Programming Methology, Fall 2024
Instructors
Marius Minea
Lectures: TuTh 4-5:15pm, Thompson 104
Labs: Wednesdays, see SPIRE for section information
Course Staff
TAs: Frank Chiu, Md. Ashraful Islam, Maximilian Kuechen, Chaolong Tang, Angela Upreti
UCAs: Atharva Kale, Carey Pope (head UCAs),
Adithya Anand, Victor Chen, Noah Ford, Manu Hegde, Liam Mutter, Aarav Nair, Vishwesh Palani, Vinayak Rao, Atharva Shahane, Wenhao Yang
Supplemental Instruction: Lucy Zhang, see Canvas/Campuswire for schedule
Tutoring: CICS offers individual tutoring for CS220, details and signup link will be posted on Campuswire.
Office hours: see schedule on Campuswire and Canvas (TBA)
Textbook:
This course does not use a textbook. Materials will be provided on Canvas and the GitHub course page
Course Goals
The goal of COMPSCI 220 Programming Methodology is to turn you into an advanced programmer with a deep understanding of modern programming methodology. We will emphasize good software engineering skills, including programming abstractions, testing, and debugging. Although the programming language that we will use is JavaScript, we will emphasize general programming principles. Everything that you will learn in the class will be applicable to other modern languages, including (for example) C++, C#, D, Go, Java, Python, Rust, and Swift.
Learning Outcomes
As a successful student, by the end of this course, you will be able to::
- write programs that use abstractions such as higher-order functions (for example: map, filter, and reduce), and object-oriented programming.
- employ an accurate mental model of programming languages that support mutable state, assignable variables, objects, higher-order functions, and garbage collection, as well as understand fundamentals of their implementation.
- design test cases to detect errors in code by applying systematic criteria, and write code predicates to validate the inputs and outputs of a potential solution to a programming problem.
- select and use appropriate design patterns such as builders, fluent APIs, publish/subscribe, state, memento, and promises for handling errors.
- reason about the correctness of code by establishing pre- and postconditions, and loop invariants.
Prerequisites
To succeed in COMPSCI 220, you should be familiar with the following concepts (from the required prerequisite course, COMPSCI 187):
- Loops
- Variables (declaration and scope)
- Defining and using functions to decompose problems
- Recursive functions with integer arguments
- Algorithms and data structures, including lists, trees, and recursion
It is helpful to review these topics if needed. If you feel insufficiently familar with one of these topics, please speak to course staff immediately. Canvas also has guidelines for writing and testing your code.
Grading, exam schedule and make-up policies
Your grade for this course will be composed of several different aspects weighted according to the tentative breakdown below.
- Homework: Programming Component (40%): There will be programming assignments throughout the semester, usually with weekly deadlines. These projects will be programmed in Ocelot and submitted via Gradescope. The lowest homework grade will be dropped.
- Quizzes (10%): Weekly quizzes will be released, usually on Monday, open for 24 hours. Once started you will have a set amount of time to complete each quiz. The lowest two quiz scores will be dropped.
- Lab Participation (8%): Each lab (discussion section) may have a short quiz or a small accompanying assignment that will be graded for completion. Two lab absences are dropped.
- Lesson Questions (2%). In-class questions will count for participation (70%) and correctness (30%). The highest 20 lecture scores will count towards your grade.
- Exams (40%): This course will have two midterm exams and one final exam. You must score at least 1/3 of exam points (33.33% exam average) to pass the course.
- Midterm 1 (12%)
- Midterm 2 (12%)
- Final Exam (16%)
This course will have two midterm exams and one final exam.
You must notify the instructor in advance if you are unable to take the exams at the scheduled time (e.g., due to illness). If a severe accident prevents you from communicating (or asking someone else to do it), you must notify the instructors as soon as you are able to. Failure to do this and missing the exam results in a grade of zero.
Letter grade thresholds:
90: A
86: A-
82: B+
78: B
74: B-
70: C+
66: C
62: C-
58: D+
54: D
These thresholds are tentative and may be adjusted based on the overall performance in the course, but will not be more strict.
Attendance, late submission and exemption policies
You are expected to attend lectures -- this is the best way to engage in discussion and understanding of the material. Lecture questions (and attendance) are part of the course grade. If you cannot attend (e.g., for medical reasons), you are expected to watch the lecture recordings.
Lab attendance is mandatory and part of the course grade. If you cannot attend a lab (e.g., for medical reasons), you must notify the TA leading your lab section ahead of time and discuss how to make up the lab activity.
Turning homework in late helps no one. When you turn homework in late, you cannot receive feedback on time and risk falling behind, as the course has moved on to the next topic. Instructors cannot detect what material needs to be re-emphasized, etc. Because of this, the general rule is that late homework will not be accepted. The only exception to this are justified medical or personal situations that fall outside the ordinary. In these cases, you must notify the instructors ahead of time and request an extension. We will review your request and decide if an extension is warranted.
All homework will be due at 11:59 PM on the due date. You should start homework early. A sudden happening on the due date, when you had planned on doing most of the work is not a reason for an extension. Please allow time to check and make sure you've submitted everything properly, and avoid any unexpected issues (slow Internet connection, uploading the wrong file in a hurry, leaving extraneous code in, etc.) Also, expect assignments to require several programming and testing sessions to complete. We suggest you begin working on them early, so we can all collaborate and help each other with any questions in a timely way.
Academic Honesty and Collaboration Policy
Since the integrity of the academic enterprise of any institution of higher education requires honesty in scholarship and research, academic honesty is required of all students at the University of Massachusetts Amherst. Academic dishonesty is prohibited in all programs of the University. Academic dishonesty includes but is not limited to: cheating, fabrication, plagiarism, and facilitating dishonesty. Appropriate sanctions may be imposed on any student who has committed an act of academic dishonesty. Instructors should take reasonable steps to address academic misconduct. Any person who has reason to believe that a student has committed academic dishonesty should bring such information to the attention of the appropriate course instructor as soon as possible. Instances of academic dishonesty not related to a specific course should be brought to the attention of the appropriate department Head or Chair. Since students are expected to be familiar with this policy and the commonly accepted standards of academic integrity, ignorance of such standards is not normally sufficient evidence of lack of intent (http://www.umass.edu/dean_students/codeofconduct/acadhonesty/).
In COMPSCI 220, you are encouraged to form study groups, learn and discuss the course material jointly with others.
You are required to work individually on all items resulting in a grade. In particular, it is forbidden to share homework code or solution ideas.
You are encouraged to ask public questions, in office hours or on Campuswire. Your questions and the answers to them can be useful for others as well (and you are encouraged to help with answers). Public questions about homework should be of a general nature (clarification, applicable course material), and not involve code snippets or specific solution ideas. Use private questions otherwise if needed.
This course assumes that all work submitted by students will be generated by the students themselves, working individually or in groups. Students should not have another person/entity do the writing of any portion of an assignment for them, which includes hiring a person or a company to write assignments and using artificial intelligence tools like ChatGPT.
As members of the College of Information and Computer Sciences at UMass Amherst we expect everyone to behave responsibly and honorably. In particular, we expect each of you not to give, receive, or use aid in examinations, nor to give, receive, or use unpermitted aid in any academic work. Doing your part in observing this code, and ensuring that others do likewise is essential for having a community of respect, integrity, fairness, and trust.
If you cheat in a course, you are taking away from your own opportunity to learn and develop as a professional. You also hurt your colleagues, and this will hurt people you will work with in the future, who expect an honest and responsible professional.
As faculty, we pledge to use academic policies designed for fairness, avoiding situations that are conducive to violating academic honesty, as well as unreasonable or unusual procedures that assume dishonesty.
Academic dishonesty as defined by the University's Academic Honest Policy includes but is not limited to:
- Cheating - the intentional use or attempted use of trickery or deception in one's academic work.
- Fabrication - intentional falsification and/or invention of any information or citation
- Plagiarism - knowingly representing the words or ideas of another as one's own work
- Facilitating Dishonesty - knowingly helping or attempting to help another commit an act of academic dishonesty
Any violation of the Academic Honesty Policy could result in a failing grade in COMPSCI 220 and initiation of the formal Academic Honesty Procedures of the University. Students are expected to be familiar with these policies, if you have any questions please email the course instructors for clarification.
The College of Information and Computer Sciences explicitly forbids any redistribution (including publicly available posting on an internet site) of any CICS course materials (including student solutions to course assignments, projects, exams, etc.) without the express written consent of the instructor of the course from which the materials come. Violations of this policy will be deemed instances of “facilitating dishonesty” (since a student making use of such materials would be guilty of plagiarism) and therefore may result in charges under the Academic Honesty Policy.
Accommodations
The University of Massachusetts Amherst is committed to providing an equal educational opportunity for all students. If you have a documented physical, psychological, or learning disability on file with Disability Services (DS), you may be eligible for reasonable academic accommodations to help you succeed in this course. If you have a documented disability that requires an accommodation, please notify me within the first two weeks of the semester so that we may make appropriate arrangements. For further information, please visit Disability Services (https://www.umass.edu/disability/).
Equity and Inclusion Statement
We are committed to fostering a culture of diversity and inclusion, where everyone is treated with dignity and respect. This course is for everyone. This course is for you, regardless of your age, background, citizenship, disability, sex, education, ethnicity, family status, gender, gender identity, geographical origin, language, military experience, political views, race, religion, sexual orientation, socioeconomic status, or work experience.
Because of that, one of the things we all need to realize is that we will be bringing different skills to the course, and we will all be learning from and with each other. Some of us are great artists, some of us aren't. Some of us have had previous experience with community organizing, and for some of us that may be something new. Some of us have very definite plans for our professional careers, some of us are still exploring. Each of these skills will help us succeed, both individually and as a group.
Please be kind and courteous. Respect that people have differences of opinion, and work and approach problems differently. There is seldom a single right answer to complicated questions. Please keep unstructured critique to a minimum. Criticism should be constructive.
Disruptive behavior is not welcome, and insulting, demeaning, or harassing anyone is unacceptable.
We follow the university's guidelines for classroom civility.
In particular, we don’t tolerate behavior that excludes people in socially marginalized groups. If you feel you have been or are being harassed or made uncomfortable by someone in this class, please contact a member of the course staff immediately, or if you feel uncomfortable doing so, contact the Dean of Students office.
This course is for all of us. We will all learn from each other. This is our welcome.
List of books or other equipment or technology required
No textbook is required for this course. The course is coding-intensive and it is expected that you have access to a computer and the internet whenever you plan to work. We use Canvas for course material and quizzes, Campuswire for communication, and Gradescope for homework submission.
Communication policy and response frequency
We use Campuswire for communication. We will attempt to answer all
questions within 24 hours and often much sooner. However, you should
not rely on last-minute questions for help on homework.
When needed, use private instructor-only posts rather than e-mail,
this will make them more readily seen, and any of the staff team can
answer them.
For sensitive private matters, email the instructor.
Chosen names and pronouns
Everyone has the right to be addressed by the name and pronouns that they use for themselves. Students can indicate their preferred/chosen first name and pronouns on SPIRE, which appear on class rosters. Please let me know what name and pronouns I should use for you if they are not on the roster. A student’s chosen name and pronouns are to be respected at all times in the classroom.
Title IX Statement
In accordance with Title IX of the
Education Amendments of 1972 that prohibits gender-based
discrimination in educational settings that receive federal funds, the
University of Massachusetts Amherst is committed to providing a safe
learning environment for all students, free from all forms of
discrimination, including sexual assault, sexual harassment, domestic
violence, dating violence, stalking, and retaliation. This includes
interactions in person or online through digital platforms and social
media. Title IX also protects against discrimination on the basis of
pregnancy, childbirth, false pregnancy, miscarriage, abortion, or
related conditions, including recovery. There are resources here on
campus to support you. A summary of the available Title IX resources
(confidential and non-confidential) can be found at the following
link: https://www.umass.edu/titleix/resources.
You do not need to make a formal report to access them. If you need
immediate support, you are not alone. Free and confidential support is
available 24 hours a day / 7 days a week / 365 days a year at the SASA Hotline 413-545-0800.
UMass instructors have been informed they are considered "responsible employees" or "mandatory reporters" which means they cannot keep Title IX information confidential and are required to report incidents to the Title IX Coordinator.
Schedule and topics (subject to change)
Week |
Topics |
1 |
Introduction and Higher-order functions |
2 |
Basic TypeScript Features. Type Signatures |
3 |
More higher-order functions |
4 |
Unit testing |
5 |
Lists |
6 |
Closures |
7 |
Mental Models |
8 |
Mental Models and Closures (cont'd.) |
9 |
Midterm review |
10 |
Property-based testing |
11 |
Object-Oriented Programming |
12 |
Streams |
13 |
More Streams |
14 |
Builders and Fluent Interfaces |
15 |
Using Git |
16 |
Observer Pattern |
17 |
Midterm 2 Review |
18 |
Asynchronous Programming (part 1) |
19 |
Asynchronous Programming (part 2) |
20 |
Program Correctness |
21 |
Program Correctness |
22 |
SOLID Principles |
23 |
Building an Interpreter (part 1) |
24 |
Building an Interpreter (part 2) |
25 |
Extending Libraries |
26 |
Final Review |