Book Image

Build Your Own Programming Language - Second Edition

By : Clinton L. Jeffery
Book Image

Build Your Own Programming Language - Second Edition

By: Clinton L. Jeffery

Overview of this book

There are many reasons to build a programming language: out of necessity, as a learning exercise, or just for fun. Whatever your reasons, this book gives you the tools to succeed. You’ll build the frontend of a compiler for your language and generate a lexical analyzer and parser using Lex and YACC tools. Then you’ll explore a series of syntax tree traversals before looking at code generation for a bytecode virtual machine or native code. In this edition, a new chapter has been added to assist you in comprehending the nuances and distinctions between preprocessors and transpilers. Code examples have been modernized, expanded, and rigorously tested, and all content has undergone thorough refreshing. You’ll learn to implement code generation techniques using practical examples, including the Unicon Preprocessor and transpiling Jzero code to Unicon. You'll move to domain-specific language features and learn to create them as built-in operators and functions. You’ll also cover garbage collection. Dr. Jeffery’s experiences building the Unicon language are used to add context to the concepts, and relevant examples are provided in both Unicon and Java so that you can follow along in your language of choice. By the end of this book, you'll be able to build and deploy your own domain-specific language.
Table of Contents (27 chapters)
1
Section I: Programming Language Frontends
7
Section II: Syntax Tree Traversals
13
Section III: Code Generation and Runtime Systems
22
Section IV: Appendix
23
Answers
24
Other Books You May Enjoy
25
Index

Answers

The following answers sketch some possible solutions to the questions at the end of each chapter; these are provided for your reflection.

Chapter 1

  1. It is much easier to generate C code than to generate machine code, but the resulting code may be larger or slower than native code, causing a performance cost. A transpiler depends on an underlying compiler that may be a bit of a moving target, but if the underlying compiler is highly portable, the transpiler will be far more portable than a compiler that generates native code.
  2. Lexical, syntax, and semantic analysis, followed by intermediate and final code generation.
  3. Classic pain points include input/output being overly difficult, especially on new kinds of hardware; concurrency; and making a program run across many different operating systems and CPUs. One feature that languages have used to simplify input/output has been to reduce the problem of communicating with new hardware via a set of strings...