Global optimization techniques in Compiler Design - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main goal of global optimization techniques in compiler design?

The main goal is to improve the performance and efficiency of the entire program by optimizing code across different parts, not just within a single block or function.

beginner

Explain the difference between local and global optimization.

Local optimization focuses on improving small sections of code, like a single block, while global optimization looks at the whole program or large parts of it to find better improvements.

intermediate

What is 'constant propagation' in global optimization?

Constant propagation is a technique where the compiler replaces variables that have constant values with those values throughout the program to simplify and speed up the code.

beginner

How does 'dead code elimination' improve program efficiency?

Dead code elimination removes parts of the code that never affect the program's output, reducing size and improving speed.

intermediate

What role does 'loop invariant code motion' play in global optimization?

It moves calculations that do not change inside a loop to outside the loop, so they are done only once, saving time during repeated loop executions.

Which of the following is a global optimization technique?

A Peephole optimization

B Register allocation

C Instruction scheduling

D Constant propagation

Constant propagation is a global optimization because it replaces constants throughout the program, while others are more local or machine-level.

What does dead code elimination remove?

A Code that never runs or affects output

B Loops that run too many times

C Variables with constant values

D Function calls

Dead code elimination removes code that does not affect the program's behavior or output.

Loop invariant code motion helps by:

A Moving code inside loops

B Moving code outside loops if it doesn't change

C Removing loops

D Duplicating loop code

It moves calculations that do not change inside loops to outside, reducing repeated work.

Global optimization techniques are applied:

A Only within a single basic block

B Only during machine code generation

C Across multiple blocks or functions

D Only at runtime

Global optimizations analyze and improve code across multiple blocks or functions.

Which optimization replaces variables with their known constant values?

A Constant propagation

B Inlining

C Loop unrolling

D Dead code elimination

Constant propagation replaces variables with constant values to simplify code.

Describe three common global optimization techniques and how they improve program performance.

Think about how each technique reduces unnecessary work or simplifies code.

Explain why global optimization is more powerful than local optimization in compiler design.

Consider how looking at the entire program helps find more opportunities.

Practice

1. What is the main goal of global optimization techniques in compiler design?

easy

A. To fix syntax errors in the code

B. To translate code into machine language

C. To improve the performance of the entire program

D. To check for logical errors during runtime

Solution

1. Step 1: Understand the purpose of global optimization

   Global optimization aims to improve the whole program's efficiency, not just parts of it.

2. Step 2: Differentiate from other compiler tasks

   Fixing syntax or translating code are separate compiler phases, not optimization.

3. Final Answer:

   To improve the performance of the entire program -> Option C

4. Quick Check:

   Global optimization = whole program improvement [OK]

Hint: Global optimization means improving the entire program [OK]

Common Mistakes:

• Confusing optimization with syntax checking
• Thinking optimization only fixes errors
• Mixing code translation with optimization

2. Which of the following is a valid example of a global optimization technique?

easy

A. Register allocation

B. Loop-invariant code motion

C. Lexical analysis

D. Syntax parsing

Solution

1. Step 1: Identify global optimization techniques

   Loop-invariant code motion moves calculations out of loops to avoid repeated work.

2. Step 2: Exclude non-optimization tasks

   Syntax parsing and lexical analysis are earlier compiler phases; register allocation is a resource management step.

3. Final Answer:

   Loop-invariant code motion -> Option B

4. Quick Check:

   Moving code out of loops = loop-invariant code motion [OK]

Hint: Look for techniques that reduce repeated work in code [OK]

Common Mistakes:

• Confusing parsing with optimization
• Thinking register allocation is optimization
• Mixing compiler phases

3. Consider this code snippet before optimization:

for (int i = 0; i < n; i++) {
  int x = 5 * 10;
  sum += x;
}

Which global optimization technique can improve this code?

medium

A. Inline expansion

B. Dead code elimination

C. Constant folding

D. Loop-invariant code motion

Solution

1. Step 1: Identify repeated calculation inside the loop

   The expression 5 * 10 does not depend on i and is recalculated every iteration.

2. Step 2: Apply loop-invariant code motion

   Move int x = 5 * 10; outside the loop to avoid repeated calculation.

3. Final Answer:

   Loop-invariant code motion -> Option D

4. Quick Check:

   Move constant calculation out of loop = loop-invariant code motion [OK]

Hint: Move calculations that don't change out of loops [OK]

Common Mistakes:

• Choosing constant folding (done once, but not moving code)
• Confusing dead code elimination with removing unused code
• Thinking inline expansion applies here

4. Identify the error in this global optimization attempt:

int sum = 0;
for (int i = 0; i < n; i++) {
  int x = i * 2;
}
sum += x;

medium

A. Variable x is used outside its scope

B. Loop condition is incorrect

C. Sum variable is not initialized

D. No optimization applied

Solution

1. Step 1: Check variable scope of x

   The variable x is declared inside the loop and cannot be accessed outside it.

2. Step 2: Analyze usage of x after the loop

   Using x after the loop causes a scope error, preventing optimization.

3. Final Answer:

   Variable x is used outside its scope -> Option A

4. Quick Check:

   Variable scope error = using inside variable outside loop [OK]

Hint: Check if variables are used only where declared [OK]

Common Mistakes:

• Ignoring variable scope rules
• Assuming sum is uninitialized
• Thinking loop condition is wrong

5. Given a program with multiple repeated calculations and unused variables scattered across functions, which combination of global optimization techniques would best improve performance?

hard

A. Dead code elimination and loop-invariant code motion

B. Constant folding and syntax checking

C. Register allocation and lexical analysis

D. Inlining and parsing

Solution

1. Step 1: Identify techniques for removing unused code and repeated calculations

   Dead code elimination removes unused variables; loop-invariant code motion moves repeated calculations out of loops.

2. Step 2: Exclude unrelated compiler tasks

   Syntax checking, lexical analysis, parsing, and register allocation are not global optimizations for code improvement.

3. Final Answer:

   Dead code elimination and loop-invariant code motion -> Option A

4. Quick Check:

   Remove unused + move repeated = dead code elimination + loop-invariant motion [OK]

Hint: Combine removing unused code and moving repeated code out [OK]

Common Mistakes:

• Confusing compiler phases with optimization
• Choosing unrelated techniques like parsing
• Ignoring the need for multiple optimizations