SYSTEM SOFTWARE NOTES 5TH SEM VTU

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COMPILERS

BASIC COMPILER FUNCTIONS

A compiler accepts a program written in a high level language as input and produces its machine language equivalent as output. For the purpose of compiler construction, a high level programming language is described in terms of a grammar. This grammar specifies the formal description of the syntax or legal statements in the

language.

Example: Assignment statement in Pascal is defined as:

< variable > : = < Expression >

The compiler has to match statement written by the programmer to the structure defined by the grammars and generates appropriate object code for each statement. The compilation process is so complex that it is not reasonable to implement it in one single step. It is partitioned into a series of sub-process called phases. A phase is a logically cohesive operation that takes as input one representation of the source program and produces an output of another representation. The basic phases are - Lexical Analysis, Syntax Analysis, and Code Generation.

Lexical Analysis: It is the first phase. It is also called scanner. It separates characters of

the source language into groups that logically belong together. These groups are called tokens. The usual tokens are:

Keyword: such as DO or IF, Identifiers: such as x or num,

Operator symbols: such as <, =, or, +, and

Punctuation symbols: such as parentheses or commas.

The output of the lexical analysis is a stream of tokens, which is passed to the next phase; the syntax analyzer or parser.

Syntax Analyzer: It groups tokens together into syntactic structure. For example, the

three tokens representing A + B might be grouped into a syntactic structure called as expression. Expressions might further be combined to form statements. Often the syntactic structures can be regarded as a tree whose leaves are the tokens. The interior nodes of the tree represent strings of token that logically belong together. Fig. 1 shows the syntax tree for READ statement in PASCAL

(read)

(id - list)

READ ( id ) {value}

Fig. 1 Syntax Tree

Code Generator: It produces the object code by deciding on the memory locations for

data, selecting code to access each datum and selecting the registers in which each computation is to be done. Designing a code generator that produces truly efficient object program is one of the most difficult parts of compiler design.

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process, illustrating this application to the example program in fig. 2. PROGRAM STATS

VAR

SUM, SUMSQ, I, VALUE, MEAN, VARIANCE : INTEGER BEGIN SUM : = 0 ; SUMSQ : = 0 ; FOR I : = 1 to 100 Do BEGIN READ (VALUE) ;

SUM : = SUM + VALUE ;

SUMSQ : = SUMSQ + VALUE * VALUE END;

MEAN : = SUM DIV 100;

VARIANCE : = SUMSQ DIV 100 - MEAN * MEAN ; WRITE (MEAN, VARIANCE)

END

Fig. 2 Pascal Program

GRAMMARS

A grammar for a programming language is a formal description of the syntax of programs and individual statements written in the language. The grammar does not describe the semantics or memory of the various statements. To differentiate between syntax and semantics consider the following example

:

VAR X, Y : REAL VAR I, J, K : INTEGER I : INTEGER

X : = I + Y ; I : = J + K ; Fig .3

These two programs statement have identical syntax. Each is an assignment statement; the value to be assigned is given by an expression that consists of two variable names separated by the operator '+'.

The semantics of the two statements are quite different. The first statement specifies that the variables in the expressions are to be added using integer arithmetic operations. The second statement specifies a floating-point addition, with the integer operand 2 being connected to floating point before adding. The difference between the statements would be recognized during code generation.

Grammar can be written using a number of different notations. Backus-Naur Form (BNF) is one of the methods available. It is simple and widely used. It provides capabilities that are different for most purposes.

A BNF grammar consists of a set of rules, each of which defines the syntax of some construct in the programming language.

A grammar has four components. They are:

1.

A set of tokens, known as terminal symbols non-enclosed in bracket. Example: READ, WRITE

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2. A set of terminals. The character strings enclosed between the angle brackets (<, >) are called terminal symbols. These are the names of the constructs defined in the grammar.

3. A set of productions where each production consists of a non-terminal called the left side of the production, as "is defined to be" (:: = ), and a sequence of

token and/or non-terminal, called the right side of the product.

Example: < reads > : : = READ <id - list >.

4. A designation of one of the non-terminals as the start symbol.

This rule offers two possibilities separated by the symbol, for the syntax of an < id - list > may consist simply of a token id (the notation id denotes an identifier that is recognized by the scanner). The second syntax.

Example: ALPHA

ALPHA, BETA

ALPHA is an < id - list > that consist of another < id - list > ALPHA, followed by a comma, followed by an id BETA.

Tree: It is also called parse tree or syntax tree. It is convenient to display the analysis

of a source statement in terms of a grammar as a tree.

Example: READ (VALUE)

GRAMMAR: (read) : : = READ ( < id -list>)

Example: Assignment statement:

SUM : = 0 ;

SUM : = + VALUE ; SUM : = - VALUE ;

Grammar: < assign > : : = id : = < exp >

< exp > : : = < term > | < exp > - < term >

< term > : : = < factor > | < term > * < factor > | < term > DIV < factor > < factor > : : = id | int | ( < exp > )

Assign consists of an id followed by the token : = , followed by an expression <exp > Fig. 4(a). Show the syntax tree.

Expressions are sequence of <terms> connected by the operations + and - Fig. 4(b). Show the syntax tree.

Term is a sequence of < factor > S connected by * and DIV Fig. 4(c).

A factor may consists of an identifies id or an int (which is also recognized by

the scan) or an < exp > enclosed in parenthesis. Fig. 4(d).

< assign >

< exp >

id

: = <exp > < term > + < exp >

{variance }

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< term >

factor

|

< factor > Dir < term >

id

X < factor >

int

Id

Fig.4 (c)

(< exp > ) Fig. 4 (d)

Fig. 4 Parse Trees

For the statement Variance : = SUMSQ Div 100 - MEAN * MEAN ; The list of simplified Pascal grammar is shown in fig.5.

1. < prog > : : = PROGRAM < program > VAR <dec - list > BEGIN < stmt > - list > END.

2.

< prog - name >: : = id

3.

< dec - list > : : = < dec > | < dec - list > ; < dec >

4.

< dec > : : = < id - list > : < type >

5. < type > : : = integer

6.

< id - list > : : = id | < id - list > , id

7. <stmt - list > : : = < stmt > <stmt - list > ; < stmt >

8. < stmt > : : = < assign > | <read > | < write > | < for > 9. < assign > : : = id : = < exp >

13. < READ > : : = READ ( < id - list >) 14. < write > : : = WRITE ( < id - list >)

15. < for > : : = FOR < idex - exp > Do < body >

16.

< index - exp> : : = id : = < exp > To ( exp >

17. < body > : : = < start > | BEGIN < start - list > END

Fig. 5 Simplified Pascal Grammar

( < prog >)

|

PROGRAM < prog - name > VAR dec - list BEGIN <Stmt - list > END Id < dec > {STATS} < stmt - list > ; < stmt > < id - list > : < type > ↓ INTEGER < write > (id - list) , id

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(id - list ) ; id < stmt - list > ; <stmt > < assign > (id - list ) . id

(MEAN) {VARIANCE}

id

(id - list ) , id id : = <MEAN> <VALUE > < stmt - list > ; <stmt > {VARIANCE} < exp >

< assign >

(id - list ) , id

{I} <stmt > ; < start >

id : = <exp> <term>

<id -list > , id {mean} <exp>

{SMSQ} < stmt > < assign > | | <term> <term> <term> * <factor> id | |

{SUM} < assign > id : = <exp> | | <factor> id {SUMSQ} | | <term> Div <factor> | [MEAN]

| | | term | >term> Div <factor > id

id : < exp > | factor {MEAN}

| factor | int < term > | id {100} <factor> int

| int {SUM} | {100} < factor > { 0} id | {SUMSQ} int {0} |

< for >

FOR <index - exp > Do < body >

Id : = <exp> To <exp> BEGIN <stm - list> END

{I} | |

< term > <term>

| |

| | |

int int

{I} {100} <symt - list> ; <stmt> <assign >

| | < stmy > <assign > | id : = <emp> < read > (SUMSQ id : = <exp> {SUM}

READ ( < id - list > ) < exp > + < term > < exp > + < term >

id | | |

{VALUE? <term > < factor > < term > <term> * <factor> | | | | |

< factor >. id <factor > <factor > id | { value} | | {value}

id id id

{SUM} {SUMSQ} {value}

Fig. 6 Parse tree for the Program 1

Parse tree for Pascal program in fig.1 is shown in fig. 6

1 (a) Draw parse trees, according to the grammar in fig. 5 for the following <id-list> S:

(a) ALPHA

< id - list >

|

id

{ ALPHA }

(b) ALPHA, BETA, GAMMA

< id - list >

id

< id - list > , {GAMMA}

id

< id - list > , {BETA}

id

[ ALPHA ]

2 (a) Draw Parse tree, according to the grammar in fig. 5 for the following < exp > S :

(a)

ALPHA + BETA

< exp >

|

< term >

|

< factor > + < factor >

|

id

{ALPHA} {BETA}

(b) ALPHA - BETA + GAMMA

< exp

< exp > -

term

< term >

< term > *

factor

| |

< factor > < factor >

id

|

{GAMMA}

id

{ALPHA} {BETA}

(c) ALPHA DIV (BETA + GAMMA) = DELTA

< exp >

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< exp >

-

< term >

< factor >

|

< term > Div < factor >

{DELTA}

< factor >

( < exp >

)

id

{ALPHA}

< exp > + < term >

< term >

factor

id

{BETA} {GAMMA}

3. Suppose the rules of the grammar for < exp > and < term > is as follows: < exp > :: = < term > | < exp > * < term> | < exp> Div < term > < term > :: = <factor> | < term > + < factor > | < term > - < factor > Draw the parse trees for the following:

(a) A1 + B1 (b) A1 - B1 * G1 (c) A1 + DIV (B1 + G1) - D1

< exp >

|

(a) A1 + B1

term

< term > + < factor >

factor

|

id

{A1}

{B1}

(b) A1 - B1 * G1 < exp >

|

teerm

teerm - < factor >

factor

term

*

factor

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|

id

factor

id

{A1} id {B1} {G1}

(c) A1 DIV (B1 + A1) - D1

< exp >

< exp > DIV < term >

< term > < term > -

< factor >

id

|

{D1}

id

{A1}

( < exp > )

< term >

< term > +

< factor >

id

{G1}

id

{B1}

LEXICAL ANALYSIS

Lexical Analysis involves scanning the program to be compiled. Scanners are designed to recognize keywords, operations, identifiers, integer, floating point numbers, character strings and other items that are written as part of the source program. Items are recognized directly as single tokens. These tokens could be defined as a part of the

grammar.

Example: <ident> : : = <letter> | <ident> <letter> | <ident> <digit>

<letter> : : = A | B | C | . . . | Z <digit> : : = 0 | 1 | 2 | . . . | 9

In a such a case the scanner world recognize as tokens the single characters A, B, . . . Z,, 0, 1, . . . 9. The parser could interpret a sequence of such characters as the language construct < ident >. Scanners can perform this function more efficiently. There can be significant saving in compilation time since large part of the source program consists of multiple-character identifiers. It is also possible to restrict the length of identifiers in a scanner than in a passing notion. The scanner generally recognizes both single and multiple character tokens directly.

The scanner output consists of sequence of tokens. This token can be considered to have a fixed length code. The fig. 7 gives a list of integer code for each token for the program in fig. 5 in such a type of coding scheme, the PROGRAM is represented by

the integer value 1, VAR has the integer value 2 and so on.

Token Program

VAR

BEGIN END END INTEGER FOR

8

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Code

1

2

3

4

5

6

7 Token READ WRITE

To

Do

;

:

,

Token

: =

+

-

K

DIV

(

)

Token

: =

+

-

K

DIV

(

)

Code

15

16

17

18

17

20

21 Token

Id

Int

Code

22

23

Fig. 7 Token Coding Scheme

For a keyword or an operator the token loading scheme gives sufficient information. In the case of an identifier, it is also necessary to supply particular identifier name that was scanned. It is true for the integer, floating point values, character-string constant etc. A token specifier can be associated with the type of code for such tokens. This specifier gives the identifier name, integer value, etc., that was found by the scanner.

Some scanners enter the identifiers directly into a symbol table. The token specifier for the identifiers may be a pointer to the symbol table entry for that identifier.

The functions of a scanner are:

 The entire program is not scanned at one time.

 Scanner is a operator as a procedure that is called by the processor when it needs another token.

 Scanner is responsible for reading the lines of the source program and possible for printing the source listing.

 The scanner, except for printing as the output listing, ignores comments.  Scanner must look into the language characteristics.

Example: FOTRAN : Columns 1 - 5 Statement number

: Column 6 Continuation of line : Column 7 . 22 Program statement PASCAL : Blanks function as delimiters for tokens

: Statement can be continued freely

: End of statement is indicated by ; (semi column)  Scanners should look into the rules for the formation of tokens.

Example: 'READ': Should not be considered as keyword as it is within quotes. i.e., all string within quotes should not be considered as token.

 Blanks are significant within the quoted string.

 Blanks has important factor to play in different language

Example 1: FORTRAN Statement:

Do 10 I = 1, 100 ; Do is a key word, I is identifier, 10 is the statement number Statement: Do 10 I = 1 ;It is an identifier Do 10 I = 1

Note: Blanks are ignored in FORTRAN statement and hence it is a assignment statement.

In this case the scanner must look ahead to see if there is a comma (,) before it can decide in the proper identification of the characters

9

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Do.

Example 2: In FORTRAN keywords may also be used as an identifier. Words such as IF, THEN, and ELSE might represent either keywords or

variable names.

IF (THEN .EQ ELSE) THEN

IF = THEN

ELSE

THEN = IF

ENDIF

Modeling Scanners as Finite Automata

Finite automatic provides an easy way to visualize the operation of a scanner. Mathematically, a finite automation consists of a finite set of states and a set of transition from one state to another. Finite automatic is graphically represented. It is shown in fig, State is represented by circle. Arrow indicates the transition from one state to another. Each arrow is labeled with a character or set of characters that can be specified for transition to occur. The starting state has an arrow entering it that is not connected to anything else.

State Final State

Transition

Fig. 8

Example: Finite automata to recognize tokens is gives in fig. 9. The

corresponding algorithm is given in fig. 10

0 - 9

A - Z

B

A - Z

Fig. 9

Get first Input-character

If Input-character in [ 'A' . . ' Z' ] then begin

while Input - character in [ 'A' . . 'Z', ' 0'. . ' 9' ] do

begin

get next input - character

End {while}

end {if first is [ 'A' .. ' Z' ] } else return (token-error)

Fig. 10

SYNTACTIC ANALYSIS

1

2

1

3

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During syntactic analysis, the source programs are recognized as language constructs described by the grammar being used. Parse tree uses the above process for

translation of statements, Parsing techniques are divided into two general classes: -- Bottom up and -- Top down.

Top down methods begin with the rule of the grammar that specifies the goal of the analysis ( i.e., the root of the tree), and attempt to construct the tree so that the terminal nodes match the statement being analyzed.

Bottom up methods begin with the terminal nodes of the tree and attempt to combine these into successively high - level nodes until the root is reached.

OPERATOR PRECEDENCE PARSING

The bottom up parsing technique considered is called the operator precedence method. This method is loaded on examining pairs of consecutive operators in the source

program and making decisions about which operation should be performed first.

Example: A + B * C - D (1)

The usual procedure of operation multiplication and division has higher precedence over addition and subtraction.

Now considering equation (1) the two operators (+ and *), we find that + has lower precedence than *. This is written as +⋖ * [+ has lower precedence *]

Similarly ( * and - ), we find that * _{⋗ - [* has greater precedence -].}

The operation precedence method uses such observations to guide the parsing process. A + B * C - D (2)

⋖

⋗

V A R B E G IN E N D E N D IN T E G E R FO R R E A S W R IT E T O D O :: , : = +-* D IV )( Id In t

PROGRAM

VAR

BEGIN

END

≐ ≐ ≐ ≐ ⋗ ⋗ ⋖ ⋖ ⋖ ⋖ ⋖ ⋖ ⋗ < ⋖ ⋖ ⋖

INTEGER

FOR

READ

WRITE

⋗ ⋗ ≐ ≐ ≐

⋖

TO

DO

;

:

⋖ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋖ ⋖ ⋖ ⋖ ⋖ ⋖ ⋖

⋗

⋗ ⋗ ⋖ ⋗

⋖ ⋖

⋖ ⋖ ⋖ ⋖ ⋖ ⋖ ⋖ ⋖ ⋖

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,

: =

+

⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ≐ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋖ ⋖ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋖ ⋖ ⋖ ⋖ ⋖ ⋖ ⋗ ⋖ ⋖ ⋖ ⋗ ⋗ ⋗ ⋗ ⋖ ≐ ⋖ ⋖ ⋖ ⋖ ⋖ ⋖ * DIV ) (

⋗ ⋗

⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋖ ⋗ ⋗ ⋗ ⋗ ⋖ ⋗ ⋗ ⋗ ⋖ ⋗ ⋖ ⋖ ⋖ ≐ ⋗ ⋗ ⋗ ⋖ ⋖ ⋖ ⋖ ⋖ ⋖ id Int

⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗⋗ ⋗ ⋗ ⋗ ≐ ⋗ ⋗ ⋗ ⋗ ⋗ ⋗⋗ ⋗ ⋗⋗

Fig 11 Precedence Matrix for the Grammar for fig 5

Equation (2) implies that the sub expression B * C is to be computed before either of the other operations in the expression is performed. In times of the parse tree this means that the * operation appears at a lower level than does either + or -. Thus a bottom up parses should recognize B * C by interpreting it in terms of the grammar, before considering the surrounding terms. The first step in constructing an operator-precedence parser is to determine the precedence relations between the operators of the grammar. Operator is taken to mean any terminal symbol (i.e., any token). We also have

precedence relations involving tokens such as BEGIN, READ, id and ( . For the grammar in fig. 5, the precedence relations is given in the fig. 11.

Example: PROGRAM _{≐ VAR ; These two tokens have equal precedence}

Begin ⋖ FOR ; BEGIN has lower precedence over FOR. There are some values which do not follows precedence relations for comparisons.

Example: ; ⋗ END and END ⋗ ;

i.e., when ; is followed by END, the ' ; ' has higher precedence and when END is

followed by ; the END has higher precedence.

In all the statements where precedence relation does not exist in the table, two tokens cannot appear together in any legal statement. If such combination occurs during parsing it should be recognized as error.

Let us consider some operator precedence for the grammar in fig. 5.

Example: Pascal Statement: BEGIN

READ (VALUE);

These Pascal statements scanned from left to right, one token at a time. For each pair of operators, the precedence relation between them is determined. Fig. 12(a) shows the parser that has identified the portion of the statement delimited by the precedence

relations _{⋖ and to be}_⋗ interpreted in terms of the grammar. (a) . . . BEGIN READ ( id )

_⋖ _≐_{⋖ ⋗} (b) . . . BEGIN READ ( < N1 > ) ; _⋖ _{≐ ≐ ⋗} (c) . . . BEGIN < N2 > ; (d) ... < N2 > READ ( <N1 > )

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id (VALUE)

Fig. 12

According to the grammar id may be considered as < factor > . (rule 12), <program > (rule 9) or a < id-list > (rule 6). In operator precedence phase, it is not necessary to indicate which non-terminal symbol is being recognized. It is interpreted as non-terminal < N1 >. Hence the new version is shown in fig. 12(b).

An operator-precedence parser generally uses a stack to save token that have been scanned but not yet parsed, so it can reexamine them in this way. Precedence relations hold only between terminal symbols, so < N1 > is not involved in this process and a relationship is determined between (and).

READ (<N1>) corresponds to rule 13 of the grammar. This rule is the only one that could be applied in recognizing this portion of the program. The sequence is simply interpreted as a sequence of some interpretation < N2 >. Fig. 12(c) shows this

interpretation. The parser tree is given in fig. 12(d).

Note: (1) The parse tree in fig. 1 and fig. 12 (d) are same except for the name of the

non-terminal symbols involved.

(2) The name of the non-terminals is arbitrarily chosen.

Example: VARIANCE ; = SUMSQ DIV 100 - MEAN * MEAN

(i) . . id 1 : = id 2 Div . . . <N1>

_⋖ _{≐ ⋖} _⋗

<id 2>

(ii) . . . id 1 : = <N1> Div int -

_⋖ _≐ _⋖_⋖ _⋗ {SUMSQ} (iii) . . . id 1 : = <N1> Div <N2> - <N1> <N2>

_⋖

≐

⋖ ⋗

<id 2> int

{SUMSQ} {100}

(iv) . . . . id 1 : = <N3> - id 3 *

<N3>

_⋖

≐

⋖

⋗

<N1> DIV <N2>

id2

int

{SUMSQ}

{100}

**v) . . . . id 1 : = <N3> - <N4> * id 4 ;**

<N4>

⋖

≐

⋖

⋗

id 3

{MEAN}

**(vi) . . . id 1 : = <N3> - <N4> * <N5>**

<N5>

_⋖

≐

⋖

⋗

id 4

{MEAN}

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(vii) . . . id 1 : = <N3> - <N6>

<N6>

⋖

≐

⋖

⋗

<N4> * <N5>

id 3

id 4

{MEAN} {MEAN}

(viii) . . . id : = <N7>

<N7>

⋖

≐

⋗

<N3> - <N6>

(ix) . . . <N8>

<N8>

<N7>

<N3>

<N6>

id 1

: =

<N1>

<N2> <N4> <N5>

{VARIANCE}

DIV

*

id 2

int - id 3 id 4

{SUMSQ} {100} {MEAN} {MEAN}

SHIFT REDUCE PARSING

The operation procedure parsing was developed to shift reduce parsing. This method makes use of a stack to store tokens that have not yet been recognized in terms of the grammar. The actions of the parser are controlled by entries in a table, which is somewhat similar to the precedence matrix. The two main actions of shift reducing

parsing are

Shift: Push the current token into the stack.

Reduce: Recognize symbols on top of the stack according to a rule of a grammar

Example: BEGIN READ ( id ) . . .

Steps Token Stream

Stack

1. . . . BEGIN

READ ( id ) . . .

2. . . . BEGIN

READ ( id )

BEGIN

Shi

ft

Shi

ft

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3. . . . BEGIN

READ ( id ) . . .

READ

BEGIN

4. . . BEGIN

READ ( id ) . . .

(

READ BEGIN

5. . . . BEGIN READ ( id ) . . .

id (

READ

BEGIN

6. . . . BEGIN READ ( id ) . . .

.

< id-list > (

READ

BEGIN Explanation

1. The parser shift (pushing the current token onto the stack) when it encounters BEGIN 2 to 4. The shift pushes the next three tokens onto the stack.

5. The reduce action is invoked. The reduce converts the token on the top of the stack to a non-terminal symbol from the grammar.

6. The shift pushes onto the stack, to be reduced later as part of the READ statement.

Note: Shift roughly corresponds to the action taken by an operator – precedence parses

when it encounters the relation ⋖ and . ≐ Reduce roughly corresponds to the action taken when an operator precedence parser encounters the relation _⋗.

RECURSIVE DESCENT PARSING

Recursive-Descent is a top-down parsing technique. A recursive-descent parser is made up of a precedence for each non-terminal symbol in the grammar. When a precedence is called it attempts to find a sub-string of the input, beginning with the current token, that can be interpreted as the non-terminal with which the procedure is associated. During this process it may call other procedures, or call itself recursively to search for other non-terminals. If the procedure finds the non-terminal that is its goal, it returns an indication of success to its caller. It also advances the current-token pointer past the sub-string it has just recognized. If the precedence is unable to find a sub-string

that can be interpreted as to the desired non-terminal, it returns an indication of failure.

Example: < read > : : = READ ( < id - list > )

The procedure for < read > in a recursive descent parser first examiner the next two input, looking for READ and (. If these are found, the procedures for < read > then call the procedure for < id - list >. If that procedure succeeds, the < read > procedure examines the next input token, looking for). If all these tests are successful, the < read > procedure returns an indication of success. Otherwise the procedure returns a failure.

There are problems to write a complete set of procedures for the grammar of fig. 15.

15 Shi

ft

Shi

ft

Shi

ft

Shi

ft

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Example: The procedure for < id - list >, corresponding to rule 6 would be unable to

decide between its alternatives since id and < list > can begin with id. <list > : : = id | < id-list >, id

If the procedure somehow decided to try the second alternative <id-list>, it would immediately call itself recursively to find an <id-list>. This causes unending chain. Top-down parsers cannot be directly used with a grammar that contains this kind of immediate left recursion.

Similarly the problem occurs for rules 3, 7, 10 and 11. Hence the fig. 13 shows the rules 3, 6, 7, 10 and 11 modification.

3 < dec - list > : : = < dec > { ; <dec > } 6 < id - list > : : = id {; id }

7 < stmt - list > : : = < stmt > { ; < stmt > }

10 < exp > : : = < term > { + < term . | -- < term > } 11 < term > : : = < factor > { + < factor > | Div < factor >.}

Fig. 13

Fig. 14 illustrates a recursive-descent parse of the READ statement: READ

(VALUE); The modified grammar is considered in the procedure for the non-terminal

<read > and < id-list >. It is assumed that TOKEN contains the type of the next input

token.

PROCEDURE READ

BEGIN

ROUND : = FALSE

If TOKEN + 8 { read } THEN

BEGIN

advance to next token

IF TOKEN + 20 { ( } THEN BEGIN

IF IDLIST returns success THEN IF token = 21 { ) } THEN BEGIN

FOUND : = TRUE advance to next token

END { if ) }

END { if READ }

IF FOUND = TRUE THEN

return success else failure end (READ)

Fig. 14

Procedure IDLIST begin FOUND = FALSE

if TOKEN = 22 {id} then begin

FOUND : = TRUE advance to Next token

while (TOKEN = 14 {,}) and (FOUND = TRUE) do

(17)

begin

if TOKEN = 22 {id} then advance to next token

else

FOUND = FALSE End {while}

End {if id}

if FOUND : = TRUE then

return success else

return failure

end {IDLIST}

Fig. 15

The fig. 15 IDLIST procedure shows an error message if ( , ) is not followed by a id. It indicates the failure in the return statement. If the sequence of tokens such as " id, id " could be a legal construct according to the grammar, this recursive-descent technique would not work properly.

Fig. 16 shows a graphic representation of the recursive parsing process for the statement being analyzed.

(i) In this part, the READ procedure has been invoked and has examined the tokens READ and ' ( " from the input stream (indicated by the dashed lines).

(ii)

In this part, the READ has called IDLIST (indicated by the solid line), which has examined the token id.

(iii) In this part, the IDLIST has returned to READ indicating success; READ has then examined the input token.

Note that the sequence of procedure calls and token examinations has completely defined the structures of the READ statement. The parser tree was constructed beginning at the root, hence the term top-down parsing.

(i)

(II)

(iii)

READ READ READ

(

id

{ Value }

{ Value

Fig. 16

Fig. 17 illustrates a recursive discard parse of the assignment statement. Variance: = SUNSQ DIVISION - MEAN * MEAN

The fig. 17 shows the procedures for the non-terminal symbols that are involved in parsing this statement.

Procedure ASSIGN begin

FOUND = FALSE

if TOKEN = 22 {id} then begin

REA

D

REA

D

REA

D

IDLIS

T

IDLIST

(18)

advance to Next token

if TOKEN = 15 {: =} then begin

advance to next token if EXP returns success then

FOUND : = TRUE

end {if : =}

return success else return failure end {ASSIGN} Procedure EXP begin FOUND = FALSE

If TERM returns success then

begin

FOUND: = TRUE

while ((TOKEN = 16 {+ } ) or (TOKEN = 17 { - } ) )

and (FOUND = TRUE) do

begin

if TERM returns success then

FOUND = FALSE

end {while} end {if TERM}

return success else return failure end {EXP} Procedure TERM begin FOUND : = FALSE

If FACTOR returns success then

begin

FOUND : = TRUE

while ((TOKEN = 18 { * }) or (TOKEN = 19 {DIV })

and (FOUND = TRUE) do

begin

if TERM returns failure then

FOUND : = FALSE end {while}

end {if FACTOR} if FOUND : = TRUE then

return failure

end {TERM} Procedure FACTOR

(19)

begin

FOUND : = FALSE

if (TOKEN = 22 { id } ) or (TOKEN = 23 {int } ) then

begin

FOUND : = TRUE advance to next token end { if id or int }

else

if TOKEN = 20 { ( } then

begin

if EXP returns success then

if TOKEN = 21 { ) } then

begin

(FOUND = TRUE) advance to next token

end { if ) } end {if ( }

return failure

end {FACTOR}

Fig. 17 Recursive-Descent Parse of an Assignment Statement

A step-by-step representation of the procedure calls and token examination is shown in fig. 1

(i)

(ii)

(iii)

id 1 : = id 1 : = id 1

: =

{ VARIANCE } { VARIANCE } {VARIANCE}

(iv)

(v)

(vi)

id 1 : = id 1 : = id 1 : =

{VARIANCE} {VARIANCE} {VARIANCE}

-

DIV DIV ASSIGN ASSIGN EXP ASSIGN _ASSIGN EXP EXP TERM EXP TERM TERM TERM

FACTOR FACTOR FACTOR FACTOR FACTOR

ASSIGN

TERM EXP

(20)

id 2

int

id

2 int

{SUMSQ} {SUMSQ} {100} {SUMSQ} {100}

(vii)

id 1 : = {VARIANCE}

DIV

id 2

int id 3

{SUMSQ} {100} {MEANS}

(viii)

id 1 : = (VARIANCE} -

*

DIV

id 2

int

id 3

id 4

{SUMSQ} {100} {MEANS} {MEANS}

Fig. 18 Step by step Representation for Variance : = SUMSQ Div 100 - MEAN * Mean

GENERATION OF OBJECT CODE

After the analysis of system, the object code is to be generated. The code generation technique used in a set of routine, one for each rule or alternative rule in the grammar. The routines that are related to the meaning of he compounding construct in the language is called the semantic routines.

When the parser recognizes a portion of the source program according to some rule of the grammar, the corresponding semantic routines are executed. These semantic routines generate object code directly and hence they are referred as code generation routines. The code generation routines that is discussed are designed for the use with the grammar in fig. .5. This grammar is used for code generations to emphasize the point that code generation techniques need not be associated with any particular parsing method.

The parsing technique discussed in 1.3 does not follow the constructs specified by this grammar. The operator precedence method ignores certain non-terminal and the recursive-descent method must use slightly modified grammar.

The code generation is for the SIC/XE machine. The technique use two data structure: (1) A List (2) A Stack

List Count: A variable List count is used to keep a count of the number of items

currently in the list. The token specifiers are denoted by ST (token)

ASSIGN ASSIGN FACTOR FACTOR TERM FACTOR TERM EXP

FACTOR FACTOR FACTOR FACTOR

TERM TERM

(21)

Example: id ST (id) ; name of the identifier

int ST (int) ; value of the integer, # 100

The code generation routines create segments of object code for the compiled program. A symbolic representation is given to these codes using SIC assembler

language.

LC (Location Counter): It is a counter which is updated to reflect the next variable

address in the compiled program (exactly as it is in an assembler).

Application Process to READ Statement:

(read)

+ JSUB

XREAD

WORD 1

< id - list >

WORD VALUE

READ

( )

{VALUE}

Fig. 19(a) Parse Tree for Read

Using the rule of the grammar the parser recognizes at each step the left most sub-string of the input that can be interpreted. In an operator precedence parse, the recognition occurs when a sub-string of the input is reduced to some non-terminal <N i>.

In a recursive-descent parse, the recognition occurs when a procedure returns to its caller, indicating success. Thus the parser first recognizes the id VALUE as an < id - list >, and then recognizes the complete statement as a < read >.

The symbolic representation of the object code to be generated for the READ statement is as shown in fig. 19(b). This code consists of a call to a statement XREAD, which world be a part of a standard library associated with the compiler. The subroutine any program that wants to perform a READ operation can call XREAD. XREAD is linked together with the generated object program by a linking loader or a linkage editor. The technique is commonly used for the compilation of statements that perform voluntarily complex functions. The use of a subroutine avoids the repetitive generation of large amounts of in-line code, which makes the object program smaller.

The parameter list for XREAD is defined immediately after the JSUB that calls it. The first word is the number of variable that will be assigned values by the READ. The following word gives the addresses of three variables.

Fig. 19(c) shows the routines that might be used to accomplish the code generation.

1.

< id - list > : : = id add ST (id) to list add 1 to List_count

2.

< id - list > : : = < id - list >, id add ST (id) to list

add 1 to LC List_Current 3. < read > : : = READ (< id - list >)

generate [ + JSUB XREAD ] record external reference to XREAD generate [WORD List - count] for each item on list of do begin

(22)

generate [WORD ST (ITEM)] end

List _count : = 0

Fig. 19 (c) Routine for READ Code Generation

The first two statements (1) and (2) correspond to alternative structure for < id - list >, that is < id - list > : : = id | < id - list >, id.

In each case the token specifies ST (id) for a new identifier being called to the < id - list > is inserted into the list used by the code-generation routine, and list-count is updated to reflect the insertion. After the entire < id-list > has been parsed, the list contains the token specifiers for all the identifiers that are part of the < id- list >. When the < read > statement is recognized, the token specifiers are removed from the list and used to generate the object code for the READ.

Code-generation Process for the Assignment Statement

Example: VARIANCE: = SUMSQ DIV 100 - MEAN * MEAN

The parser tree for this statement is shown in fig. 20. Most of the work of parsing involves the analysis of the < exp > on the right had side of the " : = " statement.:

< assign >

< exp >

(

term)

< term >

< term > < factor >

< factor >

< factor > < factor >

id

: = id DIV int

_

id *

id

{VARIANCE} { SUMSQ } {100} {MEAN} {MEAN}

Fig. 20

The parser first recognizes the id SUMSQ as a < factor > and < term > ; then it recognizes the int 100 as a < factor >; then it recognizes SUNSQ DIV 100 as a < term >, and so forth. The order in which the parts of the statements are recognized is the same as the order in which the calculations are to be performed. A code-generation routine is

called for each portion of the statement is recognized.

Example; For a rule < term >

1

: : = < term >

2

* < factor > a code is to be

generated.

(23)

The code-generation routines perform all arithmetic operations using register A. Hence the multiple < term >2 * < factor > after multiplication is available in register A. Before

multiplication one of the operand < term >2 must be located in A-register. The results after

multiplication will be left in register A. So we need to keep track of the result left in register A by each segment of code that is generated. This is accomplished by extending the token-specifier idea to non-terminal nodes of the parse tree.

The node specifier ST (< term1>) would be set to rA, indicating that the result of the completion is in register A. the variable REGA is used to indicate the highest level node of the parse tree when value is left in register A by the code generated so far. Clearly there can be only one such node at any point in the code-generation process. If the value corresponding to a node is not in register A, the specifier for the node is similar to a token specifier: either a pointer to a symbol table entry for the variable that contains the value or an integer constant.

Fig. 21 shows the code-generation routine considering the A-register of the machine.

1.

< assign > : : = id := < exp > GETA (< exp >) generate [ STA ST (id)] REGA : = null

2. <exp> :: =< term >

ST < exp > : = ST (< term >)

if ST < exp > = rA then

REGA : = < exp >

3.

< exp >1 : : = < exp >2 + < term >

if SR (< exp >2) = rA then

generate [ADD ST (< term >)]

else if ST (< term >) = rA then

generate [ADD ST (< exp >2)]

else

begin

GETA (< EXP >2)

generate [ADD ST(< term >)]

end

ST (< exp >1) : = rA

REGA : = < exp >1

4. < exp >1 : : = < exp >2 - < term >

if ST (< exp >2) = rA then

generate [SUB ST (< term >)]

else

begin

GETA (< EXP >2)

generate [ SUB ST (< term >)]

end SR (< exp >1) : = rA REGA : = < exp >1 5. < term > : : = < factor > ST (< term >) : = ST (< factor >) if ST (<term >) = rA then REGA : = < term >

6. < term >1 : : = < term >2 * < factor >

(24)

generate [ MUL ST (< factor >)]

else if S (< factor >) = rA then

generate [ MUL ST (< term >2)]

else

begin

GETA (< term >2)

generate [ MUL SrT(< factor >)]

end

ST (< term >1) : = rA

REGA : = < term >1

7. < term > : : = < term >2 DIV < factor >

if SR (< term >2) = rA then

generate [DIV ST(< factor >)]

else

begin

GETA (< term >2)

generate [ DIV ST (< factor >)]

end SR (< term >1) : = rA REGA : = < term >1 < factor > : : = id ST (< factor >) : = ST (id) 9. < factor > : : = int ST (< factor >) : = ST (int) 10. < factor > : : = < exp > ST (< factor >) : = ST (< exp >) if ST (< factor >) = rA then REGA : = < factor >

Fig. 21 Code Generation Routines

If the node specifies for either operand is rA, the corresponding value is already in register A, the routine simply generates a MUL instruction. The node specifier for the other operand gives the operand address for this MUL. Otherwise, the procedure GETA is called. The GETA procedure is shown in fig. 22.

Procedure - GETA (NODE)

begin

if REGA = null then

generate [LDA ST (NODE) ]

else if ST (NODE) π rA then begin

creates a new looking variable Tempi

generate [STA Tempi]

record forward reference to Tempi

ST (REGA) : = Tempi

Generate [LDA ST (NODE)]

end (if ≠ rA)

ST(NODE) : = rA REGA : = NODE

(25)

Fig. 22

The procedure GETA generates a LDA instruction to load the values associated to <term> 2 into register A. Before loading the value into A-register, it confirms whether A is null.

If it is not null it generates STA instruction to save the contents of register-A into Temp-variable. There can be number of Temp variable like Temp1, Temp2 . . . etc. The temporary variables used

during a completion will be assigned storage location at the end of the object program. The node specifies for the node associated with the value previously in register A, indicated by REGA is reset to indicate the temporary variable used.

After the necessary instructions are generated, the code-generation routine sets ST (< term >1) and REGA to indicate that the value corresponding to < terms >1 is now in register A.

This completes the code-generation action for the * operation.

The code-generation routine for ' + ' operation is the same as the ' * ' operation. The routine ' DIV ' and ' - ' are similar except that for these operations it is necessary for the first operand to be in register A. The code generation for < assign > consists of bringing the value to be assigned into register A (using GETA) and then generating a STA instruction.

The remaining rules in fig. 21 do not require the generation of any instruction since no computation and data movement is involved.

The object code generated for the assignment statement is shown in fig. 22. LDA SUMSQ DIV * 100 STA TMP1 LDA MEAN MUL MEAN STA TMP2 LDA TMP1 SUB TMP2 STA VARIABLE

Fig. 22

For the grammar < prog > the code-generation routine is shown in fig. 23. When <prog> is recognized, storage locations are assigned to any temporary (Temp) variables that have been used. Any references to these variables are then fixed in the object code using the same process performed for forward references by a one-pass assembler. The compiler also generates any modification records required to describe external references to library subroutine.

< prog > : : = PROGRAM < prog-name > VAR < dec list > BEGIN < stmp -- list > END.

generate [LDL RETADR] generate [RSUB]

for each Temp variable used do

generate [ Temp RESW 1]

insert [ J EXADDR ] {jump to first executable instruction}

in bytes 3 - 5 of object program. fix up forward reference to Temp variables generate modification records for external references generates [END].

The < prog-name > generates header information in the object program that is similar to that created from the START and EXTREF as assembler directives. It also generates instructions

(26)

to save the return address and jump to the first executable instruction in the compiled program. Fig. 24 shows the code generation routine for the

grammar < prog-name >. < Program > : : = id

generate [START 0]

generate [EXTREF XREAD, XWRITE] generate [STL RETADR]

add 3 to LC {leave room for jump to first executable instruction} generate [RETADR RESW 1]

Fig. 24

Similar to the previous generation routine fig. 25 shows the code-generation for < dec - list >, < dec > , < write >, < for > , < index - exp > and body.

< dec - list > : : = { alternatives }

save LC as EXADDR {tentative address of first executable instruction}

< dec > : : = > id - list > : < type > for each item on list do

begin

remove ST (NAME) from list

enter LC symbol table as address for NAME generate [ST (NAME) RESW 1]

end

LIST COUNT : = 0 < write > : : = WRITE ( < id - list > )

generate [ + JSUB XWRITE] record external reference to XWRITE generate [WORD LISTCOUNT]

for each item on list do begin

remove ST (ITEM) from list generate [WORD ST (ITEM)] end

LIST COUNT : = 0

< for > : : = FOR < id ex -- exp > Do < body >

POP JUMPADDR from stack {address of jump out of loop} POP ST (INDEX) from stack {index variable}

POP LOOPADDR from stack {beginning address of loop} generate [LDA ST (INDEX)]

generate [ADD #1] generate [ J LOOPADDR]

insert [ JGT LC ] at location JUMPADDR < index - exp > : : = id : = < exp > | TO < exp >2

GETA (< exp >;)

Push LC onto stack {beginning addressing loop} Push ST (id) onto stack {index variable}

(27)

Generate [STA ST (id)]

Generate [ COMP ST (< exp > 2)]

Push LC onto stack {address of jump out of loop} and 3 to LC [ leave room for jump instruction] REGA : = null

Fig. 25

There are no code-generation for the statements < type > : : = INTEGER

< stmt - list > : : = {either alternative} < stmt > : : = {any alternative} < body > : : = {either alternative}

For the Pascal program in fig. 1 the complete code-generation process is shown in fig. 26.

1 STATS START

0 {Program Header}

EXTREF XREAD, XREAD, XWRITE

STL

TETADR

{Save return address}

J

{EXADDR}

2 RETADDR RESW

1 3 SUM

RESW 1

SUMSQ RESW 1

I

RESW 1

VALUE

RESW 1

MEAN

RESW 1

VARIANCE

RESW 1

5 {EXADDR} LDA

# 0

{SUM = 0}

STA SUM

6 LDA # 0

{SUMSQ : = 0}

STA

SUMSQ

7 LDA # 1

{FOR I : = 1 TO 100}

{L1}

STA

I

COMP # 100

JGT

{L2}

9 + JSUB

X READ

{READ (VALUE) }

WORD

1 WORD

VALUE

10 LDA SUM

{SUM : = SUM +

VALUE}

ADD VALUE

STA

SUM

11 LDA VALUE {SUMSQ : = SUMSQ * VALUE *

VALUE}

MUL VALUE

ADD SUMSQ

STA

SUMSQ

(28)

ADD # 1

J

{L1}

13 {L2}

LDA SUM

{MEAN : = SUM

DIVISION}

DIV

# 100

STA

MEAN

14 LDA SUM

{VARIABLE : = SUMSQ DIV

DIV # 100 100 - MEAN * MEAN}

STA

TEMP1

LDA MEAN

MUL MEAN

STA

TEMP2

LDA TEMP1

SUB TEMP2

STA

VARIANCE

15 +JSUB XWRITE

{WRITE (MEAN, VARIANCE) }

WORD

2 WORD

MEAN

WORD

VARIABLE

LDL RETADR

RSUB

TEMP 1` RESW 1

{WORKING VARIABLE USED}

TEMP 2 RESW 1

END

Fig. 25 Object Code Generated for Pascal Program

8.1 MACHINE DEPENDENT COMPILER FEATURES

At an elementary level, all the code generation is machine dependent. This is because, we must know the instruction set of a computer to generate code for it. There are

many more complex issues involved. They are:  Allocation of register

 Rearrangement of machine instruction to improve efficiency of execution

Considering an intermediate form of the program being compiled normally does such types of code optimization. In this intermediate form, the syntax and semantics of the source statements have been completely analyzed, but the actual translation into machine code has not yet been performed. It is easier to analyze and manipulate this intermediate code than to perform the operations on either the source program or the machine code. The intermediate form made in a compiler, is not strictly dependent on the

machine for which the compiler is designed.

8.1.1 INTERMEDIATE FORM OF THE PROGRAM

The intermediate form that is discussed here represents the executable instruction of the program with a sequence of quadruples. Each quadruples of the form

Operation, OP1, OP2, result. Where

(29)

OP 1 & OP2 - are the operands for the operation and Result - designation when the resulting value is to be placed.

Example 1: SUM : = SUM + VALUE could be represented as

+ , SUM, Value, i, i1

: = i1 , , SUM

The entry i1, designates an intermediate result (SUM + VALUE); the second quadruple

assigns the value of this intermediate result to SUM. Assignment is treated as a separate operation ( : =).

Example 2 : VARIANCE : = SUMSQ, DIV 100 -- MEAN * MEAN

DIV, SUMSQ, #100, i1

*, MEAN, MEAN, i2 - , i1, i2, i3

: : =

i

3 ,

VARIABLE

Note: Quadruples appears in the order in which the corresponding object code

instructions are to be executed. This greatly simplifies the task of analyzing the code for purposes of optimization. It is also easy to translate

into machine instructions.

For the source program in Pascal shown in fig. 1. The corresponding quadruples are shown in fig. 27. The READ and WRITE statements are represented with a CALL operation, followed by PARM quadruples that specify the parameters of the READ or WRITE. The JGT operation in quadruples 4 in fig. 27 compares the values of its two operands and jumps to quadruple 15 if the first operand is greater than the second. The J operation in quadruples 14 jumps unconditionally to quadruple 4.

Line Operation OP 1 OP 2 Result Pascal Statement

1. : = # 0 SUM SUM : = 0

2. : = # 0 SUMSQ SUMSQ : = 0 3. : = # 1 I FOR I : = 1 to 100 4. JGT I #100 (15)

5. CALL XREAD READ (VALUE) 6. PARAM VALUE

7. + SUM VALUE i1 SUM : = SUM + VALUE

; = i1 SUM

9. * VALUE VALUE i2 SUMSQ : = SUMSQ + VALUE

10. + SUMSQ i2 i3 * VALUE

11. : = i3 SUMSQ

12. + I #1 i4 End of FOR loop

13. : = i4 I

14. J (4)

15. DIV SUM #100 i5 MEAN : = SUM DIV 100

16. : = i5 MEAN

17. DIV SUMSQ #100 i6 VARIANCE : =

1 * MEAN MEAN i7 SUMSQ DIV 100

19. - i6 i7 i8 - MEAN * MEAN

20. : = i8 VARIANCE

(30)

22. PARAM MEAN 23. PARAM VARIANCE

Fig. .27 Intermediate Code for the Pascal Program

8.1.2 MACHINE - DEPENDENT CODE OPTIMIZATION

There are several different possibilities for performing machine-dependent code optimization .

-- Assignment and use of registers: Here we concentrate the use of registers as instruction operand. The bottleneck in all computers to perform with high speed is the access of data from memory. If machine instructions use registers as operands the speed of operation is much faster. Therefore, we would prefer to keep in registers all variables and intermediate result that will be used later in the program.

There are rarely as many registers available as we would like to use. The problem then becomes which register value to replace when it is necessary to assign a register for some other purpose. On reasonable approach is to scan the program for the next point at which each register value would be used. The value that will not be needed for the longest time is the one that should be replaced. If the register that is being reassigned contains the value of some variable already stored in memory, the value can simply be discarded. Otherwise, this value must be saved using a temporary variable. This is one of the functions performed by the GETA procedure. In using register assignment, a compiler must also consider control flow of the program. If they are jump operations in the program, the register content may not have the value that is intended. The contents may be changed. Usually the existence of jump instructions creates difficulty in keeping track of registers contents. One way to deal with the problem is to divide the problem into basic blocks.

A basic block is a sequence of quadruples with one entry point, which is at the beginning of the block, one exit point, which is at the end of the block, and no jumps within the blocks. Since procedure calls can have unpredictable effects as register contents, a CALL operation is usually considered to begin a new basic block. The assignment and use of registers within a basic block can follow as described previously. When control passes from one block to another, all values currently held in registers are saved in temporary variables.

For the problem is fig. .27, the quadruples can be divided into five blocks. They are:

Block -- A Quadruples 1 - 3 Block -- B Quadruples 4 Block -- C Quadruples 5 - 14 Block -- D Quadruples 15 - 20 Block -- E Quadruples 21 - 23

Fig. 28

Fig. 28 shows the basic blocks of the flow group for the quadruples in fig. 27. An arrow from one block to another indicates that control can pass directly from one quadruple to another. This kind of representation is called a flow group.

A : 1 - 3

B : 4

C : 5 - 14

D : 15 -

E : 21 -

(31)

-- Rearranging quadruples before machine code generation:

Example : 1) DIV SUMSQ # 100 i1

2) * MEAN MEAN i2

3) - i1 i2 i3

4) : = i3 VARIANCE

LDA SUMSQ LDA T1

DIV # 100 SUB T2

STA T1 STA VARIANCE

LDA MEAN MUL MEAN STA T2

Fig. 29

Fig. 29 shows a typical generation of machine code from the quadruples using only a single register.

Note that the value of the intermediate result, is calculated first and stored in temporary variable T1. Then the value of i2 is calculated subtracting i2 from ii.

Even though i2 value is in the register, it is not possible to perform the subtraction

operation. It is necessary to store the value of i2 in another temporary variable T2 and then load

the value of i1 from T1 into register A before performing the subtraction.

The optimizing compiler could rearrange the quadruples so that the second operand of the subtraction is computed first. This results in reducing two memory

accesses. Fig. 29 shows the rearrangements. * MEAN MEAN i2 DIV SUMSQ # 100 i1 - i1 i2 i3 := i3 VARIANCE LDA MEAN MUL MEAN STA T1 LDA SUMSQ DIV # 100 SUB T1 STA VARIANCE

Fig. 29 Rearrangement of Quadruples for Code Optimization

-- Characteristics and Instructions of Target Machine: These may be special loop - control instructions or addressing modes that can be used to create more efficient object code. On some computers there are high-level machine instructions that can perform complicated functions such as calling procedure and manipulating data structures in a single operation.

Some computers have multiple functional blocks. The source code must be rearranged to use all the blocks or most of the blocks concurrently. This is possible if the result of one block does not depend on the result of the other. There are some systems where the data flow can be arranged between blocks without storing the intermediate data in any register. An optimizing compiler for such a machine could rearrange object code