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 visit office hours, ask questions in class, and use the class mailing list 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 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 preferences, 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 web.penjiapp.com/schools/george-fox, 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.
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 · 8/29Introduction
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Week 1 · 8/31Expectations
Misc: Examples |
Week 1 · 9/2Abstraction & Encapsulation
Bailey: Ch. 1 |
Week 2 · 9/5Art of Programming
FoCS: Ch. 1.1–1.3, 1.5 |
Week 2 · 9/7Java Programming
Bailey: Appx. B |
Week 2 · 9/9Java Review: Classes & Instances
Bailey: Ch. 1 |
Week 3 · 9/12Java Review: Inheritance; Generics; Javadoc
Bailey: Ch. 4 |
Week 3 · 9/14Serve Day—no classes
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Week 3 · 9/16Robust Programming: Assertions & Exceptions
Bailey: Ch. 2 |
Week 4 · 9/19Robust Programming: Unit Testing
Misc: JUnit |
Week 4 · 9/21Arrays
FoCS: Ch. 6.1–6.5 |
Week 4 · 9/23ArrayList & Vector
Weiss: Ch. 1.5–1.6 |
Week 5 · 9/26Introduction to Algorithm Analysis
Weiss: Ch. 1.1–1.3, 2.1–2.3 |
Week 5 · 9/28Amortized Analysis
Weiss: Ch. 2.4 |
Week 5 · 9/30Complexity Categories & Big-Oh Notation
Bailey: Ch. 5.3 |
Week 6 · 10/3Midterm exam review
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Week 6 · 10/5Midterm exam
Weiss: Ch. 1–2 |
Week 6 · 10/7Mid-semester break—no classes
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Week 7 · 10/10Midterm exam post mortem
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Week 7 · 10/12Abstraction & Interfaces
Bailey: Ch. 7 |
Week 7 · 10/14Iteration
Weiss: Ch. 3.1–3.3 |
Week 8 · 10/17Abstract List
Weiss: Ch. 3.1–3.2 |
Week 8 · 10/19List: Implementations
Weiss: Ch. 3.3–3.5 |
Week 8 · 10/21List: Analysis
Bailey: Ch. 9.8–9.9 |
Week 9 · 10/24Searching
Weiss: Ch. 2.4.4 |
Week 9 · 10/26Sorting
Weiss: Ch. 7.1–7.3, 7.6–7.7 |
Week 9 · 10/28Stack
Weiss: Ch. 3.6.1–3.6.2 |
Week 10 · 10/31Stack: Applications
Weiss: Ch. 3.6.3 |
Week 10 · 11/2Queue
Weiss: Ch. 3.7 |
Week 10 · 11/4Deque
Bailey: Ch. 10.4 |
Week 11 · 11/7Midterm exam review
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Week 11 · 11/9Midterm exam
Weiss: Ch. 1–3, 7 |
Week 11 · 11/11Midterm exam post mortem
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Week 12 · 11/14Abstract Tree
Weiss: Ch. 4.1 |
Week 12 · 11/16Binary Tree
Weiss: Ch. 4.1.2 |
Week 12 · 11/18Priority Queue; Heap
Weiss: Ch. 6.1–6.4; 6.9 |
Week 13 · 11/21Map & Optimal Search
Weiss: Ch. 5.1–5.3 |
Week 13 · 11/23Hashing
Weiss: Ch. 5.4–5.6, 5.9 |
Week 13 · 11/25Thanksgiving break—no classes
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Week 14 · 11/28Abstract Graph
Bailey: Ch. 16.1 |
Week 14 · 11/30Graph: Implementations
Weiss: Ch. 9.1 |
Week 14 · 12/2Graph: Algorithms
Weiss: Ch. 9.5 |
Week 15 · 12/5–12/9Selected Topics
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Week 16 · TBDFinal exam
Weiss: * |
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