Introduction

COS 265 - Data Structures & Algorithms

Who are we?

Professor

• Dr. Jonathan Denning
• Ph.D. from Dartmouth College
  • Computer Science
  • focus: Computer Graphics
• Data Structures & Algorithms are integral to CG

Lab TAs

• 10–12: Zane Merrifield
• 12–14: Jack Rainey
• 14–16: Kaleb Hiehle

Who are we?

Students

• name

• one thing that stands out in your TU experience so far

• one thing you would like to take away from this course

• what does faith-learning integration look like for a class like this?

• favorite computer animated film

Disclaimer

This course is based on the COS 226 Princeton course, for which the course book was written.

Introduction

Overview

Overview

This course continues on where COS 121 left off.

You have learned the fundamentals of coding.

Now we will go deeper...

“

This is your last chance. After this, there is no turning back. You take the blue pill—the story ends, you wake up in your bed and believe whatever you want to believe. You take the red pill—you stay in Wonderland and I show you how deep the rabbit-hole goes.
–Morpheus

”

Since you're in this course, you're taking the red pill 💊︎

Let's learn some (programming) kung-fu!

Objectives

Through this course, we will learn:

• the Java programming language
• to use the IntelliJ IDE
• how to design algorithms to solve problems
• how to analyze and compare algorithms
• properties of different abstract data types and implementations
• how to use basic features of a version control system
• critical thinking skills
• reviewing techniques

outcomes

We will continue reinforcing two outcomes that were introduced in COS 120 and reinforced in COS 121.

You will not simply learn about algorithms, but become a computer scientist who can look at a new problem, determine what matters, and thoughtfully design an effective solution.

outcomes

We will continue reinforcing two outcomes that were introduced in COS 120 and reinforced in COS 121.

• break complex problems into manageable parts
• recognize patterns and appropriate computational strategies
• evaluate solutions for correctness and efficiency

outcomes

We will continue reinforcing two outcomes that were introduced in COS 120 and reinforced in COS 121.

• design, implement, test, and refine solutions to problems
• understand how algorithms work and build them yourself
• make deliberate and informed choices about inherit tradeoffs

key idea of course

Data Structures and Algorithms are related parts, facets of computation, that are foundational to computer science.

Data Structure

organization of info with rules for storing, retrieving, and editing

Algorithm

step-by-step method for solving a problem

A computer scientist has a strong understanding of both of these.

key idea of course

During your career, you will see a problem solved with many different algorithm and data structure implementations.

Most will be bad; some will be OK; only a few will be good.

Especially now in the age of vibe coding...

My goal is to equip you with the skills necessary to see and understand the differences.

“

I will, in fact, claim that the difference between a bad programmer and a good one is whether they considers their code or their data structures more important. Bad programmers worry about the code. Good programmers worry about data structures and their relationships / algorithms.
–Linus Torvalds (creator of Linux)

”

“

For me, great algorithms are the poetry of computation. Just like verse, they can be terse, allusive, dense, and even mysterious. But once unlocked, they cast a brilliant new light on some aspect of computing.
–Francis Sullivan

”

Introduction

expectations

expectations

This is the third course in the Computer Science degree.

All of you are at least sophomores.

Therefore, you should know...

• how to write correct code that compiles and runs,
• how to properly comment your code,
• how to manage your time and turn in work before the deadline,
• how to keep up with book readings,
• that you can talk to me or a TA about any of the problems any time, but we will not do your work.

resources

You will need to refer to these resources frequently

Required Book

• Algorithms 4th edition, required book, Amazon
• Book website
• Assigned readings every week or two

Electronic Resources

• IntelliJ: integrated development environment
• GitLab: source code management and distribution, task tracking
• Slack: real-time online communications
• Plickers: attendance and comprehension
• Brightspace: course materials and gradebook

time

For any undergraduate course, you should expect to spend 2–3hrs outside class each week for each credit hour you are taking.

COS265 is 4hrs and will likely be at the upper end of that range.

electronics use

Mounting research indicates that electronics usage in classroom harms student's ability to retain and process information.

For example, although students that take notes using laptops tended to record more details, follow-up tests show that they processed and retained much less than those who took notes on paper.

Therefore, I have adopted a no-electronics-use policy.

During lecture time, you are not allowed to use a computer, even for taking notes.

Exception may be granted to those who write a 1-page argument.

See Electronics Usage Policy and Syllabus for more details.

mastery

Your goal should be to understand data structures and algorithms well enough that you can explain it clearly to me without any aid.

• Submit only code that you wrote and fully understand.
• Limit collaboration to what is defined on each assignment.
• Talk with me or the TAs.
• Read the book.
• Curate your own curiosity.

ai

AI can seem like an ally or someone who speaks with authority.

For this class, when it comes to AI, ...

I encourage you to use AI in the following ways.

• deepen your understanding of the concepts
• build connections between topics
• generate practice problems, especially studying for exams

ai

AI can seem like an ally or someone who speaks with authority...

For this class, when it comes to AI, ...

Do NOT use AI for anything related to the projects or labs.

• understanding the problem
• solving the problem
• writing the code
• debugging
• analyzing and reviewing
• etc.

“

What are you trying to tell me? That I can dodge bullets?
–Neo

”

“

No, Neo. I'm trying to tell you that when you're ready, you won't have to.
–Morpheus🕶

”

You should be able to do all the following completely on your own:

• implement a solution to computational problem
• explain and reproduce anything you submit
• analyze code for performance, memory use, edge cases, etc.
• explain tradeoffs among different solutions

disclosure

Regardless, ALWAYS disclose any outside help or collaboration, whether AI or peer.

• Disclosing help will affect your grade if not allowed
• Not disclosing help, allowed or not, is academically dishonest

Introduction

assessments

assessments

This course has several required deliverables

• Projects: about 7, related to lecture content
• Labs: coding reviews, critical thinking, exercises
• Examinations: mid-term and final
• Participation: reading, attendance, quizzes

Be mindful of the due dates and times.

They are linked in Schedule and Brightspace.

You are responsible for turning in your own work on time.

projects

Generally, I post the projects while we are still covering the needed materials.

I do this so that you can

• read the project description,
• read the project source,
• gain context for what we talk about,
• have time to digest and attempt solutions,
• be able to ask questions that are still in context.

Projects are due Tuesday at 11:59pm

• 2 weeks (~2 weekends and 2+ labs)
• small window of grace with hard cut-off
• push to gitlab; do not email/slack us your project
• expect about 12–20hrs of work for each project

projects

Projects have implementation and documentation requirements.

projects: implementation

The implementation portion of projects will be graded by running your code against unit tests. A unit test is a pass/fail (binary) test.

Each gradeable item will have a set of unit tests, and the grade you receive is based on which of the tests passed.

Tests will run just after 6pm and midnight every day.

The tester will post the results as comments to the issues and update the labels to indicate score.

It is in your interest to start work early, to submit frequently, and to test as often as you can!

projects: implementation

You will receive full credit for your implementation only if it meets all requirements completely.

projects: implementation

The project write up will describe which packages you may import and what parts you may modify (typically the body of several functions)

In general, you are not allowed to modify the function's signature, such as return value, function name, argument types or ordering, which Exceptions are thrown, etc.

projects: documentation

Each project will require you to document and analyze your work.

This work is done in the readme.md Markdown file.

projects: notes

A few additional important notes about projects...

labs

Labs are primarily used to...

• discuss assignments and course material
• explore the Java programming language
• improve general programming skills
• work on projects
• cover material in more depth

We will occassionally have a lab exercise, perform a code review, or work on critical thinking, each of which are designed to be done during lab (maybe a couple hours outside).

labs: lab exercises

Lab Exercises will give you a chance to...

• explore coding
• work on something much smaller and perhaps sillier
• earn some extra credit

labs: coding reviews

Code Reviews will give you a chance to...

• read other student's code
• analyze different implementations
• discuss great solutions and areas of improvement

labs: critical thinking

Critical Thinking assignments will give you a chance to apply critical thinking skills to...

• computer science,
• life at Taylor, and
• life in general.

Below are the five skills on which we will focus

• Asking good questions
• Consulting an expert
• Edge cases
• Similar problems/fewer variables
• Developing subgoals

examinations

We will have two exams.

Both are:

• in person
• without resources (books, notes, internet, etc.)

examinations: oral exam

The first exam is an Oral Exam just after midterm.

It is structured to simulate a technical interview.

• step through or analyze a snippet of code
• explain how a certain data structure works
• provide details on an algorithm
• contrast two data structures or algorithms
• etc.

Covers only first half of material.

This exam should take no more than 30 minutes.

examinations: final exam

The second exam is a Final Exam taken during finals week.

It is structured similar to a standardized test like the GRE or ETS.

• content similar to oral exam
• variety of problem types (multiple choice, T or F, short answer, etc.)

Covers whole semester of material.

This exam should take no more than 2 hours.

examinations: notes

The lowest exam grade will be dropped.

participation

Participation will be recorded through a variety of ways.

• interactive sessions
• office hours and Slack
• pop quizzes using Plickers cards

participation: interactive sessions

The interactive sessions will provide you hands-on experience with the material.

We plan to hold a session about every 2 or 3 weeks.

You each will get a deck of cards. Bring these cards with you to all lectures and labs.

participation: office hours and slack

Coming to office hours is a great way to get one-on-one help!

We will keep track of who comes in.

Slack is an online communication and collaboration environment that we will use for updates, questions, and answers.

You get participation points for asking and answering questions.

participation: pop quizzes

Plickers is a quiz / survey tool that uses cards (paper clickers)

I have a Plicker card for you, where on the back is written your name, the name of this course, and four letters (A,B,C,D).

Bring this to every lecture and lab. If you lose it, let me know, and I will print another for you.

During each participation assessment, orient your card so that

• I can see the "QR" code
• The letter of choice is in the top position.

participation: pop quizzes

As a backup, you may use the Mobile Plickers Card.

Let's set that up now...

course: COS265 number: see card tap save tap letter show code tap code add to home (opt)

grading

I use a 3pt grading system for COS 265 (and other courses)

Each gradeable item is scored 0–3 (or a scaled version). Assignments will have many gradeable items.

Submitting nothing is clearly a 0. But also code that doesn't compile or doesn't run will likely result in a 0.

Code that runs but produces incorrect or unexpected output will likely get a 1.

See my grading philosophy for break-down

final grades

Final grades are weighted average of assessment category scores (table below), but with one exception...

This means earning a passing grade requires passing every part of the course; cannot make up low scores in one category with high scores (including extra credit) in another.

Introduction

final details

slides

The slides are provided in interactive format using HTML

They have been tested to run and look OK in Google Chrome and mostly OK in Firefox

There may be bugs. Let me know, and I will fix them.

accessibility

I am working on improving accessibility of materials.

Please let me know how I can improve it for you.

I plan to record all lectures.

• auto-transcribed (thanks Google)
• links will be added to schedule and Brightspace

Assignment write ups have built-in accessibility features.

• links are collected and added to appendix
• bottom-right corner is dyslexic button that swaps font and increases font size

help!

At the end of the term, you will fill out an evaluation.

Please be critical, letting me know what worked and what did not.

Read the assigned book readings, so I can know if they were helpful.

first project

The first project, P00_JavaIntro, is designed to introduce you to:

• Java programming language,
• IntelliJ IDE,
• CSE GitLab
• general structure of future programming assignments
  • assignment file structure
  • modifying readme.md