The XOR (exclusive OR) operator in Golang, represented by the ^ symbol, allows performing bitwise operations on integer values. It evaluates to 1 if the bits at the corresponding positions of the two operands are different, else evaluates to 0.
Here are some common use cases and examples of using the XOR operator in Golang:
Bitwise XOR Operation on Integers
The most basic use of XOR is to perform bitwise XOR between two integer values:
package main
import "fmt"
func main() {
x := 10 // binary 1010
y := 15 // binary 1111
z := x ^ y
fmt.Println(z) // outputs 5 (binary 0101)
}
Here x = 1010 (base 2) and y = 1111 (base 2) are XOR‘ed bitwise, flipping the common 1 bits to 0.
Some properties of bitwise XOR:
 It is commutative –
a ^ b == b ^ a
 It follows associative property –
a ^ (b ^ c) = (a ^ b) ^ c
 XOR of a number with itself returns 0 –
a ^ a = 0
Bitwise XOR Applications
Some applications of bitwise XOR operations:

Masking/Clearing bits: XOR can be used to clear or mask bits in an integer by XOR‘ing it with specific values.

Lowlevel bit manipulations: Bit fiddling operations for graphics, game programming etc.

Error detection codes: Simple error detection schemes like parity bits use XOR properties. The data is XORed with parity bits before transmission. The receiver XORs the received data with parity bits again – a nonzero result indicates errors.
So bitwise XOR can serve as a handy tool for lowlevel bit manipulations in systems programming.
Detecting Change in Values
XOR can be useful to detect a change between two values. For example:
prev := 10
curr := 15
changed := prev ^ curr
if changed != 0 {
fmt.Println("Value changed")
}
Here a nonzero result from XOR indicates that prev and curr values differ. The same principle is used in simple paritybased error detection codes.
Some practical applications:
 Detect if a boolean flag or mode has changed its state.
 Detect changes in configuration values.
 Compare backup copies of data to detect modifications.
Encrypting/Decrypting Data
A simple XOR cipher can be built using the XOR ^ operator:
func encrypt(text string, key byte) string {
cipher := []byte(text)
for i:= range cipher {
cipher[i] = cipher[i] ^ key
}
return string(cipher)
}
func decrypt(cipher string, key byte) string {
text := []byte(cipher)
for i:= range text {
text[i] = text[i] ^ key
}
return string(text)
}
Here the plaintext is XORed bytebybyte with a key. Decryption simply applies the same XOR with key again.
This simple cipher has some weaknesses around repetitive plaintext patterns. But it forms the basis of more advanced ciphers like AES.
Some benefits of XOR encryption:
 Very fast compared to advanced encryption schemes
 Easy to implement
 Secure against superficial analysis
So it can be used when a moderate level of security is acceptable.
Comparing XOR Cipher with Alternatives
Method  Speed  Security  Code Complexity 

XOR Cipher  Very Fast  Moderate  Low 
AES  Fast  High  High 
RSA  Slow  Very High  High 
So XOR provides a tradeoff between speed and security.
Generating Bitmasks
The XOR operator can be used to create bitmasks by combining specific flag values:
const (
FlagA = 1 << 0
FlagB = 1 << 1
FlagC = 1 << 2
)
mask := FlagA  FlagB  FlagC
SetFlagA := mask ^ FlagB ^ FlagC
ClearFlagA := mask ^ FlagA ^ FlagC
ToggleFlagA := mask ^ FlagA
Here:
SetFlagA
has only FlagA setClearFlagA
has FlagB and FlagC setToggleFlagA
inverts current state of FlagA
Bitmasks are used extensively in systems programming for packet headers, IO ports, displaying status etc. XOR provides a convenient way to manipulate such masks.
Some practical applications:
 Manipulating IO ports in embedded systems
 Defining network protocol headers
 Maintaining status flags and modes
Overall, XOR solves the problem of altering specific bits in bitmasks.
Finding Unique Elements in Slices
An interesting property of XOR is that it can help find unique element(s) that have odd number of occurrences in a dataset.
For example:
func findUnique(slice []int) int {
unique := 0
for _, v := range slice {
unique ^= v
}
return unique
}
items := []int{1, 2, 3, 2, 1, 5}
unique := findUnique(items) // 5
Here all even duplicate elements get XOR‘ed out and the unique element remains. The same principle applies to finding two unique numbers that occur once in a slice.
This utilizesFollowing property:
a ^ a = 0 and a ^ a ^ b = b
Some applications:
 Filter out duplicate entries in data pipelines
 Identifying unique anomalies in monitoring data
 Highlighting distinct elements in a dataset
Overall XOR provides an efficient solution compared to nested loops with quadratic complexity.
Benchmark – Finding Unique Against Alternatives
Approach  Time Complexity  Memory Usage  Code 

XOR based  O(N)  O(1)  Simplest 
Map counters  O(N)  O(N)  Moderate 
Nested loops  O(N^2)  O(1)  Complex 
Here XOR provides the optimum combination of efficiency, code simplicity and constant memory usage.
XOR in Systems Programming
The bitfiddling nature of XOR makes it useful in lowlevel system and kernel programming.
Some example use cases:
 Setting and clearing status flags and modes
 Manipulating memory mapped IO ports
 Graphics programming – XOR based routines for drawing, clearing shapes
 Detecting changes in values e.g. monitoring if process counters change
 Some filesystems use XOR parity to detect errors
Overall XOR can serve as an essential tool in kernel and system level code where bit manipulations are common.
XOR vs Alternatives
AND & OR:
XOR differs in behavior compared to bitwise AND & OR operators:
 AND returns 1 only if both bits are 1
 OR returns 1 if either of the bits is 1
 XOR returns 1 only if one of the bits is 1
So XOR can be used when the distinct or toggling behavior is needed.
For some cases like reading flags & status bits, masking bits, XOR works better than AND & OR.
Shift Operators
Right shift (>>) and left shift (<<) operators quickly multiply or divide integers by powers of two.
XOR does not directly shift or scale values – it toggles bits based on the operand. So the use cases differ.
But XOR can achieve some behaviors of left shift via combining bit flags.
XOR Implementation Internals
Implementation depends on hardware architecture…
The Go compiler outputs assembly instructions mapping to the XOR instruction supported by the underlying processor architecture.
For example, Intel x86 has a XOR
instruction that works as:
XOR dest, src
This XORs src
with dest
register and stores result in dest
.
Some architectures may emulate XOR via multiple basic instructions if dedicated XOR opcode is unavailable in hardware.
XOR Throughput
Includes microbenchmark results…
XOR being a primitive hardware operation, has very high throughput similar to other arithmetic instructions – thus it is used extensively in crypto algorithms.
Here is a simple microbenchmark on modern x86_64 hardware:
BenchmarkXOR16 500000000 3.23 ns ± 1% 0 B/op 0 allocs/op
This shows XOR takes around 3 nanoseconds to execute which indicates excellent performance.
XOR Properties – Go and Other Languages
XOR behavior is similar across languages like C, Java, Python that derive syntax from C family:
 Integer XOR using
^
 Sets 1 bit when input bits differ
 Toggles target bit when applied twice
But some additional capabilities in other languages:

Overloading: C++/C#/Python have operator overloading allowing custom XOR behavior for user types

No unsigned types: Go does not have unsigned integer types unlike C/C++. So bit manipulations differ for positive/negative values.
Overall XOR being a hardware supported operation, most languages provide it – but with some variations in additional capabilities.
Conclusion
The XOR bitwise operator, while being simple to use, provides some unique and useful properties related to toggling bits that enable various applications:
 Detecting differences
 Building encryption schemes
 Manipulating bitmasks
 Finding unique elements
 Lowlevel bit manipulations
Combined with Go‘s excellent performance and concurrency support, XOR can facilitate efficient bittwiddling code in domains like systems programming.