Implementing a lexical analyzer in Compiler Design - Time & Space Complexity
When building a lexical analyzer, it is important to understand how the time it takes to process input grows as the input gets larger.
We want to know how the analyzer's work increases as the source code size increases.
Analyze the time complexity of the following code snippet.
function lexicalAnalyzer(input) {
let position = 0;
while (position < input.length) {
let token = getNextToken(input, position);
position += token.length;
}
}
function getNextToken(input, start) {
// scans characters from start to identify next token
// returns token with its length
}
This code reads the input string from start to end, extracting tokens one by one.
Identify the loops, recursion, array traversals that repeat.
- Primary operation: Scanning characters in the input string to identify tokens.
- How many times: Each character is examined once as the position moves forward through the input.
As the input size grows, the analyzer processes more characters, so the work grows roughly in direct proportion.
| Input Size (n) | Approx. Operations |
|---|---|
| 10 | About 10 character scans |
| 100 | About 100 character scans |
| 1000 | About 1000 character scans |
Pattern observation: The number of operations grows linearly with input size.
Time Complexity: O(n)
This means the time to analyze grows directly in proportion to the length of the input.
[X] Wrong: "The lexical analyzer checks every character multiple times, so it must be slower than linear."
[OK] Correct: The analyzer moves forward through the input without going back, so each character is processed once, keeping the work linear.
Understanding how lexical analyzers scale with input size shows you can reason about program efficiency, a key skill in many coding challenges and real projects.
"What if the lexical analyzer had to backtrack and re-examine characters? How would the time complexity change?"