CF

Parsing Algorithms

4h 27m 33s
English
Paid

Parsing, or syntactic analysis, is one of the essential initial stages in designing and implementing a compiler. A well-designed syntax of your programming language motivates users to prefer and choose your language over others.

The Challenges in Learning Parsing Theory

The primary issue with traditional "parser theory" in classic compiler courses and books is its perception as "too advanced," often diving directly into complex formal descriptions from the Theory of Computation and formal grammars. Consequently, students may lose interest in building a compiler at the parsing stage.

Common Missteps in Parser Instruction

Another common issue is a superficial teaching approach that covers only manual (usually recursive descent) parsing. This method often leaves students struggling to understand the actual techniques behind automated parsers.

A Combined Approach to Learning Parsing

I advocate for a deep dive into parsing theory combined with a hands-on approach. This method allows students to apply the theoretical material in practice simultaneously, enhancing understanding and engagement.

About the Essentials of Parsing Course

In the Essentials of Parsing (also known as Parsing Algorithms) class, we explore various aspects of parsing theory, with detailed descriptions of both LL and LR parsers. To make the learning process enjoyable and comprehensible, we simultaneously construct an automatic parser for a full programming language from scratch, akin to JavaScript or Python.

Outcome of the Course

Upon completing this class, you will not only be able to use a parser generator to build parsers for programming languages but will also understand how these parser generators function internally.

Implementing a parser for a programming language will enhance your professional use of other programming languages as well.

About the Authors

Dmitry Soshnikov

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Dmitry Soshnikov is a Russian software engineer and educator focused on programming-language internals, compiler construction, JavaScript engine architecture, and the theoretical computer-science foundations underneath modern software development. His independent course catalog is one of the deepest sources of long-form material on language implementation available outside university CS programs.

His CourseFlix listing carries nine courses spanning parser combinators, interpreter construction, garbage-collection algorithm internals, the design of pattern-matching engines, and JavaScript object-model deep dives. Material is paid and aimed at engineers who want to understand how the languages they use every day actually work under the hood.

Udemy

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Udemy is the largest open marketplace for online courses on the internet. Founded in 2010 by Eren Bali, Oktay Caglar, and Gagan Biyani and headquartered in San Francisco, the company went public on the Nasdaq in 2021 under the ticker UDMY. The platform hosts well over two hundred thousand courses across software development, IT and cloud, data science, design, business, marketing, and creative skills, taught by tens of thousands of independent instructors. Roughly seventy million learners use it worldwide, and the corporate arm — Udemy Business — supplies a curated subset of that catalog to enterprise customers.

Because Udemy is a marketplace rather than a single editorial publisher, the catalog is uneven by design. The strongest material lives in the long-form, project-based courses authored by working engineers — full-stack JavaScript, React, Node.js, Python data science, AWS, Docker and Kubernetes, mobile development with Flutter and React Native, and cloud certification preparation. The CourseFlix listing under this source is the slice of that catalog that has been mirrored here for offline-friendly viewing, organized by topic and updated as new releases land. Pricing on Udemy itself swings dramatically with the site's near-permanent sales, which is why the platform is best treated as a deep reference catalog: pick instructors with strong reviews and a track record of updating their material rather than buying on the headline price alone.

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#1: Formal grammars, context-free
All Course Lessons (22)
#Lesson TitleDurationAccess
1
Formal grammars, context-free Demo
12:13
2
Grammar derivations
12:51
3
Ambiguous grammars
09:20
4
Syntax tool | Letter
13:42
5
Abstract Syntax Trees
12:59
6
Backtracking parser
13:32
7
Left-recursion and Left-factoring
11:15
8
Predictive Recursive descent parser
06:15
9
LL(1) parsing: First & Follow sets
21:28
10
Construction of LL(1) parsing table
12:21
11
LL(1) parsing algorithm
10:56
12
Back to practice: Statements | Blocks
13:14
13
Function Declarations
15:59
14
LR parsing: Canonical Collection of LR-items
16:26
15
LR parsing table: LR(0) and SLR(1)
12:30
16
CLR(1) and LALR(1) parsing tables
16:18
17
LR(1) parsing algorithm
11:48
18
Control structures: If-statement
14:18
19
Variables | Assignment
07:52
20
Function calls | Unary expression
05:48
21
Member expression | Iteration
06:33
22
OOP | Final parser
09:55
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Frequently asked questions

What prerequisites should I have before taking this course?
Before enrolling in the Parsing Algorithms course, it's beneficial to have a foundational understanding of programming and basic concepts of formal grammars. Familiarity with programming languages like JavaScript or Python will be helpful since the course involves constructing a parser for a full programming language similar to these. Previous exposure to compiler design concepts can also provide a smoother learning experience.
What will I be able to build by the end of this course?
By the end of the course, students will be able to construct an automatic parser for a complete programming language, akin to JavaScript or Python. The course covers the detailed process of building both LL and LR parsers, providing practical experience in parsing a language from scratch, which includes constructing Abstract Syntax Trees and implementing control structures like If-statements.
Who is the target audience for this course?
The course is designed for individuals interested in understanding parsing theory and its application in compiler design. It suits computer science students, software engineers, and developers who want to deepen their knowledge of parsing algorithms and enhance their skills in language processing and compiler construction.
How does this course compare to other parsing or compiler courses in terms of depth?
Unlike traditional compiler courses that often present parsing theory as overly advanced and abstract, this course combines theoretical insights with practical application. It offers a deep dive into both LL and LR parsers, focusing on hands-on construction of a parser from scratch, thereby bridging the gap between theory and practice.
Which specific parsing techniques and tools are covered in this course?
The course covers a range of parsing techniques including predictive recursive descent parsing, LL(1) parsing with First & Follow sets, and construction of LL(1) parsing tables. It also delves into LR parsing, exploring LR(0), SLR(1), CLR(1), and LALR(1) parsing tables, giving students a comprehensive understanding of both manual and automated parsing methods.
What topics are not covered in this course?
The course does not cover advanced compiler optimization techniques or code generation for specific machine architectures. It focuses primarily on parsing algorithms and the construction of parsers, leaving out topics related to semantic analysis, runtime environments, and the final stages of compiler construction beyond parsing.
What is the expected time commitment for completing this course?
The course consists of 22 lessons, and although the total runtime is not specified, students should expect to dedicate several hours per week to watch the lectures and complete the hands-on exercises. The time commitment will vary depending on individual learning pace and prior experience with parsing and programming concepts.