CS 31: Algorithms, Spring 2020 (The Online Edition)

Background Assumed:
Students should have basic knowledge about programming and should be able to read and write math proofs. If you have taken CS 1, CS 10, and CS 30, you should be fine. In case you haven't, then please see the instructor. See this for what I teach in CS30.

• Drills. For almost every lecture note, I will have a corresponding drill. These are supposed to be "simple" questions which check if you are following the material you are consuming.
• Coding Assignments. Every week, I will post a coding assignment which will mostly involve you implementing one or two of the algorithms we learn in the course. This will allow you to move from the abstract to the concrete.
• Problem Set. Every week, you will be given two problems to do. Almost always, these will have subproblems. Doing these problems is where the *real* learning will take place.

• Deeparnab Chakrabarty (Instructor)
• Maryam Negahbani (Head TA)
• Anup Joshi (TA)
• Themis Haris (TA)
• Sarah Hong (TA)
• Runze Liu (TA)
• Alex Quill (TA)
• Linda Xiao (TA)

Text Books
There is no required textbook. However, the material is mostly going to be from the following two books, and I will give pointers to them as well if needed.

• (DPV) Algorithms by Dasgupta, Papadimitriou, Vazirani
• (CLRS) Introduction to Algorithms by Cormen, Leiserson, Rivest, Stein

Grading
As you all know, this term every student will be getting a (CT/NC) grade. Below is the distribution of points.

• Drills: 15%
• Coding Assignments: 25%
• Weekly Problem Sets : 30%
• Take Home Test 1 : 15%
• Take Home Test 2 : 15%

Evaluation Policies : Details

• Lateness Policy. You are not allowed to be late. All timestamps will be based on what Canvas says. However, for coding assignments and weekly psets, you will be given a bonus +1 point if you are more than 24 hours early. We are aware that sometimes stuff comes in the way, especially during these uncertain times, and that is why we will have *slack* for drills, coding assignments, and weekly psets.
  
  
• Slack. There is 15% slack on all deliverables. What this means is that at the end of the course, whatever percentage you obtain in each of these sections, will be multiplied by 100/85, capping at 100%. So, if you get 90% on the Drills, 85% on the Coding assignmnets, and 80% on the Psets, your final score will be 100% on the drills, 100% on the Coding assignments, and 94.12% on the Psets. Apart from releasing some stress, this slack also takes care of discrepancies in grading by various TAs.
  
  
• Tests. There will be two tests. Ideally, these would be in-class, closed-book, 3 hour tests. But this time, I will make them 24-36 hours long, open-notes (but no web), no-discussion, test. The extended time does not mean it is going to need this much time; indeed, the test should be do-able under 3-4 hours.
  
  
• Focus on learning and fun. I hope that all of you will make the best of this situation and actually learn this beautiful subject. Please have fun. Algorithms are indeed difficult to master, and the barrage of problems that I provide from my end (although only a few are for credit) may feel stressful. Please don't be stressed. Algorithms, it is good to remember, are not the most important thing in life.

Regrading Policy

If you feel a grader has not graded accurately, then please contact them via email cc-ing the head TA (Maryam). If even after this you feel unsatisfied, then you can email the instructor for a full regrade . I will look at the entire problem set and re-grade it completely. Note: this has to be done within 2 weeks of you being handed the solution. Also, remember, the slack available though before you exercise regrading.

Zoom Etiquette

I am sure we will all learn various etiquettes on the fly (and I will keep posting them). But a few standard things.

• Please try to be completely engaged when attending a Zoom lecture or Zoom office hours.
• Please keep your microphone and camera "muted" when not using. I know this tends to decrease engagement, but overall may be a better idea.
• Please be polite and kind to everyone. I am sure we will all make mistakes, and grace is something all of us will need.

Academic Integrity / Honor Code

Algorithms are tough, but fun. And it is even more fun when one works with a friend. I highly recommend forming study groups and watch the videos together, go over notes together, pore over practice problem + solutions together. And bang heads on the weekly problem set together. This is not only allowed, I highly encourage it. However, the final solution you write, must be your own.

For coding assignments and drills, I recommend working on your own. This will make you understand the concepts better, and make you all better coders. Only if stuck, contact the teaching personnel or your friend. For instance, if your code is not working, this is the perfect thing to share your screen with a TA and ask them what's wrong. Or asking your friend, "Hey, how does one convert a string to an integer in Python?" Perfectly OK. But there is a line here which you must make sure you don't cross.

This is important : For all your submissions, you must provide a credit statment even if you have worked alone (in which case, state "Worked alone"). Please write the names of all you have worked with. If this set is empty say so. Not writing a credit statement can give you a zero . I know many solutions are written at the last minute; spend the first 10 seconds of that minute to cite people who help you. Good habit.

Finally, some possible honor principle violations to be aware of in this online course offering.

• Sharing the same overleaf, github, replit, etc website for sharing any part of the (drill, coding, weekly pset) assignments. You simply cannot share this.
• Obtaining answers on the Web, and then simply copy-and-pasting. Especially pertains to coding assignments.