Parse trees and derivations in Compiler Design - Time & Space Complexity

Time Complexity: Parse trees and derivations

O(n^3)

Understanding Time Complexity

When building parse trees or derivations, we want to know how the work grows as the input size increases.

We ask: How much more time does it take to build these trees when the input gets bigger?

Scenario Under Consideration

Analyze the time complexity of the following parse tree construction process.

function buildParseTree(input):
  if input is a single token:
    return leaf node
  else:
    for each production rule:
      if rule matches input prefix:
        leftTree = buildParseTree(matched part)
        rightTree = buildParseTree(remaining part)
        return new tree node with leftTree and rightTree

This code recursively builds a parse tree by splitting the input according to grammar rules.

Identify Repeating Operations

Look for repeated steps that take most time.

• Primary operation: Recursive calls to build subtrees for parts of the input.
• How many times: Potentially once for each substring of the input, depending on grammar.

How Execution Grows With Input

As input length grows, the number of substrings to consider grows quickly.

Input Size (n)	Approx. Operations
10	About 1,000 recursive calls
100	About 1 million recursive calls
1000	About 1 billion recursive calls

Pattern observation: The work grows roughly with the cube of input size because many substrings are checked.

Final Time Complexity

Time Complexity: O(n^3)

This means the time to build the parse tree grows roughly with the cube of the input length, so doubling input size can make it take about eight times longer.

Common Mistake

[X] Wrong: "Building a parse tree takes time just proportional to input length because we only read tokens once."

[OK] Correct: The parser often tries many ways to split the input, so it revisits parts multiple times, making the work grow faster than input length.

Interview Connect

Understanding how parse tree building scales helps you explain parsing efficiency and challenges clearly, a useful skill in compiler design discussions.

Self-Check

"What if we used memoization to save results of subproblems? How would the time complexity change?"

Practice

1. What does a parse tree represent in compiler design?

easy

A. The list of tokens from lexical analysis

B. The sequence of machine instructions generated

C. The memory layout of variables

D. The hierarchical structure of a sentence based on grammar rules

Solution

1. Step 1: Understand the role of parse trees

   Parse trees visually show how a sentence is broken down into parts according to grammar rules.

2. Step 2: Differentiate from other compiler components

   Unlike tokens or machine instructions, parse trees focus on syntax structure, not code or memory.

3. Final Answer:

   The hierarchical structure of a sentence based on grammar rules -> Option D

4. Quick Check:

   Parse tree = hierarchical structure [OK]

Hint: Parse tree = sentence structure, not code or memory [OK]

Common Mistakes:

• Confusing parse tree with tokens list
• Thinking parse tree shows machine code
• Mixing parse tree with memory layout

2. Which of the following is the correct way to represent a derivation step in grammar?

easy

A. S → aSb

B. S = a + Sb

C. S := aSb

D. S <- aSb

Solution

1. Step 1: Identify standard grammar notation

   In grammar, derivations use the arrow symbol → to show how a symbol expands.

2. Step 2: Check each option's correctness

   S → aSb uses → correctly; others use assignment or incorrect symbols.

3. Final Answer:

   S → aSb -> Option A

4. Quick Check:

   Derivation uses → symbol [OK]

Hint: Look for arrow → in grammar rules [OK]

Common Mistakes:

• Using assignment symbols instead of arrow
• Confusing programming assignment with grammar rules
• Using incorrect arrow symbols

3. Given the grammar rules:
S → aSb | ab
What is the leftmost derivation of the string aabb?

medium

A. S → aSb → aaSbb → aabb

B. S → ab → aabb

C. S → aSb → ab

D. S → aSb → aab

Solution

1. Step 1: Apply leftmost derivation rules

   Start with S, replace leftmost S using S → aSb to get aSb.

2. Step 2: Apply rule again to inner S

   Replace inner S with aSb again to get aaSbb, then replace S with ab to get aabb.

3. Final Answer:

   S → aSb → aaSbb → aabb -> Option A

4. Quick Check:

   Leftmost derivation = S → aSb → aaSbb → aabb [OK]

Hint: Replace leftmost non-terminal first [OK]

Common Mistakes:

• Replacing rightmost non-terminal first
• Skipping intermediate derivation steps
• Confusing production rules

4. Identify the error in this derivation sequence for grammar S → aSb | ab to produce aabb:
S → aSb → ab → aabb

medium

A. Used wrong production rule for S

B. String aabb cannot be derived from this grammar

C. Incorrectly replaced inner S with ab too early

D. No error, derivation is correct

Solution

1. Step 1: Analyze the derivation steps

   The derivation replaces S with aSb, then immediately replaces S with ab but in the wrong position.

2. Step 2: Check correctness of replacement order

   The inner S should be replaced after expanding the outer S fully; here it skips a step causing incorrect string formation.

3. Final Answer:

   Incorrectly replaced inner S with ab too early -> Option C

4. Quick Check:

   Early replacement error = Incorrectly replaced inner S with ab too early [OK]

Hint: Check order of non-terminal replacements carefully [OK]

Common Mistakes:

• Replacing non-terminals out of order
• Assuming all strings are derivable
• Ignoring grammar rules sequence

5. Consider the grammar:
E → E + T | T
T → T * F | F
F → (E) | id
Which parse tree correctly represents the expression id + id * id?

hard

A. Parse tree where '*' is root, left child '+' with two 'id' leaves, right child 'id'

B. Parse tree where '+' is root, left child 'id', right child '*' with two 'id' leaves

C. Parse tree with '+' as root and both children as 'id'

D. Parse tree with '*' as root and both children as 'id'

Solution

1. Step 1: Understand operator precedence in grammar

   Multiplication (*) has higher precedence than addition (+), so '*' groups tighter.

2. Step 2: Build parse tree accordingly

   The root is '+', left child is 'id', right child is '*', which has two 'id' children.

3. Final Answer:

   Parse tree where '+' is root, left child 'id', right child '*' with two 'id' leaves -> Option B

4. Quick Check:

   Operator precedence respected = Parse tree where '+' is root, left child 'id', right child '*' with two 'id' leaves [OK]

Hint: Remember * binds tighter than + in parse trees [OK]

Common Mistakes:

• Ignoring operator precedence
• Swapping '+' and '*' as root
• Misplacing leaves in parse tree