Depth understanding of Building AI system (Compilers) ..
To build an AI system able to handle very intense data there several complex components we should integrate including compiler, distributed system, and formal methods.
A compiler is a specialized type of computer software that translates source code written in a programming language (the source language) into another language (the target language). The primary purpose of a compiler is to turn the source code, which is human-readable and written in high-level programming languages like C, Java, or Python, into machine code, which can be executed by a computer's central processing unit (CPU).
The process of compiling typically involves several stages:
Lexical Analysis
Lexical analysis is the first phase in the process of compiling a program, where the source code is transformed into a sequence of tokens.. Here's a detailed breakdown of what happens during lexical analysis:
1. Tokenization
2. Removing Whitespaces and Comments
3. Character Stream to Token Stream
4. Error Handling
5. Symbol Table Creation
6. Regular Expressions
7. Efficiency
8. Lexical Analyzer Tools
To demonstrate lexical analysis, let's consider a simple example: a program to add two numbers in both C++ and Python. I'll provide the code for each, followed by an explanation of how lexical analysis would be applied to them
// C++
#include <iostream>
using namespace std;
int main() {
int a = 5;
int b = 3;
int sum = a + b;
cout << "The sum is: " << sum << endl;
return 0;
}
Lexical Analysis on C++ Code
#Python
# Simple program to add two numbers
a = 5
b = 3
sum = a + b
print("The sum is:", sum)
Lexical Analysis on Python Code
Implementing Lexical Analysis
To implement lexical analysis, you would define the rules for identifying these tokens. For instance:
Example Implementation for Python:
Here's a very basic implementation of a lexical analyzer in Python:
import re
# Define token patterns
token_patterns = {
'INTEGER': r'\d+',
'IDENTIFIER': r'[a-zA-Z_][a-zA-Z0-9_]*',
'OPERATOR': r'[+\-*/]',
'PUNCTUATION': r'[;:,]',
'STRING': r'\".*?\"'
}
# Sample source code
code = 'a = 5; b = 3; sum = a + b; print("The sum is:", sum);'
# Tokenizing function
def tokenize(code):
tokens = []
while code:
match = None
for token_type, pattern in token_patterns.items():
regex = re.compile(pattern)
match = regex.match(code)
if match:
value = match.group(0)
tokens.append((token_type, value))
code = code[match.end():]
break
if not match:
raise SyntaxError(f'Illegal character: {code[0]}')
return tokens
# Tokenize the sample code
tokenized_code = tokenize(code)
print(tokenized_code)
Implementing a Syntax Analyzer for These Examples:
Given the simplicity of these examples, a generalized parser could look like:
Simplified Grammar:
For both examples, the grammar can be simplified to:
program → statement*
statement → declaration | expressionStmt | printStmt
declaration → "int" IDENTIFIER "=" expression ";"
expressionStmt → expression ";"
printStmt → "print" "(" expression ")"
expression → IDENTIFIER | NUMBER | expression "+" expression
class Token:
def __init__(self, type, value):
self.type = type
self.value = value
class Parser:
def __init__(self, tokens):
self.tokens = tokens
self.current_token = None
self.next_token()
def next_token(self):
self.current_token = self.tokens.pop(0) if self.tokens else Token('EOF', None)
def eat(self, token_type):
if self.current_token.type == token_type:
self.next_token()
else:
raise Exception(f"Unexpected token: {self.current_token.type}, expected: {token_type}")
def expression(self):
# expression → term (( "+" | "-" ) term)*
result = self.term()
while self.current_token.type in ('+', '-'):
operator = self.current_token
self.eat(operator.type)
if operator.type == '+':
result += self.term()
elif operator.type == '-':
result -= self.term()
return result
def term(self):
# term → factor (( "*" | "/" ) factor)*
result = self.factor()
while self.current_token.type in ('*', '/'):
operator = self.current_token
self.eat(operator.type)
if operator.type == '*':
result *= self.factor()
elif operator.type == '/':
result /= self.factor()
return result
def factor(self):
# factor → NUMBER | "(" expression ")"
token = self.current_token
if token.type == 'NUMBER':
self.eat('NUMBER')
return token.value
elif token.type == '(':
self.eat('(')
result = self.expression()
self.eat(')')
return result
# Example usage
tokens = [Token('NUMBER', 5), Token('+', '+'), Token('NUMBER', 3)]
parser = Parser(tokens)
result = parser.expression()
print(result) # Output: 8
Type of Compilers :
1. Single-Pass Compilers
2. Multi-Pass Compilers
3. Source-to-Source Compilers (Transpilers)
4. Cross Compilers
5. Optimizing Compilers
6. Just-In-Time (JIT) Compilers
7. Ahead-of-Time (AOT) Compilers
8. Hardware Specific Compilers
9. Bootstrapping Compilers
10. Decompilers
11. Profile-Guided Optimizing Compilers