Introduction to the Course

Performant Software Systems with Rust — Lecture 1

Baochun Li, Professor
Department of Electrical and Computer Engineering
University of Toronto

About me

function hello(name) {
    return "hello " + name
}

Baochun Li

• B.Eng., CS, Tsinghua University (1995)
• M.Sc. & Ph.D., CS, Univ. of Illinois, Urbana-Champaign (1997 & 2000)
• Computer Engineering Group, ECE, Univ. of Toronto (2000 - present)
• IEEE Fellow (2015)
• Fellow, Canadian Academy of Engineering (2023)
• Fellow, Engineering Institute of Canada (2024)

My research

• Research interests
  • Cloud computing, distributed machine learning
  • Computer networking
  • Security & privacy
• Vision
  • Bridge the gap between theory and practice
• Small research team
  • alumni \(\rightarrow\) academia: 22
• Website: iqua.ece.toronto.edu

Overarching course objective

To develop a practical and in-depth understanding on best practices of building modern software systems with Rust

Why Rust?

• Reliable
  • Memory safe
  • Thread safe \(-\) no race conditions
  • Static types
  • Runtime errors \(\rightarrow\) compile-time errors

Why Rust?

• Highly performant
  • Full control over low-level details
  • No garbage collectors
  • Minimized memory footprint
  • Threads and stackless coroutines

Why Rust?

• Excellent ecosystem and tooling
  • Surprisingly useful compile-time error messages
  • The cargo package manager & crates.io
  • Documentation & docs.rs

What do we cover (tentative)

• Basic Programming Concepts and Ownership
• Structs and Enums
• Options and Error Handling
• Strings, Vectors, Hash maps, and Slices
• Generic types, Traits, and Lifetimes
• Functional Rust with closures and iterators
• Smart Pointers to Data on the Heap
• Fearless Concurrency
• Best Practices, Design Patterns, and Idiomatic Rust

Rust is a language for the next 40 years

• High and low level
• Code for web assembly, containers, or bare metal chips
• Fast, reliable, productive — pick three
• Fearless concurrency

The last 40 years were written in C, the next 40 will be written in rust.

As a recent example, OpenAI’s Codex CLI was previously implemented in TypeScript, and re-implemented in Rust two months ago. After its release on August 8, 2025, its performance is much better.

A note about AI

• AI has been widely known to be effective as a coding assistant
  • At Anthropic, 80% of the code is written by AI
  • At Ampcode.com, 95% of the code is written by AI
• But what about the cream — 5-20% — at the top?
  • Humans are still essential, at least today
  • But without knowing the language at the finest detail, you cannot write that last 5%!

In this course, we want to talk about making not just any software, but perfect, highly performant software, that AI cannot make (yet).

Textbook

The Rust Programming Language

Course Website

https://www.eecg.toronto.edu/~bli/ece1724

• At a glance
• Syllabus
• Lecture slides and video recordings

Announcements and grades will be posted to q.utoronto.ca

Office Hours

Mondays, 1-2 p.m., BA 4118

or by appointment

Assignments

1. Reversi board game
2. Search utility
3. Web client
4. Web server

• Do not use AI except code completion

Course Project

• Objective: Building a performant software framework
• Done in teams of 2-3 students
• Third-party frameworks from crates.io can be used
• Some inspiring project ideas will be announced for teams to choose from
• Teams can, of course, start with their own project ideas
• Do not use AI to write new code; you can use AI to locate bugs, as long as you include prompts (e.g. CLAUDE.md) and conversation histories in your GitHub repo

Academic Integrity

• Do not copy from other students or provide your code to others
• Trivial to detect