Important #1: Click to sign up for this class on Piazza!
Important #2: Click to register with Gradiance with class token 79BCDDD4.
Important #3: Click to register with Gradescope with entry code 4PVY8R.
Important #4: Click to access the interactive spreadsheet to answer questions during lecture!

What do we teach?

  • Machine learning and scientific computing need a lot of cycles; machines such as GPUs are complex to code. How do we automatically generate efficient code for these machines effectively. (Parallelism and Locality)
  • The highest programming language is obviously natural language. Can we program our virtual assistant to perform compound tasks in natural language? We use machine learning techniques to map natural language into formal languages. Note: no prior knowledge in machine learning is needed. (Neural networks, Satisfiability Modulo Theories)
  • Can we use program analysis to automatically detect security bugs in programs? (Pointer analysis)
  • How do we automatically manage memory efficiently so users do not have to manage it themselves? (Garbage collection)
  • How do we make high-level programming languages efficient by optimizing the code? (Data-flow analysis)

How do you learn this?

This is a course where math and programming meet. Learning compiler techniques has much in common with learning mathematical proofs. You learn by trying, finding your own insights. This means the assignments can take a variable amount of time! We want you to formulate your own variations of problems and solve them.

How is the course structured?

  • Highly interactive lectures, textbook reading.
  • Programming assignments analyze Java code.
  • Problem sessions for discussion.
  • Piazza for offline questions.
  • 2 Exams.

Logistics When, where, what and how

Lectures Monday and Wednesday 4:00 pm - 5:20pm
Review Session Friday 4:00pm - 5:20pm
Prerequisites CS 103 or CS 103B, and CS 107; Java programming language experience
Textbook Compilers: Principles, Techniques, & Tools (Second Edition), Alfred V. Aho, Monica S. Lam, Ravi Sethi, Jeffrey D. Ullman, Addison-Wesley, 2007.
Class Q&A Website CS243 on Piazza - for all questions related to the material.
Interactive Spreadsheet Link
Videos of Lectures CS 243 Canvas Page
Staff Mailing List
Office Hours Sign-up QueueStatus 1321
SCPD Office Hours Sign-up on QueueStatus, write SCPD in name
Exam 1 February 17
Exam 2 March 17

Where do I ask questions?

All questions related to the material should go to Piazza. Using Piazza for questions should significantly decrease the average response time, since there are more instructor/TAs and students there to see the question. If another student can answer the question, that will help them learn, too.

Administrative questions should all go to Please do not email individual staff members.

Grading Policy

Assignments 55%
Exam 1 20%
Exam 2 25%
Extra Credit: Class participation: up to 3%
Extra Credit: Lab: up to 3%

Staff Professor and TA details

Monica Lam, Instructor

Office Hours Mondays and Wednesdays:
after class
Contact Details

Andrea Brand-Sanchez, Admin

Phone (650) 723-1658

How are office hours structured?

The TAs each hold office hours twice a week over Zoom. The instructor holds office hours by arrangement via email.

Nikhil Athreya, TA

Office Hours Mon/Tue 12PM - 2PM
Zoom link
Contact Details

Zhouheng Sun, TA

Office Hours Wed/Thu 12PM - 2PM
Zoom link
Contact Details

Tentative Schedule Subject to change

Date Topic Reading Lecture notes Assignment out Assignment due
Jan 11 [Mon]Introduction1.1-5, 8.4, 8.5, 9.1Lecture 1 HandoutFill in your student profiles and screen names here.Jan 13
Jan 13 [Wed]Dataflow Analysis Introduction9.2Lecture 2 HandoutReview Session
Jan 18 [Mon]holiday
Jan 20 [Wed]Dataflow Analysis Foundation9.3Lecture 3 HandoutHW1, Solution, JoeQ slidesJan 27
Jan 25 [Mon]Constant Propagation, Loops9.4, 9.6Lecture 4 Handout.
Jan 27 [Wed]Partial Redundancy Elimination9.5Lecture 5 HandoutHW2,
Review Session: Slides, Handout
Feb 3
Feb 1 [Mon]Register Allocation8.8Lecture 6 Handout
Feb 3 [Wed]Instruction Scheduling10.1-10.4Lecture 7 HandoutHW3, Solution
Review Session: Handout, Writeup
Feb 10
Feb 8 [Mon]Software Pipelining10.5Lecture 8 Handout
Feb 10 [Wed]Parallelization11.1-11.4, 11.6Lecture 9 HandoutHW4,
Review Session: Handout
Feb 24
Feb 15 [Mon]holiday
Feb 17 [Wed]First Examination
Feb 22 [Mon]Loop Transformations11.7-11.9Lecture 10 Handout
Feb 24 [Wed]Pipelined Parallelism11.8, 11.9Lecture 11 HandoutHW5,, Solution
Review Session: Handout , Writeup
Mar 3
Mar 1 [Mon]Pointer Analysis12Lecture 12 Handout
Mar 3 [Wed]BDDs in Pointer Analysis12Lecture 13 HandoutHW6, Solution
Review session: Handout
Mar 10
Mar 10 [Mon]Garbage Collection7.4 - 7.7.4Lecture 14 Handout
Mar 8 [Wed]Satisfiability Modulo Theories (SMT)Lecture 15 HandoutHW7
Review session: Handout
Mar 19
Mar 15 [Mon]Natural Language ProgrammingLecture 16 Handout
Mar 17 [Wed]Second Examination

Handouts and Graded Assignments

CS243 will be using the Gradiance automated homework system for some of the required work. You should open your free account at and then sign up for the class using the "class token" 79BCDDD4.

Gradiance looks like multiple-choice questions, but it is really quite different. You are given problems to work out, just as you would in an ordinary homework. You are then given a multiple-choice question to test whether or not you have the correct solution. If you get a choice wrong, you are given a hint and encouraged to try again. You are allowed to try as many times as you like, and the goal is to get everything right eventually. To avoid repeated guessing on one problem at a time, you need to repeat all the questions each time you submit, and you will be given a different set of choices each time.

SCPD students: Please submit written assignments to us through the CS 243 Gradescope. Lecture notes will be available for download by the morning of the lecture.

Assignment Policy

Group Work

Homework will consist of both written and programming assignments. You are encouraged to work on the programming assignments in groups of two, but you must do the written assignments by yourself.

Late Policy

In general, no late assignments are accepted. However, you have two grace days for the entire quarter. That means you can be late by one day for two assignments, or use the two days up for one assignment.


Programming assignments will have specific submission instructions included with the handouts. We will use a certain amount of automatic grading to help us deal with the massive amounts of code everyone submits, so please follow the submission instructions exactly as written!

Some of the written homework should be submitted via Gradiance, as described above. If you have any issues accessing the Gradiance site, please contact the TAs.

Where are the assignments?

All assignments are posted on the schedule

Honor Code Cheating and Plagiarism is a no-no

You are free to discuss the assignment and solutions with others. However, you must write your own assignment, and must not represent any portion of others' work as your own. Anybody violating the honor code will be referred to the Judical-Affairs Office. If convicted, the normal penalty is a quarter suspension or worse.

The full honor code can be found here

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