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Language Processor Implementation
using Python
Objectiv
e


Implement parser, syntax analyzer, semantic
analyzer for Pascal language



Show main approaches to implementation of
semantic analysis as well as intermediary code
generation



Parameterize language processor
Choosing Programming
Language

I investigated strong and week points of
several programming languages:
 Java
 Perl
 Python
 C++
 Delphi
As a result I chose Python due to several very good
reasons.
Python
Benefits

High level programming language
 Supports object oriented paradigm
 Convenient data types
 Relatively fast due to using C based libraries
 Easy readable syntax
 Cross-platform
 Convenient tools for parsing YAML
 Supports regular expressions out of the box

Language Processor Work
Scheme
Entry

Parser

Syntax

Semantics

Code gen

Exit
Вихід
In memory tables
Parser.
Tokens
Identifier

^[A-Za-z][A-Za-z_0-9]{0,255}$
Integer Const
^[+-]?d{1,10}$
Float Const
^([+-]?((d+.d+)|(d+.d+e[+-]d+)))$
String Literal
^'.{0,65535}'$
Algorythm of Analyzing
Lexems

def getClass(self, word):
c = None
if ((word in self.KeyWords)
or (word in metadata["delimiters"])
or (word in metadata["double"])
or (word in metadata["conditional_delimiters"])
or (word in metadata["multiplicative"])
or (word in metadata["additive"])
or (word in metadata["Relation"])):
c = word
else:
for r in self.RegExp.keys():
if re.compile(r).match(word):
c = self.RegExp[r]
return c
Attribute Table



Separate class



Design pattern Singleton



Uses hash table as internal structure



Fast access



Convenient format
Attribute Table Look
Syntax
Analyzer


Context free grammar



Left associated grammar



EBNF



Configuration format is yaml



Language grammar is easily changed without
source code modification
YAML Configuration Format
Benefits


Short and readable



yaml uses data structures that are native to
programming languages like Perl, Python
Configuration Format of Language
Grammar

EBNF

rule
program ::=
EBNF

Program ID ; block .

rule in configuration
programme:
- [program, id, ;, Block, "."]
Semantic Analyzer. Semantic
Actions
Rule

without semantic actions
complex_action:
- [begin, action_list, end]
Rule

with semantic actions
complex_action:
- [begin, "#200", action_list, end, "#220"]
Attribute
classes
Making

code generation process easier, I created a
bunch of classes like AttrFor.

class

AttrFor (AttrObject):

self.parameter = None
self.first = None
self.last = None
self.step = None
self.body = None
Abstract Parse
Tree
Intermediary code
generation
We

are using tetrads language in order to generate
intermediary code
How tetrads language looks:
Z := X op Y
Z := op X
Z := Y
Z := Y[X]
Z:
GOTO Z
If condition GOTO Z
Example of input file
program q;
var
a, b: integer;
i: integer;
d: integer;
begin
d := 4;
for i:= 1 to (2+2*2)*2 do
begin
b:=b + 1;
a:=a * 2;
end;
d:=a;
end.
Output of language processor using intermediary code

d:=4
i:=1
@Lid1:
if i > 12 goto @Lid2
b:=b + 1
a:=a * 2
i := i + 1
goto @Lid1
@Lid2:
d:=a
Bottom line


I implemented parser, syntax analyzer, semantic analyzer,
intermediary code generation of Pascal programming
language



I showed main concepts of semantic analysis as well as
intermediary code generation



Language processor has been parameterized
Ad

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Language processor implementation using python