Syllabus - Computer Science 314 - Data Structures (Computer Programming 2)
The University of Texas at Austin · Spring 2024

Please note, situations not covered explicitly by this syllabus shall be arbitrated by the instructor.


Table of Contents:

  1. Course Content

  2. Meeting Times and Lab Hours

  3. Materials, Resources, and Logistics

  4. Grading Policy

  5. Important Registrar Dates

  6. Getting Help

  7. Academic Honesty and Code of Conduct

  8. Religious Holidays

  9. Students with Disabilities Information


Course web page: www.cs.utexas.edu/~scottm/cs314

Course Objectives:  This is a second course in computer programming. The purpose of the course is to learn how to use and implement canonical data structures in medium sized programs. The data structures covered include lists, iterators, stacks, queues, priority queues, trees, binary search trees, balanced binary search trees, sets, maps, hash tables, heaps, tries, and graphs. The course also covers testing, reasoning about programs (pre/post conditions, assertions), debugging, abstraction of data, basic algorithm analysis/ rough estimate of  number of executable computations, recursion, canonical sorting and searching algorithms, an introduction to the object oriented concepts of encapsulation, inheritance, and polymorphism, dynamic programming, and functional programming in Java. Students will be able to implement medium sized programs using the concepts listed. The course is taught using Java. This page contains a detailed list of the course content.

Quantitative Reasoning Flag: This course carries the Quantitative Reasoning flag. Quantitative Reasoning courses are designed to equip you with skills that are necessary for understanding the types of quantitative arguments you will regularly encounter in your adult and professional life. You should therefore expect a substantial portion of your grade to come from your use of quantitative skills to analyze real-world problems.

We have high expectations, but you can succeed in the course. Based on the historical GPA and drop rate, about 20% of the students who attempt this course do not complete it. Succeeding takes a lot of hard work. Here are some tips for success in the course.

Formal Course Prerequisite: CS312 (or credit for CS312) with a grade of C- or higher

Informal Course Prerequisites: Mastery of the following basic programming topics: data types, variables, expressions and operators, control structures (looping and decision making), procedures( a.k.a. functions, methods, or subroutines), parameters, arrays (1d and 2d), simple user defined data types (records, structures, objects), top down design.

You should be able to design and implement a program in Java based on a problem statement. The problem should be complex enough that a well designed solution requires the following:

  1. 200 - 300 lines of code
  2. roughly 8 procedures / functions / methods
  3. uses arrays or lists of objects

For example, create from scratch a program that allows two people to play a game of connect 4 on the computer. The display can be a simple text based interface. Both players share the same keyboard and take turns.

Startup: Most of the things you need to do to set up your infrastructure for the class are on the class startup page.


Class Meetings - (Building Information for UT Austin)

Lecture (Students may attend either of the 2 classroom lectures with Professor Scott regardless of which one they are registered for.):

Conduct for in person lectures:

Discussion Sections.

Students must attend the discussion section (held on Mondays) for which they are officially registered. Look at your class schedule on UT Direct (NOT Canvas) to verify your unique course number. Check your class schedule at the MyUT website: https://my.utexas.edu/

Discussion sections (colloquially known as just section) meet most Mondays during the semester. See the course schedule for the days sections meet. Sections are led by Teaching Assistants who have taken and excelled in this course. During section you will have the chance to work on small-ish programming  problems similar in nature to the types of questions that will appear on exams.

You must be present at the start of section when the problem is given to received credit. Section problems cannot be made up. Section problems with little or no effort shall receive little or no points. 

Supplemental Instruction and Collaborative Study Sessions

This course is supported by Collaborative Study (CoStudy) and Supplemental Instruction (SI) Sessions. CoStudy Sessions and SI sessions  are led by experienced and trained students who develop engaging, structured, small-group activities for you to work through. These sessions are held at a consistently scheduled time for you and your classmates to tackle difficult content and learn the best approaches to the course! More information on session times and how to access them will be available via the course discussion website, Ed Discussion. You’re welcome to attend sessions at any point in the semester.

Teaching Staff:

Recommended Materials:

1. Recommended data structures book: Building Java Programs: A Back to Basics Approach (5th Edition), Publication Date: March 28, 2019 | ISBN-13: 978-0135471944 | Pearson Education / Addison  Wesley. (Previous versions of the book are acceptable, but there may be differences in section numbers for assigned reading and problem numbers for suggested exercises.)  Textbook homepage is www.buildingjavaprograms.com
 

2. Recommended  recursion book: Thinking Recursively with Java by Eric Roberts, ISBN: 978-0471701460

Class Discussion Tool: We have a discussion group for the class on Ed Discussion. Access Ed Discussion via Canvas.

We use Canvas to:

Email: All students must become familiar with the University's official e-mail student notification policy. It is your responsibility to keep the University informed as to changes in your e-mail address. You are expected to check e-mail on a frequent and regular basis in order to stay current with University-related communications, recognizing that certain communications may be time-critical. It is recommended that e-mail be checked daily. The complete text of this policy and instructions for updating your e-mail address are available at this page which includes instructions on how to update the email address you have on record with UT.

You are responsible for checking your e-mail and the class discussion group on Ed Discussion regularly for class work and announcements.

Software: Required software for the course:

1. Java. Download the Java SE Development Kit. You can download Java 8 from Oracle or more recent versions from the OpenJDK project. In CS314 we shall limit ourselves to the features of Java version 8.0.

2. An IDE. (Interactive Development Environment. A program that helps you write programs.) I do not prescribe the IDE you must use in this course as you are simply turning in .java files that must compile on the CS department lab machines. Plus many IDEs have far more features than we will make use of in this course. Many past students prefer IntelliJ. I use Eclipse, but more due to inertia than anything else. Some students will tell you "real programmers only use a text editor and the command line!" I respectfully disagree. I think IDEs offer some very valuable tools beyond a basic text editor and the command line, although I do agree it is vital as a CS student to learn to interact with a computer system via the command line.

3. A zip tool. Assignments submissions shall be .zip files (archive files, a file with other files inside of it). Some IDEs include zip tools. I use 7Zip, but there are many, many options.

4. Zoom. (for some help hours and ) Provided by UT. See utexas.zoom.us.

5. CS department account and the ability to access it remotely. If you want to verify your program will compile on the CS department machines you must have the ability to connect to the CS department machines, transfer files from your system to a CS department machine, and then compile and run your program on a CS department machine.

One of the course TAs, Sam Laberge put together an extensive guide (pdf version, original web page here: www.cs.utexas.edu/~slaberge/docs/lab_machines/)  to using the CS Department Lab Machines remotely. (Meaning using your machine and an internet connection to log into a CS department machine and issue it commands.)

Accessing and running a program remotely requires the following:


Schedule: The schedule of lecture topics, reading assignments, and assignment due dates is available online, via the class web page.  The schedule page contains links to slides for the lectures, assignments, and readings. Complete the readings before class. The schedule is subject to change.

Sharing of Course Materials is Prohibited: No materials used in this class, including, but not limited to, lecture hand-outs, videos, assessments (quizzes, exams, papers, projects, homework assignments), in-class materials, review sheets, and additional problem sets, may be shared online or with anyone outside of the class unless you have my explicit, written permission. Unauthorized sharing of materials promotes cheating. It is a violation of the University’s Student Honor Code and an act of academic dishonesty. I am well aware of the web sites used for sharing materials, and any materials found online that are associated with you, or any suspected unauthorized sharing of materials, will be reported to Student Conduct and Academic Integrity in the Office of the Dean of Students. These reports can result in sanctions, including failure in the course.


Grading: The class components used to determine your final grade are:

Component Type Number Points Total Points
Background survey (extra credit) - Due 1/16 on Canvas 1 10 10
Syllabus and Course Mechanics Quiz - Due 1/18 on Canvas 1 10 10
Academic Integrity Quiz - Due 1/23 on Canvas. (Note any score that is no 100% shall be reduced to zero. The quiz is open note and you can retake as many times as you like.) 1 10 10
Programming assignments - see schedule or assignments page for due dates 11 20 each 220
Section Problems completed in discussion sections  - see schedule for due dates 8 4 each 32
Exam 1, Thursday, February 15 6:45 - 9 pm.
Location: UTC 2.112A
Topics 1 - 8
1 250 250
Exam 2, Thursday March 28, 6:45 - 9 pm.
Location: UTC 2.112A
Topics 1 - 19.

1 250 250
Exam 3, Friday, May 3, 3:30 - 5:30 pm. Location TBD.
All topics.
1 250 250
Instructor and TA End of Course Surveys (extra credit) Details on due dates last weeks of semester 1 10 10

Grade distributions. Based on the roughly 5000 students who have taken CS314 with me:

Guiding Principle - No whining: Feedback and concerns about the course are always welcome; legitimate grading errors that are identified in a timely fashion will certainly be corrected, but whining is counter-productive and will only irritate those who evaluate your work to determine grades. Realize if you ask for a regrade "because it can't hurt to ask" your score may actually go down if we find more errors and problems.


Important Dates for Changing Academic Status and Dropping the Course: Refer to the Registrar's academic calendar for the deadlines for changes in academic status. Highlights include:

See the College of Natural Science Guidelines and Procedures page for more information. (cns.utexas.edu/advising/guidelines-procedures)


Where to get Help when You’re Struggling, Having a Crisis or an Emergency

Please, when something bad happens, or when you’re feeling overwhelmed, get help. Don’t endure it on your own. Even talking through the situation often helps. Here are some options:


 University Code of Conduct:

The core values of the University of Texas at Austin are learning, discovery, freedom, leadership, individual opportunity, and responsibility. Each member of the University is expected to uphold these values through integrity, honesty, trust, fairness, and respect toward peers and community.

Academic Honesty: TL;DR (too long didn't read) If you copy code from the web, another student, or use a generative AI, that is cheating in my course. The teaching staff will catch you and you shall be written up for academic dishonesty with penalties up to and including an F in the course.

Taken from the CS department Code of Conduct.

"The University and the Department are committed to preserving the reputation of your degree. It means a lot to you. In order to guarantee that every degree means what it says it means, we must enforce a strict policy that guarantees that the work that you turn in is your own and that the grades you receive measure your personal achievements in your classes:

Every piece of work that you turn in with your name on it must be yours and yours alone unless explicitly allowed by an instructor in a particular class. Specifically, unless otherwise authorized by an instructor:

You are responsible for complying with this policy in two ways:

  1. You must not turn in work that is not yours, except as expressly permitted by the instructor of each course.
  2. You must not enable someone else to turn in work that is not theirs. Do not share your work with anyone else. Make sure that you adequately protect all your files. If you place your source code on a CS department machine ensure the permissions are set so that no one else can view it. Even after you have finished a class, do not share your work or published answers with the students who come after you. They need to do their work on their own. This means do not post your solution code to any public web site such as public repositories on GitHub. If you have a GitHub repositories with school work, make them private. Do not post your work to the web even after you have completed CS314.

The penalty for academic dishonesty will be a course grade of F and a referral of the case to the Dean of Students. Further penalties, including suspension or expulsion from the university may be imposed by that office.

One final word: This policy is not intended to discourage students from learning from each other, nor is it unmindful of the fact that most significant work in computer science and in the computing industry is done by teams of people working together. But, because of our need to assign individual grades, we are forced to impose an otherwise artificial requirement for individual work. In some classes, it is possible to allow and even encourage collaboration in ways that do not interfere with the instructor's ability to assign grades. In these cases, your instructor will make clear to you exactly what kinds of collaboration are allowed for that class."

For CS314 the policy on collaboration is modified as follows:

If you are repeating the course you may reuse code you completed on your own. You may NOT use code from a program you worked on as part of pair or code that was from a program involved in an academic dishonesty case. You must start from scratch on any and all programs that:

You are encouraged to study for tests together, to discuss at a very high level methods for solving the assignments, to help each other in using the software, and to discuss methods for debugging code.

You are committing academic dishonesty if you look at someone else code (current students, past students and code from the web) in electronic or printed form OR discuss the code in at such a detailed level that solutions turn out essentially the same. You are committing academic dishonesty if use a large language model (LLM) / generative AI such as chatGPT to generate your code. You shall not ask anyone to give you a copy of their code or, conversely, give your code to another student who asks you for it.

Similarly, you shall not discuss your algorithmic strategies at such a detailed level that you and your collaborators end up turning in essentially the same code. Discuss very high level approaches together, but do the coding on your own. Realize with complex problems, two programs that have produce the same results given the same input will vary significantly in approach and structure. You are making many, hundreds, of micro decisions as you design and implement your programs. It is extraordinarily unlikely two people working on the same complex problem will produce the same solution.

Likewise, your experimental results must be your own. You may not copy these from another student.

Examples of cheating are many and include using a large language model / generative AI such as chatGPT to produce your code for you, copying or referring to solutions from websites such as CourseHero, GitHub, and PasteBin, accessing another student's account, looking at someone else's solution code, copying or downloading someone else's solution code, referring to solutions from previous semesters, having another student walk you through the solution and how to code it, discussing the problem at such a detailed that you are essentially coding together, having another student perform significant debugging of your code, having another student write your code for you and / or allowing others to copy of access your solution code. . This means you shall not look on the internet for code to solve your problems. This list is not all inclusive.

Examples of allowable collaboration include discussions of general concepts and solution strategies and help with syntax errors.

The code you can reuse in this course are:

  1. Code you wrote in  a previous course, if you wrote the code yourself.
  2. Any code you develop with the instructor or TAs in class and during help hours.
  3. Code (with attribution) from the class slides and the class coding examples.
  4. You may post your test cases on the class discussion group, but you must implement your own tests. You may not share solution code or experiment code in any way.

You shall not make use of code you find from other sources including the world wide web or produce by LLM / generative AIs. Materials from the web should only be used for educational purposes. Thus, you can read about linked lists and look at examples of linked list code, but you must not copy any code from the web or be looking at any of this code from the web when writing anything you turn in.

You are also allowed to post short segments of code (2 lines or less) of code that are giving you syntax errors to the class discussion group in order to get help on fixing the syntax error.

If you have any doubts about what is allowed, ask your instructor.

Plagiarism detection software shall be used on assignments to find students who have copied code from one another, the web or used code generated by a LLM / chatbot. 

For more information on Scholastic Honesty and the UT Honor code see the University Policy on Scholastic Dishonesty


Religious Holidays: By UT Austin policy, you must notify "as far in advance of the absence as possible so that arrangements can be made."  Please email me at least fourteen (14) days prior to the date of observance of a religious holy day so I have time to set up accommodations. If you must miss a class, an examination, a work assignment, or a project in order to observe a religious holy day, you will be given an opportunity to complete the missed work within a reasonable time after the absence.


Disabilities and Access: If you are a student with a disability, or think you may have a disability, and need accommodations please contact Disabilities and Access (DAA). You may refer to DAA’s website for contact and more information: diversity.utexas.edu/disability/. If you are already registered with DAA, please deliver your Accommodation Letter to me as early as possible in the semester so we can discuss your approved accommodations.

Students with a documented disability may request appropriate academic accommodations from the Division of Diversity an Community Engagement, Disabilities and Access, diversity.utexas.edu/disability/about/
Please request a meeting as soon as possible to discuss any accommodations
• Please notify me as soon as possible if the materials being presented in class are not accessible


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