CS 231 Data Structures and Algorithms
Syllabus

• Section A: M-W-F 9:00 - 9:50 am, Lovejoy 213
• Section B: M-W-F 11:00 - 11:50 am, Lovejoy 205
• Lab A: M 1:00 - 2:20 pm Davis 102
• Lab B: M 2:30 - 3:50 pm Davis 102
• Lab C: T 1:00 - 2:20 pm Davis 102
• Lab D: T 2:30 - 3:50 pm Davis 102

The following structure will rarely change.

In order to provide as much help as possible to you as you work on assignments in this course, the CS Department has hired the following upper-level CS students to work as TAs in Davis in the afternoons and evenings. You are strongly encouraged to take advantage of this resource.

TA Hours: All TA sessions will be in person in Spring 2022. Here is the TA schedule and Windows Support.

1. Students understand the advantages and disadvantages of fundamental data structures and can implement them using object- oriented design principles.
2. Students understand, can implement, and can calculate the time and space efficiency of classic search, sort, and traversal algorithms, including the use of big-Oh notation.
3. Students understand the tradeoffs between different implementations of data structures and algorithms and can make appropriate design decisions based on application data requirements.
4. Students can use fundamental data structures and algorithms appropriately to solve a variety of computational problems.
5. Students can communicate the results of their work and describe an algorithm.

The work in lab will lead into and be part of the week's project. Labs will also count significantly towards participation.

During each lab, the instructor will not answer questions about any projects until you have completed the exercises for that lab.

Programming projects involve completing more significant programs as well as a writeup describing the work completed in the project.

There will be regular opportunities for you to practice what you have learned and to demonstrate your accomplishments.

The course grade will be determined as follows:

• Homeworks will be assigned on Mondays and due on Thursdays at noon.
• This is a hard deadline.
  Late submissions will not be accepted.
• The homeworks will prepare you for the quiz on Friday! Take them seriously and you should be well-prepared for the quiz.
• Homework will be graded in a binary fashion: if you hand in a reasonable attempt, you get a 1, otherwise a 0.

• There is a quiz on most Fridays.
• The quizzes let you show me what you have learned. These should be quick and straightforward if you participate in lecture and review lecture notes.
• If you know in advance that you can not attend a quiz (team sports, etc.) you can arrange with your professor take it a day early on Thursday during office hours.
• Please contact your professor in the event of illness and other unforeseen circumstances, we will work out accommodations.

• You are expected to attend every class and lab. This is important for the overall learning experience and cohesion of the course.
• If you must miss a class for any reason, please email me in advance. I am happy to work with you.
• For this course to be truly successful, your presence and participation is important. When you have a question, ask it. It is highly probable that one of your classmates has the same question.

Sections A & B:Thursday, May 12 at 6:00pm. There are no make-ups.

It should go without saying that you should back up any files related to this course. If the code you submit to us is somehow lost (through your fault or our fault), I must be able to get another copy from you. I suggest keeping your CS231 labs and projects on Google Drive, Dropbox, or Microsoft OneDrive. That way, you have a backup stored in the cloud.

There is no required textbook for this course. All lecture notes and code from class will be posted on Moodle.

• A Practical Introduction to Data Structures and Algorithm Analysis, Java version, by Clifford Shaffer
• Data Structures and Algorithms, by Goodrich, Tamassia, and Goldwasser
• Java Structures, by Duane A. Bailey

Labs and Projects: Come to lab ready to focus on the new project. Ask the instructor and TAs for help if you need it.

Short homeworks: Try them. You will receive full credit as long as you make an honest attempt to complete every question. Please ask or email questions if something isn't clear. As long as you submit your response by Thursday at noon you will get credit. Review the homework solutions to check your understanding of the material before the quiz. There is no partial credit for late homeworks because we may go over the answers in class on Friday before you take the quiz.

Quizzes: Study for the quizzes by doing the homeworks.

Participation: Speak up in class. Come to office hours. Ask your instructors or TA for help.

Final Exam: The final exam will be similar to a large set of quizzes (but written from a more wholistic perspective). The best way to study for the final exam is to retake all of the old quizzes. Also, read through your notes and make sure you understand everything in them.

Computer science, both academically and professionally, is a collaborative discipline. In any collaboration, however, all parties are expected to make their own contributions and to generously credit the contributions of others. In our class, therefore, collaboration on assignments is encouraged, but you as an individual are responsible for understanding all the material in the assignment and doing your own work. Always strive to do your best, give generous credit to others, start early, and seek help early from both your professors and classmates.

The following rules are intended to help you get the most out of your education and to clarify the line between honest and dishonest work. We reserve the right to ask you to verbally explain the reasoning behind any answer or code that you turn in and to modify your project grade based on your answers. It is vitally important that you turn in work that is your own. We do use automated plagiarism detection software, so please be sure to abide by these, rather minimal, rules. Reports of academic dishonesty are handled by an academic review board and a finding of academic dishonesty may result in significant sanctions. For more details on Colby's Academic Integrity policies and procedures, see colby.edu/academicintegrity.

• If you have had a substantive discussion of any homework or programming solution with a classmate, then be sure to cite them in your write-up. If you are unsure of what constitutes "substantive", then ask me or err on the side of caution. As one rule of thumb, you may discuss your approach to solving a problem, but you must not share or look at another classmate's code or written answers to project questions.
• You must not copy answers or code from another student either by hand or electronically. Another way to think about it is that you should communicate with one another in natural human sentences, not in lines of code from a programming language.

Colby College is a community dedicated to learning and committed to the growth and well-being of all its members.

As a community devoted to intellectual growth, we value academic integrity. We agree to take ownership of our academic work, to submit only work that is our own, to fully acknowledge the research and ideas of others in our work, and to abide by the instructions and regulations governing academic work established by the faculty.

As a community built on respect for ourselves, each other, and our physical environment, we recognize the diversity of people who have gathered here and that genuine inclusivity requires active, honest, and compassionate engagement with one another. We agree to respect each other, to honor community expectations, and to comply with College policies.

As a member of this community, I pledge to hold myself and others accountable to these values. More ...

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If you wish to speak confidentially about an incident of sexual misconduct, please contact Colby Counseling Services (207-859-4490) or the Director of the Gender and Sexual Diversity Program, Emily Schusterbauer (207-859-4093).

Students should be aware that faculty members are considered responsible employees; as such, if you disclose an incident of sexual misconduct to a faculty member, they have an obligation to report it to Colby's Title IX Coordinator. "Disclosure" may include communication in-person, via email/phone/text, or through class assignments.

To learn more about sexual misconduct or report an incident, visit http://www.colby.edu/sexualviolence/.