CSC 301.01, Class 01: An introduction to the coure

Overview

• Preliminaries
  • Notes and news
  • Upcoming work
  • Extra credit
  • Questions
• Course goals
• Course format
• Approaching algorithms.
• Problem: Getting from here to there
• Problem: Optimal soldering plans
• Problem: Scheduling overlapping tasks

News / Etc.

• Welcome back! I look forward to having an excellent semester with you all.
• I will take quick attendance.
• I expect all of you to sign the department’s academic honesty policy. Please turn it in by Wednesday.
• As is typical for the start of the semester, the course Web site is in rougher shape than I would like. Expect it to take form over the next few weeks.
• I will be using the white board more than in other classes, particularly since I will be drawing data structures. Do you want to share daily note-taking responsibilities? We will revisit the question on Monday.
• Friday PSA.

Upcoming Work

• Read chapter 1 of Skiena by Monday.
• Homework 1, due Wednesday

Extra Credit

Academic

• CS Table, Tuesday, topic tbd.
• CS Extras, Thursday, Contracts.

Peer

Good things to do

• Ag days next Thursday.

Questions

How do we report on extra credits?

If you attend one, send me a short (one-to-two paragraph) email within two days of the event.

I prefer that you send me announcements in advance of class.

Course Goals

• Think of it as “207, enhanced/extended/made more challenging”
• Learn how to design and analyze algorithms and data structures.
  • Tools (methodologies for design, examples)
  • Verification techniques
  • Think about efficiency and how you analyze it carefully
• More of the core literature
  • You already know trees, merge sort, Quicksort, binary search map/reduce, priority queues, priority queues implemented as heaps,

Detour priority queues

Idea: Implement priority queues as lists that are sorted from highest priority to lowest.

• Add “Learn about heaps, priority 5”
• List with (heaps/5) at the front.
• Add “Study for the CSC 301 final, priority 1000”
• List of the form [(heaps/5),(301final/1000)]
• How much time does it take to put something in the right place in this list?
  • O(n^2)
  • O(nlogn)
  • O(n)
  • O(logn) (+1)
  • O(1)

Course Format

Often, Sam will pose problems and let you work on them and present them.

• Incredibly supportive random calling on people
• Small group work

Approaching Algorithms

You are now experienced computer science students. When some gives you a problem that admits an algorithmic solution, what do you do?

Think->Pair->Share

Approach one -> Getting from point A to point B

• There are places along the way from point A to point B, think about the places along the way and how you get from point A to the next point to the next …
• More generally, break the problem up into smaller problems.
• Once you have a solution, go back and see if you can make it better.
• Top-down decomposition

Approach two -> Just try something

• Kind of like freewriting in English. Get something out there.

Approach three -> Use the literature

• Identify similar problems that might give you insight on how to solve this problem.

Approach four -> Try examples

• Solve some examples of the problem by hand to gain insight.

Approach five -> Use a standard algorithm design strategy

• Divide and conquer
• Greed
• We wll learn others

Additional things to help any approach

• Make sure that you understand the problem
  • Formal specs
  • Unit tests
  • Talking to people
• Draw pictures
• Make sure that it’s correct
• Consider how efficient it is

Problem: Getting From Here to There

• Let’s pretend that net neturality is eliminated.
• We now have a problem: We need to get information from place to place, and we may want the least expensive path, or the quickest, or …

We start by modeling the the problem

• How do you represent/think about the input?
• This is probably a weighted graph problem.
• A graph is a collection of points (“nodes”, “vertices”) that have connections between them (“edges”).
• Weighted graphs include a value associated with each edge.
• Problem: Find the path (sequence of edges) from A to B with the least total cost.

Problem: Optimal Soldering Plans

Skipped

Stolen/modified from Skienna

• We have a bunch of points that we need to have a robot solder on a circuit board.
• We want the least wear and tear on the robot.
• How do we determine how to order the points?

Problem: Scheduling Overlapping Tasks

Skipped

Stolen/modified from Skienna

• You have a bunch of tasks, each of which has a start time and a length.
• You can only do one task at a time.
• How do you maximize the number of tasks you complete?

Extension

• What if each task also has a value? How do you maximize the value of the tasks you complete?