Code Optimization | Code Optimization Techniques

Code Optimization-

 

Code Optimization is an approach to enhance the performance of the code.

 

The process of code optimization involves-

• Eliminating the unwanted code lines
• Rearranging the statements of the code

 

Advantages-

 

The optimized code has the following advantages-

• Optimized code has faster execution speed.
• Optimized code utilizes the memory efficiently.
• Optimized code gives better performance.

 

Code Optimization Techniques-

 

Important code optimization techniques are-

 

 

1. Compile Time Evaluation
2. Common sub-expression elimination
3. Dead Code Elimination
4. Code Movement
5. Strength Reduction

 

1. Compile Time Evaluation-

 

Two techniques that falls under compile time evaluation are-

 

A) Constant Folding-

 

In this technique,

• As the name suggests, it involves folding the constants.
• The expressions that contain the operands having constant values at compile time are evaluated.
• Those expressions are then replaced with their respective results.

 

Example-

 

Circumference of Circle  = (22/7) x Diameter

 

Here,

• This technique evaluates the expression 22/7 at compile time.
• The expression is then replaced with its result 3.14.
• This saves the time at run time.

 

B) Constant Propagation-

 

In this technique,

• If some variable has been assigned some constant value, then it replaces that variable with its constant value in the further program during compilation.
• The condition is that the value of variable must not get alter in between.

 

Example-

 

pi = 3.14

radius = 10

Area of circle = pi x radius x radius

 

Here,

• This technique substitutes the value of variables ‘pi’ and ‘radius’ at compile time.
• It then evaluates the expression 3.14 x 10 x 10.
• The expression is then replaced with its result 314.
• This saves the time at run time.

 

2. Common Sub-Expression Elimination-

 

The expression that has been already computed before and appears again in the code for computation is called as Common Sub-Expression.

 

In this technique,

• As the name suggests, it involves eliminating the common sub expressions.
• The redundant expressions are eliminated to avoid their re-computation.
• The already computed result is used in the further program when required.

 

Example-

 

Code Before Optimization	Code After Optimization
S1 = 4 x i S2 = a[S1] S3 = 4 x j S4 = 4 x i  // Redundant  Expression S5 = n S6 = b[S4] + S5	S1 = 4 x i S2 = a[S1] S3 = 4 x j S5 = n S6 = b[S1] + S5

 

3. Code Movement-

 

In this technique,

• As the name suggests, it involves movement of the code.
• The code present inside the loop is moved out if it does not matter whether it is present inside or outside.
• Such a code unnecessarily gets execute again and again with each iteration of the loop.
• This leads to the wastage of time at run time.

 

Example-

 

Code Before Optimization	Code After Optimization
for ( int j = 0 ; j < n ; j ++) { x = y + z ; a[j] = 6 x j; }	x = y + z ; for ( int j = 0 ; j < n ; j ++) { a[j] = 6 x j; }

 

4. Dead Code Elimination-

 

In this technique,

• As the name suggests, it involves eliminating the dead code.
• The statements of the code which either never executes or are unreachable or their output is never used are eliminated.

 

Example-

 

Code Before Optimization	Code After Optimization
i = 0 ; if (i == 1) { a = x + 5 ; }	i = 0 ;

 

5. Strength Reduction-

 

In this technique,

• As the name suggests, it involves reducing the strength of expressions.
• This technique replaces the expensive and costly operators with the simple and cheaper ones.

 

Example-

 

Code Before Optimization	Code After Optimization
B = A x 2	B = A + A

 

Here,

• The expression “A x 2” is replaced with the expression “A + A”.
• This is because the cost of multiplication operator is higher than that of addition operator.

 

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