A developer's comprehensive guide to crafting, compiling, and implementing programming languages
Clinton L. Jeffery
Programming_Language#
frontend#
Unicon#
Java#
Embark on a journey through essential components of language design, compiler construction, preprocessors, transpilers, and runtime systems in this second edition, authored by the creator of the Unicon programming language.
Key Features
Book Description
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.
What you will learn
Who this book is for
This book is for software developers interested in the idea of inventing their own language or developing a domain-specific language. Computer science students taking compiler design or construction courses will also find this book highly useful as a practical guide to language implementation to supplement more theoretical textbooks. Intermediate or better proficiency in Java or C++ programming languages (or another high-level programming language) is assumed.
Table of Contents
“I can solidly recommend this book! [It] takes a cohesive approach to not only the technology itself, but the design patterns and wider SDLC that should be considered to deliver a complete solution. You can see the author is aware of evidence-based approaches to process (i.e. Forsgren, Humble, Kim). I also appreciate how they went in-depth into […] not only your standard frontend to backend dissection, but also scaling, decoupling, multi-region, intersystem concerns, events, [and] observability.”
Imran Ahmad PhD, Senior Data Scientist, Canadian Federal Government
Clinton L. Jeffery is Professor and Chair of the Department of Computer Science and Engineering at New Mexico Institute of Mining and Technology. He received his B.S. from the University of Washington, and M.S. and Ph.D. degrees from the University of Arizona, all in computer science. He has conducted research and written many books and papers on programming languages, program monitoring, debugging, graphics, virtual environments, and visualization. With colleagues, he invented the Unicon programming language, hosted on the Unicon website.
Imran Ahmad has been a part of cutting-edge research about algorithms and machine learning for many years. He completed his PhD in 2010, in which he proposed a new linear programming-based algorithm that can be used to optimally assign resources in a large-scale cloud computing environment. In 2017, Imran developed a real-time analytics framework named StreamSensing. He has since authored multiple research papers that use StreamSensing to process multimedia data for various machine learning algorithms. Imran is currently working at Advanced Analytics Solution Center (A2SC) at the Canadian Federal Government as a data scientist. He is using machine learning algorithms for critical use cases. Imran is a visiting professor at Carleton University, Ottawa. He has also been teaching for Google and Learning Tree for the last few years.