CF

Garbage Collection Algorithms

2h 13m 20s
English
Paid

Master the complexities of memory management and ensure your programs run efficiently by understanding the intricacies of Garbage Collection Algorithms. This course is designed to equip you with the knowledge to tackle memory leaks and dangling pointers, which are prevalent issues in manual memory management.

Course Overview

Automatic memory management is a key feature in most modern high-level programming languages. Unlike manual memory allocation and deallocation, the garbage collector manages memory automatically, ensuring efficient usage and reuse. This course, Essentials of Garbage Collectors, delves into various techniques and algorithms in practice today.

Target Audience

Compiler Engineers

This course is particularly beneficial for compiler engineers. If you're designing a language, you'll likely need to implement a garbage collector. Even languages like Rust, known for memory safety, adopted automatic reference counting (ARC) and other collectors.

Other Engineers

If you aren't a compiler engineer, this class still holds value. Building a garbage collector is an advanced engineering task that enhances your understanding of complex systems, providing transferable skills and a deeper knowledge of data structures and algorithms.

Language Requirements

You don’t need to rely exclusively on C or C++ for this project. Although they are excellent for raw memory manipulations, this course focuses on theoretical aspects and generic design algorithms. Implement these concepts in any language, such as JavaScript, Python, or Rust.

Most algorithms are presented in generic pseudo-code to facilitate porting to any programming language.

Course Structure

  • Concise Lectures: Each lecture is focused and to-the-point, concentrating solely on relevant content.
  • Animated Presentations: Dynamic visuals and live-editing notes help simplify complex topics, avoiding the limitations of static slides.

Recommended Reading

Augment your learning with these recommended books:

  • The Garbage Collection Handbook: The Art of Automatic Memory Management by Antony Hosking, Eliot Moss, and Richard Jones
  • The Compiler Design Handbook: Optimizations and Machine Code generation by Y.N. Srikant, Priti Shankar

Course Requirements

Requirements:
  • Understanding of basic data structures and algorithms (trees, graphs, linked lists, etc.)
  • Basic knowledge of computer memory (bytes, addresses, pointers)

Intended Learners

Who this course is for:
  • Compiler engineers
  • Engineers eager to learn about sophisticated memory management algorithms and apply their generic knowledge to other systems

Learning Outcomes

What you'll learn:

  • Foundations of Automatic Memory Management algorithms and data structures
  • History and types of memory management: Static, Stack, Heap allocations
  • Virtual memory concepts and Memory Layout
  • Differences between Tracing and Direct collectors
  • Understanding Semantic and Syntactic garbage
  • Implementing various collectors: Mark-Sweep, Mark-Compact, Reference counting, Copying, Generational
  • Exploring Parallel, Incremental, and Concurrent collectors
  • Tri-color abstraction and its role in marking
  • GC Barriers and their application

About the Authors

Dmitry Soshnikov

Dmitry Soshnikov thumbnail

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

Udemy thumbnail

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: Allocation types
All Course Lessons (17)
#Lesson TitleDurationAccess
1
Allocation types Demo
05:07
2
Manual memory management
03:56
3
Object header
03:20
4
Virtual memory and Memory layout
08:58
5
Mutator, Allocator, Collector
04:36
6
Allocators: Free-list vs. Sequential
08:57
7
Semantic vs. Syntactic garbage
04:43
8
Tracing vs. Direct collectors
06:10
9
Mark-Sweep collector
07:43
10
Mark-Compact collector
10:17
11
Copying collector
11:02
12
Reference counting collector
09:47
13
Generational collector
08:38
14
Mark-Region GC: Immix collector
12:59
15
Parallel, Incremental, Concurrent GC
07:22
16
Tri-color abstraction
07:32
17
GC barriers
12:13
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Frequently asked questions

What are the prerequisites for enrolling in this course?
Prospective students should have a solid understanding of programming concepts and be familiar with high-level programming languages that utilize automatic memory management. While a background in C or C++ can be beneficial for understanding raw memory manipulations, it is not mandatory, as the course focuses on theoretical aspects and generic design algorithms.
What kind of projects or systems will I be able to build after completing this course?
After completing the course, you will be equipped to design and implement various garbage collection algorithms, such as Mark-Sweep, Mark-Compact, and Copying collectors. You'll gain insights into building complex systems that require efficient memory management, which is crucial for developing programming languages or optimizing existing software systems.
Who is the target audience for this course?
The course is particularly beneficial for compiler engineers who are involved in designing programming languages and need to implement garbage collectors. Additionally, it holds value for other engineers interested in understanding complex systems and enhancing their knowledge of data structures and algorithms.
How does the depth of this course compare to other courses on similar topics?
This course provides a deep dive into the intricacies of garbage collection algorithms, covering a wide range of techniques such as Tracing vs. Direct collectors, Reference counting, and Generational collectors. It goes beyond basic concepts, exploring advanced topics like Parallel, Incremental, and Concurrent GC, making it more comprehensive than introductory courses.
What specific tools or platforms does the course focus on?
The course does not focus on specific tools or platforms. Instead, it emphasizes theoretical aspects and generic design algorithms applicable across different programming environments. It offers a conceptual understanding of garbage collection mechanisms, which can be applied in various contexts, including language design and software optimization.
What topics are not covered in this course?
The course does not cover topics related to the implementation of garbage collectors in specific programming languages or platforms. It also does not delve into basic programming concepts, assuming that students already have foundational knowledge in programming and memory management.
How can the knowledge gained from this course be applied in other areas or careers?
The knowledge gained from understanding garbage collection algorithms is highly transferable to other areas, such as systems programming, language design, and software optimization. It enhances your ability to manage memory efficiently, a crucial skill in developing robust and performant software across various industries.