CS 106
Introduction to Computer Science 2

Lectures

CS 106 LEC 001: Mondays and Wednesdays, 10:00–11:20, MC 1085

CS 106 LEC 002: Mondays and Wednesdays, 2:30–3:50, QNC 1507

Labs

CS 106 LAB 101: Mondays and Wednesdays, 1:00–2:20, MC 3003

CS 106 LAB 102: Mondays and Wednesdays, 4:00–5:20, MC 3003

CS 106 LAB 103: Mondays and Wednesdays, 1:00–2:20, MC 3005

CS 106 LAB 105: Mondays and Wednesdays, 1:00–2:20, MC 3027

Students from LAB 104,106 should attend LAB 102 in MC3003

Midterm

Wednesday March 1st, 7:00–8:50, rooms TBA

Final Exam

TBA

For questions related to course content, contact an instructor or an ISA. The best place to ask questions is on Piazza, but you can also send email (add "@uwaterloo.ca" to the addresses below) or visit during office hours. For questions about marking, contact the Assistants first, who will consult with the Instructor if necessary. For questions about course logistics (particularly absences), contact the Coordinator.

The lecture schedule below is given in terms of Section 002 (the 2:30pm class). Section 001 (10:00am) will follow roughly one lecture period later. Both sections will have the same assignment and lab deadlines.

Week of	Lectures	Suggested readings
02 January	Module 00: Administration Module 01: Processing recap [notes]	CS 105 lecture notes
09 January	Module 02: Arrays and Strings [notes, sketches]	Learning Processing, Chapters 9 and 17; Online tutorial on arrays; Online tutorial on strings
16 January	Module 03: Input and Output [notes, sketches]	Learning Processing, Sections 15.1, 17.1, 17.2, 17.3, 18.3, 18.4, 21.3, 21.4
23 January	Module 04: Advanced Shapes [notes, sketches]	Learning Processing, Sections 14.3, 13.8, 13.9; online tutorial about the PVector class
30 January	Module 05: User Interfaces [notes, sketches]
06 February	Module 06: Geometric Context [notes, sketches]	Learning Processing, Sections 14.1, 14.5, 14.7, 14.8, 14.9 (ignoring 3D)
13 February	Module 07: Recursion [notes, sketches]	Learning Processing, Section 13.11 Nature of Code, Chapter 8
20 February	Reading week: no lectures
27 February	Module 08: Randomness [notes, sketches]	Learning Processing, Sections 13.3–13.6
06 March	Bonus: 3D [2016 notes, sketches] Module 09: Noise [notes, sketches]	Nature of Code Introduction, especially I.6, "Perlin Noise (A Smoother Approach)"
13 March	Module 10: Text processing [notes, sketches]	The first part of Shiffman's online notes about data Learning Processing, Sections 17.1, 17.2 and Chapter 18
20 March	Module 11: Tables [notes, sketches]
27 March	Module 12: Tree-structured data [notes, sketches]
03 April	Wrap-up [notes]

Participation	5%
Labs	5%
Assignments	30%
Midterm	20%
Final	40%

Please see the bottom of the course outline page for more information about re-marking of assignments and the midterm.

Before submitting code for assignments, you should familiarize yourself with the code style guidelines (as well as Processing's auto-format feature!) and read the instructions on how to submit code on LEARN.

• Assignment 00: Warmup (Due: Thursday, January 12th at 6:00pm)
• Assignment 01: Arrays and Strings (Due: Sunday, January 22nd at 11:59pm)
• Assignment 02: Input and Output (Due: Sunday, January 29th at 11:59pm)
• Assignment 03: Advanced Shapes (Due: Sunday, February 5th at 11:59pm)
• Assignment 04: User Interfaces (Due: Sunday, February 12th at 11:59pm)
• Assignment 05: Geometric Context (Due: Sunday, February 19th at 11:59pm)
• Assignment 06: Recursion and Randomness (Due: Sunday, March 12th at 11:59pm)
• Assignment 07: Noise (Due: Sunday, March 19th at 11:59pm)
• Assignment 08: Text Processing (Due: Sunday, March 26th at 11:59pm)
• Assignment 09: Tables (Due: Monday, April 3rd at 11:59pm)

• Lab 00: Orientation (Due: Monday, January 9th at 6:00pm)
• Lab 01: Arrays and Strings (Due: Wednesday, January 18th at 6:00pm)
• Lab 02: Input and Output (Due: Wednesday, January 25th at 6:00pm)
• Lab 03: Advanced Shapes (Due: Wednesday, February 1st at 6:00pm)
• Lab 04: User Interfaces (Due: Wednesday, February 8th at 6:00pm)
• Lab 05: Geometric Context (Due: Wednesday, February 15th at 6:00pm)
• Lab 06: Recursion and Randomness (Due: Wednesday, March 8th at 6:00pm)
• Lab 07: Noise (Due: Wednesday, March 15th at 6:00pm)
• Lab 08: Text Processing (Due: Wednesday, March 22nd at 6:00pm)
• Lab 09: Tables (Due: Wednesday, March 29th at 6:00pm)

Practice

• We have created a large set of practice programming exercises to help you build your skill at writing short functions. Some of these exercises may be included in labs during the term.

Processing

• This course is taught using the Processing programming environment. You can download a free copy of Processing for just about any computer. When working on assignments, the reference section will be especially useful.
• The required textbook for the course is Daniel Shiffman's Learning Processing, second edition. You should already have this book from CS 105. I will also make occasional references to Shiffman's other book, The Nature of Code, which is available for free online.
• If you need a gentler introduction to programming in Processing, you might want to look at Reas and Fry's Getting Started with Processing (second edition). Reas and Fry are the inventors of Processing. They also have a more comprehensive book called Processing: A Programming Handbook for Visual Designers and Artists (second edition), which goes deeper on programming and includes lots of inspiring art examples.
• Andrew Glassner runs an online course on learning Processing at his website The Imaginary Institute. He also has another good book on Processing, Processing for Visual Artists: How to Create Expressive Images and Interactive Art. The course isn't free, but he has published an excellent series of introductory tutorials on bits of mathematics that artist-programmers should know. Some of these might be useful refreshers on techniques we'll use in CS 106.

Course technology

• We use Piazza for questions, discussions, announcements, and other topics of interest to students in the course. Visit The course's Piazza page for timely updates on course material. Feel free to use Piazza to seek help with assignments from the course staff or each other, but keep academic integrity in mind. Don't post anything publicly that might constitute an academic offence (e.g., a partial solution to a programming question). If in doubt, you can always make your post private, so that other students can't see it.
• Non-public aspects of the course (such as assignment submission and marks) happen on LEARN. But for the most part, all other course-related documents will be posted publicly here.
• The course uses iClickers for in-class feedback and quizzes. The Faculty of Mathematics has a fairly extensive iClicker FAQ if you have any questions. You will need to register your clicker in order for your in-class responses to be recorded. You can also view your clicker marks online.

Other documentation

• There are a few general documents that will help you get through this course, which are identical to the ones we made available to you in CS 105. Make sure you've read the Survival Guide for starters. Then, before submitting code for assignments and labs, make sure you're up to speed on our suggested code style guidelines and that you know how to submit code on LEARN.

Academic Integrity

In order to maintain a culture of academic integrity, members of the University of Waterloo community are expected to promote honesty, trust, fairness, respect and responsibility. [Check www.uwaterloo.ca/academicintegrity/ for more information.]

Grievance

A student who believes that a decision affecting some aspect of his/her university life has been unfair or unreasonable may have grounds for initiating a grievance. Read Policy 70, Student Petitions and Grievances, Section 4, www.adm.uwaterloo.ca/infosec/Policies/policy70.htm. When in doubt please be certain to contact the department's administrative assistant who will provide further assistance.

Discipline

A student is expected to know what constitutes academic integrity [check www.uwaterloo.ca/academicintegrity/] to avoid committing an academic offence, and to take responsibility for his/her actions. A student who is unsure whether an action constitutes an offence, or who needs help in learning how to avoid offences (e.g., plagiarism, cheating) or about 'rules' for group work/collaboration should seek guidance from the course instructor, academic advisor, or the undergraduate Associate Dean. For information on categories of offences and types of penalties, students should refer to Policy 71, Student Discipline, www.adm.uwaterloo.ca/infosec/Policies/policy71.htm. For typical penalties check Guidelines for the Assessment of Penalties, www.adm.uwaterloo.ca/infosec/guidelines/penaltyguidelines.htm.

Appeals

A decision made or penalty imposed under Policy 70 (Student Petitions and Grievances) (other than a petition) or Policy 71 (Student Discipline) may be appealed if there is a ground. A student who believes he/she has a ground for an appeal should refer to Policy 72 (Student Appeals) www.adm.uwaterloo.ca/infosec/Policies/policy72.htm.

Students with Disabilities

AccessAbility Services (AAS), located in Needles Hall, Room 1132, collaborates with all academic departments to arrange appropriate accommodations for students with disabilities without compromising the academic integrity of the curriculum. If you require academic accommodations to lessen the impact of your disability, please register with AAS at the beginning of each academic term.

More Information

Academic Integrity and Students with Disabilities