Chapter V: Compiler
Overview:
 To study the design and operation of compiler for
high-level programming languages.
 Contents
 Basic
compiler (one-pass compiler) functions
 Machine-dependent extension:
(object-code generation & code optimization)
 Compiler design alternative:
multi-pass compiler, interpreters, p-code compilers &
compiler-compilers.
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Basic compiler functions
 Example
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Basic compiler functions (cont.)
 Source program
 Regard each statement as a sequence of token.
 The task of scanning the source statement, recognizing and
classifying the various tokens, is known as lexical analysis.
(scanner)
 Recognized all tokens as some language construct by
the grammar.
 This process is called syntactic analysis or parsing. (parser)
 Generation of object code.
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Compilation process
 Scanning (lexical analysis)
 Parsing (syntactic analysis)
 Code generation
 Ps. It can achieve in a single pass !
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Grammars
 A grammar for a programming language is a
formal description of the syntax, of programs and
individual statements written in the language.
 The difference between syntax and semantics,
 E.g.,
I := J + K
X := Y + I
where X,Y : Real
I,J,K : Integer
They are identical syntax.
However, the semantic are quite different.
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Grammars (cont.)
 BNF (Backus-Naur Form)
 A kind of syntax description.
 Simple.
 Widely used.
 It provide capabilities that are sufficient for most purposes.
 BNF consists of a set of rules, each of which defines
the syntax of some construct in the programming
language.

E.g.,
<read> ::= READ ( <id-list>)
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Grammars (cont.)
<read> ::= READ ( <id-list>)
 <id-list> ::= id | <id-list>, id

Character strings enclosed between < and > are called
nonterminal symbol.
 Character strings not enclosed between < and > are
called terminal symbol (I.e, tokens).


E.g.,
READ(value, sum, x, y)
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Simplified Pascal grammar
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Simplified Pascal grammar (cont.)
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Simplified Pascal grammar (cont.)
 To display the analysis of a source statement in
terms of a grammar a a tree (parse tree or syntax
tree).
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The parse tree for
VARIANCE := SUMSQ DIV 100 – MEAN * MEAN
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Grammars (cont.)
 Draw parse tree for
 ALPHA – BETA * GAMMA
 If there is more than one possible parse tree for a
given statement, the grammar is said to be
ambiguous.
 The ambiguous grammar would leave doubt about
what object code should be generated.
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Lexical analysis (scanning)
 Scanning the program to be compiled and recognizing
the tokens that make up the source statements.
 Scanner are usually designed to recognize keywords,
operators, and identifiers, integer, floating-point
numbers, character strings, …,etc.
 The identifier might be defined by the rules:
<ident> ::= <letter> | <ident> <letter> | <ident> <digit>
 <letter> ::= A | B | C | D | … | Z
 <digit> ::= 0 | 1 | 2 | 3 | … | 9

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Token coding scheme
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Lexical scan
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The lexical scanning
 It must deal with the following cases:
 For example,
 DO 10 I = 1, 100
 DO 10 I =1
 (FORTRAN ignores blank in the statement)
 IF (THEN .EQ. ELSE) THEN
IF = THEN
ELSE
THEN = IF
ENDIF
 A number of tools have been developed for automatically
constructing lexical scanners from specifications stated in a
special-purpose language.
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Modeling Scanners as Finite Automata
 The tokens of most programming languages can
be recognized by a finite automation.
 Starting state vs. final state.
 If the automation stops in a final state, we say that
it recognizes (or accept) the string being scanned,
otherwise, it fails to recognize the string.
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Modeling Scanners as Finite Automata (cont.)
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Modeling Scanners as Finite Automata (cont.)
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Modeling Scanners as Finite Automata (cont.)
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Modeling Scanners as Finite Automata (cont.)
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The implementation of finite automata
 Using algorithm code (for Fig. 5.8 (b))
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The implementation of finite automata (cont.)
 Using tabular representation
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