An introduction to the concepts of information organization and manipulation. The course covers basic sequential structures such as array-backed lists, singly- and doubly-linked lists, stacks, and queues, and moves on to more complex data structures such as trees, graphs, priority queues, and dictionaries. Programming projects are completed in one or more high-level languages.
Students will:
This course will be programming intensive. Though many data structures are now provided by libraries or programming languages themselves, we will implement many of these structures in this course to gain programming experience and an understanding of basic programming principles. The data structures studied here form the fundamental building blocks used in developing complex programs.
Programming assignments will be carried out in a prescribed high-level language. Instruction in the use of this language will be provided, but the focus of this course will not be on a particular programming language, but on language-independent data structures. You are assumed to have previous experience with one or more high-level languages and will be expected to independently acquire the language skills necessary for this course with a minimum level of instruction.I will, in fact, claim that the difference between a bad programmer and a good one is whether he considers his code or his data structures more important. Bad programmers worry about the code. Good programmers worry about data structures and their relationships.
The course will include regular homework and/or programming assignments. There will be no credit given for late assignments (without an excused absence)—turn in as much as you can. Unless otherwise specified, no handwritten work will be accepted.
Reading should be completed before the lecture covering the material per the provided schedule. Not all reading material will be covered in the lectures, but you will be responsible for the material on homework and exams. Quizzes over the assigned reading may be given at any time.
See the GFU CS/IS/Cyber policies for collaboration and discussion of collaboration and academic integrity. Most students would be surprised at how easy it is to detect collaboration or other academic integrity violations such as plagiarism in programming—please do not test us! Remember: you always have willing and legal collaborators in the faculty. We encourage you to ask questions in class, ask for help in the CS lab, use the class mailing list, and visit office hours for assistance.
Unless otherwise specified (e.g., for a group assignment or project), you are expected to do your own work. This also applies to the use of online resources (e.g., StackOverflow, ChatGPT). Put simply: if you are representing someone else's work as your own, you are being dishonest. Any suspected incidents of academic integrity violations will be investigated and reported to the Academic Affairs Office as they arise.
Almost all of life is filled with collaboration (i.e., people working together). Yet in our academic system, we artificially limit collaboration. These limits are designed to force you to learn fundamental principles and build specific skills. It is very artificial, and you'll find that collaboration is a valuable skill in the working world. While some of you may be tempted to collaborate too much, others will collaborate too little. When appropriate, it's a good idea to make use of others—the purpose here is to learn. Be sure to make the most of this opportunity but do it earnestly and with integrity.
If you have specific physical, psychiatric, or learning disabilities and require accommodations, please contact Disability & Accessibility Services (DAS) as early as possible so that your learning needs can be appropriately met. For more information, go to georgefox.edu/das or contact das@georgefox.edu).
My desire as a professor is for this course to be welcoming to, accessible to, and usable by everyone, including students who are English-language learners, have a variety of learning styles, have disabilities, or are new to online learning systems. Be sure to let me know immediately if you encounter a required element or resource in the course that is not accessible to you. Also, let me know of changes I can make to the course so that it is more welcoming to, accessible to, or usable by students who take this course in the future.
The Academic Resource Center (ARC) on the Newberg campus provides all undergraduate students with free writing consultation, academic coaching, and learning strategy review (e.g., techniques to improve reading, note-taking, study, time management). The ARC offers in-person appointments; if necessary, Zoom appointments can be arranged by request. The ARC, located on the first floor of the Murdock Library, is open from 1:00–10:00 p.m., Monday through Thursday, and 12:00–4:00 p.m. on Friday. To schedule an appointment, go to the online schedule at traccloud.georgefox.edu, call 503-554-2327, email the_arc@georgefox.edu, or stop by the ARC. Visit arc.georgefox.edu for information about ARC Consultants' areas of study, instructions for scheduling an appointment, learning tips, and a list of other tutoring options on campus.
George Fox University uses a robust referral and support system, Fox360, to learn about students who are experiencing various student success concerns. Students who are referred by a professor, other employee, or fellow student will be contacted by a member of our Student Support Network to explore the student's situation, develop a plan, and connect with relevant campus resources. GFU community members who have a concern about a student's well-being can submit an aleart by going to fox360.georgefox.edu. Our goal is to provide 360° care for students as they navigate their college experience. For more information see ssn.georgefox.edu or contact Rick Muthiah, Director of Learning Support Services.
Please review the entirety of the university's official COVID-19 web page for the most up-to-date community guidance.
The final course grade will be based on:
Graded course activities will be posted to Canvas. Take care to read the specifications carefully and proceed as directed. Failure to pay attention to detail will often result in few to zero points being awarded on a given activity.
Grades will be updated as often as possible; you are encouraged to use the "What-If" functionality to calculate your total grade by entering hypothetical scores for various items.Note that some graded activities in this course will be submitted via GitLab.
Week 1 · MonIntroduction
|
Week 1 · WedExpectations
Misc: Examples |
Week 1 · FriAbstraction & Encapsulation
Bailey: Ch. 1 |
Week 2 · MonArt of Programming
|
Week 2 · WedJava Programming
Bailey: Appx. B |
Week 2 · FriJava Review: Classes & Instances
Bailey: Ch. 1 |
Week 3 · MonJava Review: Inheritance; Generics; Javadoc
Bailey: Ch. 4 |
Week 3 · WedServe Day—no classes
|
Week 3 · FriRobust Programming: Assertions & Exceptions
Bailey: Ch. 2 |
Week 4 · MonRobust Programming: Unit Testing
Misc: JUnit |
Week 4 · WedArrays
|
Week 4 · FriArrayList & Vector
Bailey: Ch. 3.1–3.5 |
Week 5 · MonIntroduction to Algorithm Analysis
Bailey: Ch. 5.1–5.2 |
Week 5 · WedAmortized Analysis
|
Week 5 · FriComplexity Categories & Big-Oh Notation
Bailey: Ch. 5.3 |
Week 6 · MonMidterm exam review
|
Week 6 · Wed, 10/4Midterm exam
Bailey: Ch. 1–5 |
Week 6 · FriMidterm exam post mortem
|
Week 7 · MonAbstraction & Interfaces
Bailey: Ch. 7 |
Week 7 · WedIteration
Bailey: Ch. 8.1–8.2 |
Week 7 · FriMid-semester break—no classes
|
Week 8 · MonAbstract List
Bailey: Ch. 9.1–9.3 |
Week 8 · WedList: Implementations
Bailey: Ch. 9.4–9.7 |
Week 8 · FriList: Analysis
Bailey: Ch. 9.8–9.9 |
Week 9 · MonSearching
Bailey: Ch. 11.1–11.2 |
Week 9 · WedSorting: Insertion, Selection, Merge Sort
Bailey: Ch. 6.1–6.4 |
Week 9 · FriSorting: Quick Sort
Bailey: Ch. 6.5, 6.7 |
Week 10 · MonStack
Bailey: Ch. 10.1 |
Week 10 · WedQueue
Bailey: Ch. 10.2 |
Week 10 · FriDeque
Bailey: Ch. 10.4 |
Week 11 · MonMidterm exam review
|
Week 11 · Wed, 11/8Midterm exam
Bailey: Ch. 1–10 |
Week 11 · FriMidterm exam post mortem
|
Week 12 · MonAbstract Tree
Bailey: Ch. 12.1 |
Week 12 · WedBinary Tree
Bailey: Ch. 12.4, 12.7 |
Week 12 · FriBinary Tree: Traversals
Bailey: Ch. 12.6 |
Week 13 · MonPriority Queue; Heap
Bailey: Ch. 13.1, 13.3 |
Week 13 · WedBinary Min-Heap
Bailey: Ch. 13.4 |
Week 13 · FriThanksgiving break—no classes
|
Week 14 · MonMap & Optimal Search
Bailey: Ch. 15.1–15.3 |
Week 14 · WedHashing
Bailey: Ch. 15.4–15.7 |
Week 14 · FriAbstract Graph
Bailey: Ch. 16.1 |
Week 15 · MonDirected Graph: Implementations
Bailey: Ch. 16.2–16.4 |
Week 15 · WedDirected Graph: Analysis
Bailey: Ch. 16.2–16.4 |
Week 15 · FriFinal exam review
|
Week 16 · TBDFinal exam
Bailey: * |
This page was last modified on 2023-08-27 at 15:08:51.
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