Compiler Design¶

Topic Overview¶

Compiler design is one of the foundational areas of computer science, bridging the gap between human-readable programming languages and machine-executable code. A compiler translates source code written in a high-level language into a lower-level representation — typically machine code, bytecode, or another programming language — through a series of well-defined phases.

This topic covers the complete pipeline of compilation: from scanning raw characters into tokens, parsing tokens into structured representations, analyzing meaning, generating intermediate code, optimizing it, and finally producing target code. Along the way, you will encounter deep connections to formal language theory, algorithm design, graph theory, and computer architecture.

Understanding compiler design is valuable not only for building compilers but also for:

Language design: Creating domain-specific languages (DSLs) and configuration languages
Tool building: Writing linters, formatters, transpilers, and static analyzers
Performance understanding: Knowing what optimizations your compiler performs (and what it cannot do)
Software engineering: Applying patterns like visitors, interpreters, and intermediate representations to general software design
Security: Understanding how code injection, sandboxing, and code analysis tools work

Learning Objectives¶

By completing this topic, you will be able to:

Explain the phases of compilation and how they interact
Implement lexical analyzers using finite automata theory
Construct parsers using both top-down and bottom-up techniques
Design abstract syntax trees and perform semantic analysis
Generate intermediate representations and perform optimizations
Understand runtime environments, garbage collection, and virtual machines
Use modern compiler infrastructure (LLVM) for practical compilation tasks
Build a simple end-to-end compiler or interpreter for a small language

Prerequisites¶

Before studying Compiler Design, you should be comfortable with:

Algorithm (this project): Particularly graph algorithms, trees, and dynamic programming
Programming (this project): Strong grasp of data structures, recursion, and OOP
Python (this project): Most examples use Python for clarity
C_Programming (this project): Helpful for understanding low-level code generation
Discrete mathematics: Sets, relations, functions, proof techniques (induction, contradiction)
Basic computer architecture: Registers, memory, instruction sets (covered in Computer_Architecture)

Lesson Table¶

#	Title	Key Topics	Estimated Time
01	Introduction to Compilers	Compiler structure, phases, bootstrapping, T-diagrams	2-3 hours
02	Lexical Analysis	Tokens, regular expressions, DFA/NFA, lexer implementation	3-4 hours
03	Finite Automata	NFA-to-DFA conversion, minimization, Myhill-Nerode, Lex/Flex	3-4 hours
04	Context-Free Grammars	BNF, derivations, parse trees, ambiguity, CNF, CYK	3-4 hours
05	Top-Down Parsing	Recursive descent, LL(1), FIRST/FOLLOW sets	3-4 hours
06	Bottom-Up Parsing	LR(0), SLR, LALR, parser generators (Yacc/Bison)	4-5 hours
07	Abstract Syntax Trees	AST design, visitor pattern, tree traversal strategies	2-3 hours
08	Semantic Analysis	Type checking, symbol tables, scoping rules	3-4 hours
09	Intermediate Representations	Three-address code, SSA form, control flow graphs	3-4 hours
10	Runtime Environments	Activation records, calling conventions, stack frames	3-4 hours
11	Code Generation	Instruction selection, register allocation, tiling	3-4 hours
12	Optimization -- Local and Global	Data flow analysis, constant propagation, dead code elimination	4-5 hours
13	Loop Optimization	Loop-invariant code motion, strength reduction, vectorization	3-4 hours
14	Garbage Collection	Mark-Sweep, Copying, Generational, Reference Counting	3-4 hours
15	Interpreters and Virtual Machines	Bytecode, stack-based VM, JIT compilation basics	3-4 hours
16	Modern Compiler Infrastructure	LLVM IR, pass structure, DSL design	3-4 hours

Total estimated time: 50-65 hours

Learning Path Recommendations¶

Path 1: Foundations First (Recommended)¶

Follow the lessons in order. This path builds each concept on the previous ones:

01 Introduction
    |
02 Lexical Analysis  --->  03 Finite Automata
    |
04 Context-Free Grammars
    |
    +---> 05 Top-Down Parsing
    +---> 06 Bottom-Up Parsing
    |
07 Abstract Syntax Trees
    |
08 Semantic Analysis
    |
09 Intermediate Representations
    |
    +---> 10 Runtime Environments
    +---> 11 Code Generation
    +---> 12 Local/Global Optimization
    +---> 13 Loop Optimization
    |
14 Garbage Collection
    |
15 Interpreters and VMs
    |
16 Modern Compiler Infrastructure

Path 2: Quick Practical Compiler¶

If you want to build a working compiler or interpreter quickly:

01 Introduction  -->  02 Lexical Analysis  -->  04 CFGs  -->  05 Top-Down Parsing
    -->  07 ASTs  -->  08 Semantic Analysis  -->  15 Interpreters and VMs

Path 3: Optimization Focus¶

If you are interested in compiler optimizations and performance:

01 Introduction  -->  09 Intermediate Representations  -->  12 Local/Global Optimization
    -->  13 Loop Optimization  -->  11 Code Generation  -->  16 LLVM

Path 4: Language Theory¶

If you are interested in formal language theory and parsing:

02 Lexical Analysis  -->  03 Finite Automata  -->  04 CFGs
    -->  05 Top-Down Parsing  -->  06 Bottom-Up Parsing

Topic	Relevance
Algorithm	Graph algorithms (DFS, topological sort) used in data flow analysis and optimization
OS_Theory	Process memory layout, linking, loading — directly related to runtime environments
Computer_Architecture	Instruction sets, registers, caches — essential for code generation
Programming	Design patterns (Visitor, Interpreter) used extensively in compiler construction
Python	Implementation language for most examples in this topic
C_Programming	Target language understanding; many compilers are written in C
Math_for_AI	Linear algebra and graph theory concepts overlap with optimization algorithms

Recommended Textbooks and References¶

Aho, Lam, Sethi, Ullman — Compilers: Principles, Techniques, and Tools (2nd ed., "The Dragon Book")
Cooper, Torczon — Engineering a Compiler (2nd ed.)
Appel — Modern Compiler Implementation in ML/Java/C
Muchnick — Advanced Compiler Design and Implementation
Grune, Bal, Jacobs, Langendoen — Modern Compiler Design (2nd ed.)

Example Code¶

Example code for this topic can be found in examples/Compiler_Design/.

Examples include: - Lexer implementations (Python) - Parser implementations (recursive descent, operator precedence) - AST construction and traversal - Simple interpreter and bytecode VM - Optimization passes

This topic is part of the Study Materials collection.