Syllabus
Purpose and Objectives
This course teaches the design, implementation, analysis, and proper application of abstract data types, data structures, and their associated algorithms. We will explore a wide variety of data structures both conceptually and concretely via implementation. The class involves a significant hands-on programming component; you will both implement and use several data structures yourself. To summarize, in this course you will:
After this course you will know how to:
- Understand the basic data structures commonly used in computer science, such as arrays, linked lists, stacks, queues, trees, and graphs.
- Analyze the time and space complexity of different algorithms, and understand the trade-offs between different data structures and algorithms.
- Implement basic algorithms, such as sorting and searching.
- Understand the principles of algorithm design, including divide-and-conquer, dynamic programming, and greedy algorithms.
- Use data structures and algorithms to solve real-world problems in an efficient and effective manner.
This syllabus contains policies and expectations I have established for CS2126. Please read carefully the entire syllabus before continuing in this course. I intend for these policies and expectations to create a productive learning atmosphere for all students. Unless you are prepared to abide by these policies and expectations, you risk losing the opportunity to participate further in the course. Policies and expectations as set forth in this syllabus may be modified at any time by the course instructor. Notice of such changes will be made by announcement in class, by written or email notice, or by changes to this syllabus posted on the course website.
Contact
The best way to get in contact for personal, private (FERPA, etc) messages is via my email address hemannja@shu.edu. You should expect a response within 48 hours. If I deem it even potentially useful to others, I will likely anonymize your letter, answer it in an FAQ post to the class, and forward you the link.
A great regular way to reach out for help is via my office hours. Outside of my office hours, you should not expect to reach me by MS Teams chat. I rarely check it outside of those hours, and will likely not receive your message.
Additional Support
In addition to lecture, I provide the following additional resources for students to avail themselves. Do consider taking regular advantage of them.
Scheduled Office Hours
Course personnel will make ourselves available for 4-6 hours of office hours available weekly, concentrated toward assignment due dates. If our office hours schedule in particularly ill-suited to your class schedule, let me know and I may be able to adjust them.
Textbooks
- Cormen et al. “Introduction to Algorithms, Fourth Edition”. MIT Press (2022)
- Aditya Bhargava. “Grokking Algorithms: An Illustrated Guide for Programmers and Other Curious People”. Manning Publications (2016).
For the most part lectures are intended to be standalone, with the textbook as a supplement for students who want to reinforce their learning or go deeper into a topic. Some topics, however, will not be covered directly in lecture; you will therefore need to read the relevant textbook chapter to be able to understand what follows in class. The Cormen text is comprehensive, but not always easy to approach. Its emphasis is also more on the theoretical side of things than this class’s. Nonetheless, it is a useful book to have on hand for computer scientists, and will supplement our in-class activity. The “Grokking” text is intended to give you an easier segue into some of those topics.
Supplementary Videos
The great thing about learning elementary data structures and algorithms is that so many of these topics are covered so well in multiple mediums. I will link to a variety of supplementary videos about various CS2126-related topics. I recommend watching them early on; they offer valuable advice that can be quite helpful in understanding assignments.
Assessment
This class uses a form of Specifications Grading (Nilson 2015). In particular, it features mainly qualitative assessment, and does not rely on points, percentages, and weighted averages to determine final grades.
This is likely quite different from what you have seen in your other classes, and will take some getting used to on your part. This system, however, has a number of benefits for students—see [Why Spec](why-specs**.
Programming Assignments
This class features five programming homeworks and a final project that has a programming component, which chiefly contribute to our functional correctness learning objective. All programming assignments and related sub-assignments (see below) must be done individually; see our Academic Integrity policy later.
When evaluating your programming submissions, I will give you feedback regarding where they fell short as well as assign the following possible outcomes:
- Got it: your submission implements the specification correctly and in full.
- Almost there: your submission implements the specification with minor mistakes or omissions.
- On the way: your submission has elements of a correct solution, but requires non-trivial further work to be correct and/or complete.
- Not yet: your submission requires significant further work.
- Cannot assess: I could not evaluate your submission as is; repairs are required before I can do so.
Specifics of what is required to achieve each outcome are included in the handout for each assignment; our expectations are stated up front, no surprises.
Resubmissions
Making mistakes and correcting them is a natural part of the learning process. An outcome of On the way or Not yet is NOT a failure: it just means you still have things to learn from this assignment. Our assignments are intentionally challenging and our grading is intentionally strict in order to maximize your learning; it’s perfectly normal to not get them entirely correct on the first try.
To give you the opportunity to incorporate our feedback and get credit for your improved learning, I will allow you to resubmit the code portion of each homework one week after the initial deadline. See schedule at the end for exact dates. To determine final grades, I will use the best of the two outcomes your submissions have achieved.
Self-Evaluations
Each of the five programming homeworks will be followed by a self-evaluation, due one week after the initial deadline. Self-evaluations will consist of a few questions about the code you turned in. Specifically, the code you turned in for the first submission, not the resubmission, and not work in progress towards the resubmission. You can download your original submission from Canvas if you overwrote/misplaced it.
The purpose of these self-evaluations is to evaluate your submissions on non-functional correctness: desirable aspects of programs that go beyond strictly producing correct answers. Aspects like efficiency, testing, robustness, or factoring. In actual programming (i.e., not in classes), these are just as important (if not more so) than raw functional correctness. This class will give you opportunities to cultivate these skills and habits as you work on assignments.
Project Report
Instead of a self-evaluation, the final project will include a written report where you will explain your design and provide rationales for your decisions. More details are included in the final project handout.
The final project and its associated report contribute to our evaluation and integration learning objectives.
Worksheets
To evaluate specific aspects of our theory learning objective, we will have two worksheet-style assignments.
To ensure everyone has a solid theoretical foundation, these worksheets will be done as Canvas quizzes with unlimited retries; I encourage you to re-do them until you fully understand.
Exams
We will have two in-person, on-paper midterm exams which will chiefly assess our theory learning objective. No notes or electronics (laptops, calculators, tablets, phones, smart watches, etc.) will be allowed during exams. Specifics and logistical details will be announced leading to each exam.
Final Grades
Final letter grades will be determined as follows.
To help you keep track of your progress, please see the self-serve final grade worksheet on Blackboard.
Base Grade
Your base grade will be determined based on your performance on homeworks and the final project:
| A- | B | C+ | D | ||
|---|---|---|---|---|---|
| Excellent | Good | Satisfactory | Poor | ||
| Homeworks | Got it | all 5 | 3 | 2 | 1 |
| Almost there | – | 1 | 1 | 1 | |
| On the way | – | 1 | 1 | 1 | |
| Not Counted | – | – | 1 | 2 | |
| Final Project | Minimum outcome | Got it | Almost there | On the way | On the way |
For example, a student whose homework submissions earned 4 “Got it” but one “On the way” and whose project submissions earned an “Almost there” would earn a base grade of B.
Failing to meet the criteria for a D will result in a base grade of F.
Warning These criteria put a lot of importance on the final project, which is intentional. I find that the learning experiences from the project are especially valuable. This course therefore considers it very important, and I want you to do so as well.
Modifiers
This base grade will then get adjusted with modifiers based on your performance in other aspects of the class. Each of these can either increase your grade by a partial letter grade, leave your grade unchanged, or decrease your grade by a partial letter grade. There are a total of six possible modifiers:
EDIT 1/26/24. I edited this table to clarify
| +1 | +0 | -1 | |
| Worksheets | Both worksheet1 100% and Worksheet 2 100% | Worksheet1 >= 80% and worksheet2 >= 80% | Either worksheet < 80% |
| *Self evaluations | Score (out of 5) | +1 | +0 | -1 |
| Number of evals scoring 5s | >= 4 | – | – | |
| Number of evals scoring >= 3/5s | – | >= 3 | <= 2 | |
| Number of evals scoring <= 2/5s | <= 1 | <= 2 | >= 3 |
EDIT: 2/5/24 REMOVED BOTTOM LINE OF CHART BECAUSE IT WAS SUPERFLUOUS EDIT: 2/6/24 NOT SUPERFLUOUS, ACTUALLY FIRST COL 3RD ROW MATTERS
Here “Above expectations” means “a higher outcome than required for your base grade.”
Both worksheets are considered together to determine a single modifier; both must meet the expected level. Similarly, all five self-evaluations are considered together to determine the self-evaluation modifier. Each exam, however, has its own modifier.
EDIT 01-24-2024
To match the assignment I’ve handed out, I’ll do exam scores out of 20. Depending on the score you earn on an exam, its modifier will range from +1 (an increase of one partial letter grade) to -3 (a decrease of a full letter grade), with the plurality of scores leading to a neutral modifier (no change).
In addition to each exam providing its own modifier, if your performance improves significantly between the two exams, you will earn a positive +1 modifier. Here, “significantly” means the second exam is two modifier steps (or more) above the first one: e.g., going from a -1 to a +1, or from a -3 to a 0. That is to say, exam improvement only if Exam #2 modifier is >= Exam #1 modifier + 2.
| See caveat above | +1 | 0 | -1 | -2 | -3 |
|---|---|---|---|---|---|
| Exam #1 | 18-20/20 | 12-17/20 | 8-11/20 | 4-7/20 | 0-3/20 |
| Exam #2 | 18-20/20 | 12-17/20 | 8-11/20 | 4-7/20 | 0-3/20 |
Here is how the project grading works. See caveats below.
| +2 | +1 | 0 | -1 | |
|---|---|---|---|---|
| Project program | 2x Above expectations* |
Above expectations** |
Meets expectations |
|
| Project documents | Outstanding | Minor errors or omissions |
Major errors or omissions |
| Caveats | Description |
|---|---|
| * | Base grade requires On the way, earned Got it. |
| ** | Base grade requires On the way, earned Almost there. Or requires Almost there, earned Got it. |
For example, suppose our hypothetical student who earned a base grade of B got everything right on both worksheets (Increase), submitted self-evaluations that earned three 5/5s and two 2/5s (Unchanged), did poorly on Exam 1 (Decrease) but well on exam 2 (Unchanged), and wrote an excellent project report (Increase). This would work out to an increase of one partial letter grade, for a final grade of B+. Good job, hypothetical student!
EDIT 2/5/24 For a second example we consider another hypothetical student. This student received a two “Got it”s two “On the way”s and a “Not yet”. They scored a 3 on all of their self evals. They had a project score of “Almost there” and a positive modifier on their project. They also received positive modifiers on both worksheets, and their exams were a 13 on exam 1 and a 20 on exam 2. That’s some nice work on the exam, but unfortunately that’s still an B-.
Going up one partial letter grade means going forward one step in this sequence, and going down one letter grade means going backwards one step.
The letter grade sequence “saturates” on either end: applying four + modifiers to a base of B results in an A, and applying two - modifiers to a base of D results in an F.
EDIT: 2/5/24
However, an F will remain an F even in the presence of positive modifiers. Which is to say, you cannot modifier your way out of a natural F.
Late Policy
Unless otherwise indicated assignments are due by 09:59 p.m. on their due date. Dropboxes will close automatically, and late is late.
To accommodate everyday slippage and minor life hiccups, each student starts the class with three late tokens. To use it you will need to email me your late submission. Each of these late tokens can be exchanged for a two-day no questions asked extension to any (non-exam) assignment, including re submissions. Only one token can be used per submission; i.e., two days is the maximum extension possible. Late tokens will be used automatically when you submit late; you don’t need to reach out and ask for permission. This two-day extension will begin from the moment you turn something in late; that is to say, your extended due date will be 09:59 PM two calendar days after the original due date. I will be tracking these late tokens for the class.
In a student runs out of tokens, I’ll be in touch. Being occasionally late is perfectly fine. Being consistently late, on the other hand, may be a sign of deeper underlying issues: let’s talk so we can figure out the best way to help you.
Barring extreme circumstances, we will not grant further ad-hoc extensions or accommodations. If you do end up in a situation that would warrant additional flexibility, you must contact your dean of students and have them contact me. They will help you coordinate extensions and accommodations across all your classes, which will ensure you get the support you need across the board, not just in this class.
Caveats
Even this amount of flexibility and self-control over your grades has some limitations in penalties from small mistakes. It is your responsibility to make sure the work you submit is as close a reflection of your actual learning as possible, so I can get the best picture I can of where you’re at as a student. And in turn, so you can get as much recognition as possible for your learning. Concretely, this means:
-
For programming assignments, being thorough in your testing to avoid silly mistakes, and taking full advantage of our feedback when working on resubmissions.
-
For “one-shot” assessments like exams or self-evaluations, be very careful to read instructions completely and thoroughly, and ask for clarifications if need be. I can’t assess your learning if you answer the wrong question.
Academic Integrity
It’s OK to meet with colleagues, form study groups, discuss assignments with them, compare alternative approaches, go over examples from textbooks or other sources. But it is never OK to share code or homework solutions, or even to see each other’s code or solutions. What you turn in must be your own work. Copying (or even studying) code, solution sets, test cases, materials from other previous terms, etc., from anywhere (e.g., other people, web, GitHub) is strictly prohibited. In this context, cheating refers to copying or submitting as your own, with or without consent, someone else’s work as your own. Misrepresentation of someone else’s work as one’s own is a grave violation of academic ethics. This includes copying from someone else answers to questions during an examination as well as copying programs from internet sources. Plagiarism refers to using someone else’s work in your own and not properly crediting the authors of that work. This includes adapting someone else’s code to solve a problem or write a program. The only exception to this rule applies to course resources from the current semester such as starter code, code from lectures, resource videos, or test cases you received in grading feedback; you may use those as you see fit. Tools which automatically generate code for you (e.g., GitHub copilot) are also strictly prohibited. If you discuss your work with other people, please acknowledge them by listing their names in your submission.
There will be no tolerance for cheating and plagiarism in this course. Any material that is not entirely your own work needs to be properly indicated and cited. This includes any work produced together with fellow students. You MUST indicate any sources of help outside of the course text(s) and your own work, including the names of students with whom you worked, internet resources or other sources of help. Failure to do so constitutes a violation of academic integrity. When in doubt, ask your instructor. Violations of academic integrity will lead to a score of zero on the offending assignment and likely an immediately failing grade for the course.
It is also forbidden to share, post, or otherwise publicize course materials. This includes (but is not limited to) homeworks, exams, solutions, test cases, or your own submissions (in whole or in part). This extends even after the semester ends; course material remains private information which you may not share or reproduce.
Academic Accommodations
It is the policy and practice of Seton Hall University to promote inclusive learning environments. If you have a documented disability you may be eligible for reasonable accommodations in compliance with University policy, the Americans with Disabilities Act, Section 504 of the Rehabilitation Act, and/or the New Jersey Law against Discrimination. Please note, students are not permitted to negotiate accommodations directly with professors. To request accommodations or assistance, please self-identify with the Office for Disability Support Services (DSS), Duffy Hall, Room 67 at the beginning of the semester. For more information or to register for services, contact DSS at (973) 313-6003 or by e-mail, or visit their webpage.
Equity and Compliance
One of our responsibilities in supporting student learning 360° is to help create a safe learning environment both in person and virtually. You should carefully consult the university’s relevant information and policies, and if you have or experience any violations of the above I encourage you to take full advantage of the university resources.
It is also important that you know that federal regulations and University policy require me to promptly convey any information about certain kinds of misconduct known to me to our Title IX Coordinator. In that event, they will work with a small number of others on campus to ensure that appropriate measures are taken and resources are made available to the student who may have been harmed. Protecting a student’s privacy is of utmost concern, and all involved will only share information with those that need to know to ensure the University can respond and assist.
Technology and Platforms
We will use a variety of tools and platforms to facilitate teaching and learning over the semester. Please see the technology page for more details.
Acknowledgments
Thanks over the years for inspiration and content from at least the following: Dan Friedman, Shriram Krishnamurthi, Lindsey Kuper, Vincent St-Amour, Jessie Tov, and Marco Morazán.
