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Building a Simple Compiler with Recursive-Descent Parsing: A Step-by-Step Guide for CSE340

Learn how to implement a simple compiler using recursive-descent parsing, semantic analysis, and execution for a custom language. This guide breaks down the CSE340 Fall 2025 Project 1 into manageable steps with real-world analogies.

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Introduction: Why Compilers Matter in 2026

In 2026, compilers are more relevant than ever. From AI code generators like GitHub Copilot to just-in-time compilation in JavaScript engines, understanding how source code becomes executable is a superpower. The CSE340 Fall 2025 Project 1 tasks you with building a simple compiler for a custom language. This guide will walk you through the core concepts, focusing on recursive-descent parsing, semantic checking, and execution—without giving away the full solution.

Understanding the Project Structure

Your compiler reads a program with four sections: TASKS, POLY, EXECUTE, and INPUTS. The TASKS section lists which features to enable. POLY declares polynomials (like functions). EXECUTE contains statements (assignments, I/O, etc.). INPUTS provides a stream of numbers for INPUT statements. Your job is to parse this input, detect syntax errors, then perform semantic analysis and execute if no errors exist.

Think of it like a TikTok trend: you receive a template (the grammar), you fill in your content (the program), and the compiler checks if it's valid before posting (executing).

Recursive-Descent Parsing: The Heart of Your Compiler

Recursive-descent parsing is a top-down method where each non-terminal in the grammar becomes a function. For example, a function parseProgram() might call parseTasks(), parsePoly(), etc. You'll use the provided LexicalAnalyzer class to get tokens via GetToken() and peek(). The expect() function helps verify expected tokens.

This approach is like following a recipe for a viral pasta dish: each step (function) handles one ingredient (token) and passes control to the next step.

Example: Parsing a Polynomial Declaration

Consider the grammar rule: poly_decl -> IDENT EQUAL poly_body SEMICOLON. Your parsePolyDecl() function would expect an IDENT token, then EQUAL, parse the body, and finally expect SEMICOLON. If any token is missing, you report a syntax error.

void Parser::parsePolyDecl() {
    expect(IDENT);
    expect(EQUAL);
    parsePolyBody();
    expect(SEMICOLON);
}

This pattern repeats for every grammar rule. The key is to look ahead (peek) to decide which production to follow, avoiding ambiguity.

Semantic Analysis: Beyond Syntax

Once syntax is correct, your compiler checks semantic rules. For example, in polynomial declarations, the variables used in the body must match the declared parameters. If a polynomial G(X,Y) = X Y^2 + X Z uses Z which is not declared, that's a semantic error (code 2).

This is like verifying that all tags in a social media post are actually defined before posting. Your compiler must store the AST or symbol table to cross-check.

Data Structures for Semantic Analysis

You'll need structures to store polynomials: name, parameter list, and body expression. Use maps or vectors to hold these. For execution, maintain a runtime environment where variables get values from INPUT or assignments.

Trend analogy: Think of the symbol table as a fantasy football roster—each player (variable) has a name and stats (value). When you trade (assign), you update the stats.

Execution: Running the Program

If no errors, your compiler executes the statements in the EXECUTE section. For each assignment like X = F(4), you evaluate the polynomial F with argument 4. Polynomial evaluation involves substituting the variable with the given number and computing the result.

For example, F = x^2 + 1 with x=4 yields 17. Your compiler must handle arithmetic, possibly using a simple expression evaluator.

Handling INPUT and OUTPUT

INPUT reads from the INPUTS list in order. OUTPUT prints the value. This mimics reading user input in a real program. In 2026, this is like a chatbot reading your message and replying—simple but foundational.

Common Pitfalls and Tips

  • One lexer instance: Do not create multiple LexicalAnalyzer objects; it will break.
  • Read the grammar carefully: Understand the difference between poly_decl and poly_body. The grammar is your contract.
  • Test incrementally: Start with parsing a valid program, then add error detection, then semantic checks, then execution.
  • Use the provided code: Don't modify lexer.cc or inputbuf.cc. They handle tokenization and input buffering.

Connecting to Real-World Trends

In 2026, AI-assisted coding tools like Copilot and CodeWhisperer rely on parsing and semantic analysis to suggest code. Your simple compiler uses the same principles: tokenization, parsing, and semantic checking. Even the viral app BeReal uses a compiler-like process to verify photo metadata before posting.

By mastering this project, you're not just passing CSE340—you're building skills used in modern compilers, interpreters, and even AI models that generate code.

Conclusion

Building a simple compiler is a rite of passage in computer science. The CSE340 Fall 2025 Project 1 teaches you recursive-descent parsing, semantic analysis, and execution. Break the project into tasks, understand the grammar, and test early. With this guide, you'll be ready to tackle syntax errors, semantic mistakes, and finally run your own language.