- Compiler Design Tutorial
- Compiler Design - Home
- Compiler Design - Overview
- Compiler Design - Architecture
- Compiler Design - Phases of Compiler
- Compiler Design - Lexical Analysis
- Compiler - Regular Expressions
- Compiler Design - Finite Automata
- Compiler Design - Syntax Analysis
- Compiler Design - Types of Parsing
- Compiler Design - Top-Down Parser
- Compiler Design - Bottom-Up Parser
- Compiler Design - Error Recovery
- Compiler Design - Semantic Analysis
- Compiler - Run-time Environment
- Compiler Design - Symbol Table
- Compiler - Intermediate Code
- Compiler Design - Code Generation
- Compiler Design - Code Optimization

- Compiler Design Useful Resources
- Compiler Design - Quick Guide
- Compiler Design - Useful Resources
- Compiler Design - Discussion

- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who

# Compiler Design - Regular Expressions

The lexical analyzer needs to scan and identify only a finite set of valid string/token/lexeme that belong to the language in hand. It searches for the pattern defined by the language rules.

Regular expressions have the capability to express finite languages by defining a pattern for finite strings of symbols. The grammar defined by regular expressions is known as **regular grammar**. The language defined by regular grammar is known as **regular language**.

Regular expression is an important notation for specifying patterns. Each pattern matches a set of strings, so regular expressions serve as names for a set of strings. Programming language tokens can be described by regular languages. The specification of regular expressions is an example of a recursive definition. Regular languages are easy to understand and have efficient implementation.

There are a number of algebraic laws that are obeyed by regular expressions, which can be used to manipulate regular expressions into equivalent forms.

## Operations

The various operations on languages are:

Union of two languages L and M is written as

L U M = {s | s is in L or s is in M}

Concatenation of two languages L and M is written as

LM = {st | s is in L and t is in M}

The Kleene Closure of a language L is written as

L* = Zero or more occurrence of language L.

## Notations

If r and s are regular expressions denoting the languages L(r) and L(s), then

**Union**: (r)|(s) is a regular expression denoting L(r) U L(s)**Concatenation**: (r)(s) is a regular expression denoting L(r)L(s)**Kleene closure**: (r)* is a regular expression denoting (L(r))*(r) is a regular expression denoting L(r)

## Precedence and Associativity

- *, concatenation (.), and | (pipe sign) are left associative
- * has the highest precedence
- Concatenation (.) has the second highest precedence.
- | (pipe sign) has the lowest precedence of all.

### Representing valid tokens of a language in regular expression

If x is a regular expression, then:

x* means zero or more occurrence of x.

i.e., it can generate { e, x, xx, xxx, xxxx, … }

x+ means one or more occurrence of x.

i.e., it can generate { x, xx, xxx, xxxx … } or x.x*

x? means at most one occurrence of x

i.e., it can generate either {x} or {e}.

[a-z] is all lower-case alphabets of English language.

[A-Z] is all upper-case alphabets of English language.

[0-9] is all natural digits used in mathematics.

### Representing occurrence of symbols using regular expressions

letter = [a – z] or [A – Z]

digit = 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 or [0-9]

sign = [ + | - ]

### Representing language tokens using regular expressions

Decimal = (sign)^{?}(digit)^{+}

Identifier = (letter)(letter | digit)*

The only problem left with the lexical analyzer is how to verify the validity of a regular expression used in specifying the patterns of keywords of a language. A well-accepted solution is to use finite automata for verification.