Lab for Automated Reasoning and Analysis LARA

Hand-Written Lexical Analyzer for While

Lexical Analyzer

Also called: lexer, scanner, or tokenizer

Transforms sequence of characters

w h i l e ( c o u n t < 1 0 ) { LF c o u n t =

into sequence of tokens

while ( count < 10 ) { count =

Interfaces for Lexer

In practice, we read characters and generate tokens on demand

Work with streams instead of sequences, with procedures like

  • current - return current element in stream
  • next - advance the current element

Lexer uses input stream of characters

Lexer provides:

Identifiers and Keywords

Regular expression for identifiers: letter (letter|digit)*

if (isLetter) {
  b = new StringBuffer
  while (isLetter || isDigit) {
     b.append(ch.current)
     ch.next
  }
}

Keywords look like identifiers, but are designated as keywords.

One implementation: a constant Map from strings to keyword token numbers

  • if not in map, then it is ordinary identifier

Integer Constants

Regular expression for numbers: digit digit*

if (isDigit) {
  k = 0
  while (isDigit) {
     k = 10 * k + digitToNumber(ch.current)
     ch.next
  }
}

For digitToNumber etc see ASCII

Skipping Comments

if (ch.current='/') {
  ch.next
  if (ch.current='/') {
     while (!isEOL && !isEOF) {
       ch.next
     }
  }
}

How about nested comments?

  • need a counter

Longest Match Rule

There are multiple ways to break character stream into tokens.

Consider language with identifiers, ⇐, <, =

Consider this character stream:

interpreters <= compilers

These are some ways to analyze it into tokens:

  1. ID(interpreters) LEQ ID(compilers)
  2. ID(inter) ID(preters) LESS AssignEQ ID(com) ID(pilers)
  3. ID(i) ID(nte) ID(rpre) ID(ter) LESS AssignEQ ID(co) ID(mpi) ID(lers)

This is resolved by longest match rule:

  • if multiple tokens could follow, take the longest token possible

Note: consider language with only three operators:

  1. '<'
  2. '<='
  3. '=>'

Then for the sequence '<=>' the lexer will report an error:

  • first token is '<=
  • second token is not recognized

In practice, this is not a problem, we can always use space.

Token Priority

What if our token classes intersect?

Longest match rule does not help

Example: a keyword is usually also an identifier

Priority: order all tokens, if in doubt take one with higher priority

  • if it looks both like keyword and like an identifier, then it is a keyword

Combining Lexers for All Tokens

How do we know when we are supposed to analyze string, when integer sequence etc?

For manual construction: use lookahead (next symbol in stream) to decide on token class

  • compute first(e) - symbols with which e can start
  • check in which first(e) current token is

Given regular expression e, how to compute first(e)?

  • use automata (we will see this next)
  • rules that directly computate them (also work for grammars, we will see them for parsing)

Examples of first(e) computation:

  • first(ab*) = a
  • first(ab*|c) = {a,c}
  • first(a*b*c) = {a,b,c}
  • first( (cb|a*c*)d*e) ) =

Notion of nullable ( r ) - whether $\varepsilon \in r$, that is, whether empty string belongs to the regular language.

Sometimes first(e1) and first(e2) overlap for two different token classes:

  • we must remember where we were and go back, or work on recognizing multiple tokens at the same time
  • example: comment begins with division sign, so we should not 'drop' division token when checking for comment!

A partial lexer: Lexer.scala and LexerTest.scala

 
cc09/hand-written_scanner_for_while_language.txt · Last modified: 2010/09/28 16:56 by vkuncak
 
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