The Neighboring Bitwise XOR problem gives you a binary array derived where derived[i] = original[i] XOR original[(i+1) % n]. Given this derived array, determine whether a valid original binary array could have produced it. This Neighboring Bitwise XOR coding problem tests circular XOR constraint reasoning and bit manipulation.
Amazon and Google ask this to test the ability to reason about circular XOR constraints mathematically, rather than by simulation. The key insight — that the XOR of all derived values must equal 0 for a valid original to exist — requires understanding XOR properties deeply. The array and bit manipulation interview pattern is directly demonstrated.
XOR parity check. If we XOR all values in derived, each original[i] appears exactly twice in the expansion (once as derived[i-1]'s second term and once as derived[i]'s first term). Since x XOR x = 0, the XOR of all derived values equals 0 if and only if a valid original exists. Simply return XOR(derived) == 0.
derived = [1, 1, 0]. XOR all: 1^1^0 = 0 → true (valid original exists). Verification: if original[0]=0, then original[1] = 0^1=1, original[2]=1^1=0. Check: derived[2]=0^0=0 ✓.
derived = [1, 1]. XOR: 1^1 = 0 → true. derived = [1, 0]. XOR: 1^0 = 1 ≠ 0 → false.
Circular XOR problems often have elegant parity arguments. When a problem defines a derived sequence as XOR of consecutive pairs in a circular array, the XOR of the entire derived sequence collapses to 0 (if valid). Practice similar XOR parity problems — "does a binary array of operations have a consistent solution?" — to build intuition for when XOR constraints can be verified in O(1) using global parity rather than simulation.
| Title | Difficulty | Topics | LeetCode |
|---|---|---|---|
| Count Triplets with Even XOR Set Bits II | Medium | Solve | |
| Decode XORed Permutation | Medium | Solve | |
| Maximum K to Sort a Permutation | Medium | Solve | |
| Single Number III | Medium | Solve | |
| Single Number II | Medium | Solve |