements simultaneously.

# How to Identify

  • Elements appear kkk times (where k>2k > 2k>2), and exactly one element appears a different number of times.
  • Rigid constraints mandate O(1)O(1)O(1) auxiliary space, precluding the use of frequency hash tables.
  • The requirement calls for low-level, high-performance bitstream parsing.

# Description

Step-by-step explanation:

  • Step 1: Establish Bit Trackers. To count up to 3 occurrences per bit position, a 3-state transition system (00→01→10→0000 \rightarrow 01 \rightarrow 10 \rightarrow 0000→01→10→00) is needed. This requires two variables: ones and twos.
  • Step 2: Initialize States. Initialize both tracking registers ones and twos to 0.
  • Step 3: Linear Pass. Loop through each number num in the array exactly once.
  • Step 4: Update States. For each number, update the bits in our tracking states using bitwise logic gates:
    1. ones = (ones ^ num) & ~twos; (Capture bits appearing for the first time, or resetting if appearing a third time).
    2. twos = (twos ^ num) & ~ones; (Capture bits appearing for the second time).
  • Step 5: Output. Elements appearing three times cycle fully back to state 00. The unique element leaves its bits trapped in the first state container. Return ones.

# The Intuition

Think of this as constructing a row of 3-way cyclic light switches for each of the 32 bit positions.

Every time a 1 bit hits a position, its switch clicks forward: State 00 (Seen 0 times)→State 01 (Seen 1 time)→State 10 (Seen 2 times)→State 00 (Seen 3 times)\text{State } 00 \text{ (Seen 0 times)} \rightarrow \text{State } 01 \text{ (Seen 1 time)} \rightarrow \text{State } 10 \text{ (Seen 2 times)} \rightarrow \text{State } 00 \text{ (Seen 3 times)}State 00 (Seen 0 times)→State 01 (Seen 1 time)→State 10 (Seen 2 times)→State 00 (Seen 3 times)

  • The expression ones ^ num toggles the bit between appearing an odd and even number of times.
  • The masking expressions & ~twos and & ~ones act as safety interlocks. They prevent a bit from activating state 1 if it is currently moving into state 2, or resetting state 2 if it is cycling back down to 0.
  • Since all bits are processed in parallel via the CPU's word register, we run this light switch board across the entire stream in a single pass.

# Complexity

LabelWorstAverage
Time ComplexityO(n)O(n)O(n)O(n)O(n)O(n)
Space ComplexityO(1)O(1)O(1)O(1)O(1)O(1)

# Time Complexity

O(n)O(n)O(n). The array is parsed in a single linear pass. Each element triggers only 6 basic bitwise operations, running with a constant factor coefficient of 1.

# Space Complexity

O(1)O(1)O(1). Auxiliary memory allocation is locked to two local tracking primitive integers (ones and twos), independent of array scaling.

# Code

class Solution {
    /**
     * Finds the element that appears exactly once when all others appear three times.
     * Uses bitwise parallel state reduction to optimize the constant execution overhead.
     */
    public int singleNumber(int[] nums) {
        // Tracks bits that have appeared 1 time (modulo 3)
        int ones = 0; 
        // Tracks bits that have appeared 2 times (modulo 3)
        int twos = 0; 
        
        for (int num : nums) {
            // Update 'ones' only if the bit isn't already part of a pair tracked in 'twos'
            ones = (ones ^ num) & ~twos;
            
            // Update 'twos' only if the bit isn't actively held in the newly calculated 'ones'
            twos = (twos ^ num) & ~ones;
        }
        
        // Elements seen 3 times clear out to 0. The single item remains in 'ones'.
        // If the unique item appeared twice, we would return 'twos'.
        return ones;
    }
}

# Caveats

  • Fragile State Alignment: The ordering of the statements is critical. If you alter the assignment sequencing without adjusting the interlocking components (e.g., trying to calculate twos first using the historical ones), the state logic will collapse.

  • Strict Multiplicity: This exact bitwise combination logic is hardcoded specifically for frequencies of three (3). It cannot handle unaligned arrays without altering the state truth tables entirely.

# Concepts to Think About

  • Two's Complement Representation: Understanding why signed integers and bit shifting behave consistently at the register boundaries.

  • K-Bit Counter Simulation: Generalizing bit counters using combinations of boolean expressions derived via Karnaugh Maps (K-Maps).

  • Parallel Processing via Word Size: How bitwise gates leverage the processor's underlying architectural data registers to avoid itemized indexing loops.

# Logical Follow-up

Question: What if the unique element appears exactly twice instead of once?

Solution: The elements appearing three times will cycle back to 00. The element appearing twice will be caught in state 10. Therefore, you would return twos instead of ones.

Question: How can we generalize this approach if every element appears k times and one appears exactly once?

Solution: Determine the number of tracking bits required (⌈log₂(k)⌉). Maintain m variables (bit1, bit2, ... bitM). Use a bitwise mask representing the binary layout of k to identify when the counters reach k, then apply an AND NOT operation across all tracking variables to clear the state back to zero.

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CONTENTS
QuestionSolutionPatternHow to IdentifyDescriptionThe IntuitionComplexityCodeCaveatsConcepts to Think AboutLogical Follow-up