Code Optimization Techniques

Code Optimization Techniques

Code optimization is a phase in compiler design aimed at improving the intermediate code to make the final executable more efficient, without changing the program’s output or logic.

Optimization can target:

• Execution speed
• Memory usage
• Power consumption (in embedded systems)

There are two types:

• Machine-independent optimization (applied on IR)
• Machine-dependent optimization (applied during or after code generation)

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🔹 1. Constant Folding

• Description: Compile-time evaluation of constant expressions.

• Benefit: Saves runtime computation.

Example:

int x = 3 * 5;

Optimized to:

int x = 15;

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🔹 2. Constant Propagation

• Description: Replaces variables with known constant values.

• Benefit: Simplifies expressions and exposes more optimization opportunities.

Example:

int a = 10;
int b = a + 5;

Optimized to:

int b = 10 + 5;

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🔹 3. Common Sub-expression Elimination (CSE)

• Description: Eliminates duplicate expressions already computed.

• Benefit: Reduces redundant calculations.

Example:

t1 = a + b;
t2 = a + b;

Optimized to:

t1 = a + b;
t2 = t1;

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🔹 4. Dead Code Elimination

• Description: Removes code that does not affect program output.

• Benefit: Reduces program size and increases speed.

Example:

int x = 10;
x = 20;   // x = 10 is dead code

Optimized to:

int x = 20;

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🔹 5. Strength Reduction

• Description: Replaces expensive operations with cheaper equivalents.

• Benefit: Improves execution time.

Example:

x = a * 2;      // multiplication

Optimized to:

x = a + a;      // faster addition

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🔹 6. Loop Invariant Code Motion

• Description: Moves code that computes the same result in every iteration outside the loop.

• Benefit: Reduces redundant computations inside loops.

Example:

for (int i = 0; i < n; i++) {
    x = a * b;
    arr[i] = x + i;
}

Optimized to:

x = a * b;
for (int i = 0; i < n; i++) {
    arr[i] = x + i;
}

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🔹 7. Copy Propagation

• Description: Replaces occurrences of variables that are copies of others.

• Benefit: Enables further optimizations like dead code elimination.

Example:

b = a;
c = b + 1;

Optimized to:

c = a + 1;

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🔹 8. Peephole Optimization

• Description: Looks at small sliding windows (“peepholes”) of instructions to perform local optimizations.

• Benefit: Simple and effective for final-stage optimization.

Example:

MOV R1, R2
MOV R2, R1

Optimized to: (No effect)

// Removed (they cancel each other)

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Summary Table

Technique	Purpose	Key Benefit
Constant Folding	Evaluate expressions at compile time	Faster execution
Constant Propagation	Replace vars with constants	Exposes more optimizations
Common Sub-expression Elim.	Avoid recomputation	Reduces redundant code
Dead Code Elimination	Remove unused code	Smaller, faster code
Strength Reduction	Use cheaper operations	Improves performance
Loop Invariant Code Motion	Move code out of loops	Reduces loop overhead
Copy Propagation	Replace variable copies	Simplifies expressions
Peephole Optimization	Small local improvements	Refines final output