EBoard 32: Binary search trees, continued

Warning This class is being recorded (and transcribed) (assuming Teams succeeds).

Approximate overview

• Administrivia
• Questions
• Binary search trees
• Lab

Administrivia

• Please return cards, boards, and markers to the back of the room when you finish class today.
• New policy: Overspent tokens and missing labs/reflections cannot drop you below a B-.
• New policy: Up to six missing labs/reflections permitted.
• I was unsuccessful at getting grading done this weekend. I apologize. It’s high on my priority list.
• Starting Wednesday, we are doing a week of hash tables (yay!); start with a reading by Osera.

Upcoming Token activities

Academic

• Tuesday, 2023-11-14, Noon, Day PDR: CS Table: Cell Phone Addiction.
• Wednesday, 2023-11-15, 4pm, HSSC Kernel: Madison Van Oort ’08 speaks on Frictions in the Future of Work.
• Thursday, 2023-11-16, 11-noon, JRC 101: Convocation: Richard Robinson on Nanoparticles 101.
• Thursday, 2023-11-16, 4:15pm, HSSC Kernel: CS Poster Session.

Cultural

Peer

• Monday, 2023-11-13, 4-6pm, 3D Printing Workshop, Stew Makerspace
• Tuesday, 2023-11-4, 4-6pm, 3rd floor HSSC, somewhere: Wilson Catalyst
• Thursday, 2023-11-4, 7-9pm, 3rd floor HSSC, somewhere: Wilson Catalyst
• Saturday, 2023-11-18, 1pm, Osgood: Swimming vs Augustana.
• Language study! Talk to your colleague.

Wellness

• We need more of these!

Misc

• Monday, 2023-11-13, 4-5:30pm, HSSC N1112: Politics of AI Info Session.
• Subject yourself to a study of types.

Other good things (no tokens)

Upcoming work

• MP8 pre-assessment due Sunday
• PM’s reading on Hash tables due Tuesday night
• MP8 due Thursday.
• MP8 post-assessment due Friday
• MP9 assigned Friday (JSON)

Questions

Registration

Trees/BSTs

Administrative

When will we get MP1 redos back?

I’ll check with the graders.

Where are the LAs?

Coming soon. All take-home. All open-ended. All infinite (well, arbitrarily finite) redos.

MP8

Other

Binary Search Trees

Um, Aardvark, Penguin, Cat, Panda, Frog, Elk, Squid, Dog, Jellyfish

How do we remove things?

• Leaves: Easy. Just remove the link to the child.
• Interior nodes with only one child: Build the link over the node.
• Interior nodes with two children.
  • Rebuild the tree (expensive)
  • What’s more efficient (remaining \(O(height)\))?
  • Delete the rightmost thing in the left subtree (or the leftmost thing in the right subtree) and put its value in the current node.
  • Historically: “And rebalance, if we can do it efficiently” (301)

Lab

Same places, same partners.

“Wow, writing set recursively is much easier than writing it iteratively.”