Advanced data structures and related algorithms. Formal software development methods and software engineering fundamentals. Introduction to requirements analysis processes that provide the specification of algorithmic requirements.
This course introduces advanced data structures, such as trees, graphs, and heaps. Several new algorithms using these data structures are covered. Students also learn software development methods and software engineering fundamentals and use those skills to develop projects of increasing size and scope effectively.
These courses are being taught 100% online, and each module is self-paced. There may be some bumps in the road as we refine the overall course structure. Students will work at their own pace through a set of modules, with approximately one module being due each week. Material will be provided in the form of recorded videos, online tutorials, links to online resources, and discussion prompts. Each module will include a coding project or assignment, many of which will be graded automatically through Codio. Assignments may also include portions which will be graded manually via Canvas or other tools.
In theory, each student begins the course with an A. As you submit work, you can either maintain your A (for good work) or chip away at it (for less adequate or incomplete work). In practice, each student starts with 0 points in the gradebook and works upward toward a final point total earned out of the possible number of points. In this course, each assignment constitutes a portion of the final grade, as detailed below:
Up to 5% of the total grade in the class is available as extra credit. See the Extra Credit - Bug Bounty assignment for details.
Letter grades will be assigned following the standard scale:
Warning
Read this late work policy very carefully! If you are unsure how to interpret it, please contact the instructors via the help email. Not understanding the policy does not mean that it won’t apply to you!
Since this course is entirely online, students may work at any time and at their own pace through the modules. However, to keep everyone on track, there will be approximately one module due each week. Each graded item in the module will have a specific due date specified. All of the components of a module will be subject to the late policy if the module is submitted late. This penalty will be assessed via a single separate assignment entry in the gradebook, containing the sum of all grade reductions in the course for that student.
The following table outlines the highest possible score that a module can earn based on when it is complete
| Wednesday | Thursday | Friday | Saturday | |
|---|---|---|---|---|
| Before or at 11:59PM CST | 100% | 90% | 80% | 70% |
| After 11:59PM CST | 90% | 80% | 70% | 60% |
The table reads as: The assignments of a module turned in on Friday before midnight can receive at most 80% of the possible points.
Assignments which are submitted late but score below the threshold will not receive a penalty. For example, if a module is completed on Friday afternoon and the project scores 75/100, then no penalty will be received.
For the purposes of recordkeeping, the submission time of the confirmation quiz in each module will be used to establish the completion time of the entire module in case of a discrepancy. This is because Codio may update submission times when assignments are regraded, but the quiz in Canvas should only be completed once.
However, even if a module is not submitted on time, it must still be completed before a student is allowed to begin the next module. So, students should take care not to get too far behind, as it may be very difficult to catch up.
Finally, all course work must be submitted on or before the last day of the semester in which the student is enrolled in the course in order for it to be graded on time.
If you have extenuating circumstances, please discuss them with the instructor as soon as they arise so other arrangements can be made. If you find that you are getting behind in the class, you are encouraged to speak to the instructor for options to make up missed work.
Students should strive to complete this course in its entirety before the end of the semester in which they are enrolled. However, since retaking the course would be costly and repetitive for students, we would like to give students a chance to succeed with a little help rather than immediately fail students who are struggling.
If you are unable to complete the course in a timely manner, please contact the instructor to discuss an incomplete grade. Incomplete grades are given solely at the instructor’s discretion. See the official K-State Grading Policy for more information. In general, poor time management alone is not a sufficient reason for an incomplete grade.
Unless otherwise noted in writing on a signed Incomplete Agreement Form, the following stipulations apply to any incomplete grades given in Computational Core courses:
To participate in this course, students must have access to a modern web browser and broadband internet connection. All course materials will be provided via Canvas, Piazza, and Codio. Modules may also contain links to external resources for additional information, such as programming language documentation.
The details in this syllabus are not set in stone. Due to the flexible nature of this class, adjustments may need to be made as the semester progresses, though they will be kept to a minimum. If any changes occur, the changes will be posted on the Canvas page for this course and emailed to all students. All changes may also be posted to Piazza.
Kansas State University has an Honor and Integrity System based on personal integrity, which is presumed to be sufficient assurance that, in academic matters, one’s work is performed honestly and without unauthorized assistance. Undergraduate and graduate students, by registration, acknowledge the jurisdiction of the Honor and Integrity System. The policies and procedures of the Honor and Integrity System apply to all full and part-time students enrolled in undergraduate and graduate courses on-campus, off-campus, and via distance learning. A component vital to the Honor and Integrity System is the inclusion of the Honor Pledge which applies to all assignments, examinations, or other course work undertaken by students. The Honor Pledge is implied, whether or not it is stated: “On my honor, as a student, I have neither given nor received unauthorized aid on this academic work.” A grade of XF can result from a breach of academic honesty. The F indicates failure in the course; the X indicates the reason is an Honor Pledge violation.
For this course, a violation of the Honor Pledge will result in an automatic 0 for the assignment and the violation will be reported to the Honor System. A second violation will result in an XF in the course.
The Codio platform can perform automatic plagiarism detection by comparing submitted projects against other students' submissions and known solutions. That information may be used to determine if plagiarism has taken place.
Students with disabilities who need classroom accommodations, access to technology, or information about emergency building/campus evacuation processes should contact the Student Access Center and/or their instructor. Services are available to students with a wide range of disabilities including, but not limited to, physical disabilities, medical conditions, learning disabilities, attention deficit disorder, depression, and anxiety. If you are a student enrolled in campus/online courses through the Manhattan or Olathe campuses, contact the Student Access Center at accesscenter@k-state.edu, 785-532-6441; for K-State Polytechnic campus, contact Academic and Student Services at polytechnicadvising@ksu.edu or call 785-826-2674.
Note
This is our personal policy and not a required syllabus statement from K-State. It has been adapted from this statement created by two educators at Brown University. We feel that a statement such as this is very powerful and important in today’s world, and we’ll do our best to live up to it.
In an ideal world, science and technology would be objective. However, much of science and technology is subjective and is historically built on a small subset of privileged voices. In this class, we will reference many materials from a diverse set of sources, but limits still exist on this diversity. I acknowledge that it is possible that there may be both overt and covert biases in the material due to the lens with which it was written, even though the material is primarily of a technical nature.
Please contact me or submit anonymous feedback through the Computer Science department office if you have any concerns or suggestions regarding this course and related materials.
Furthermore, I would like to create a learning environment for my students that supports a diversity of thoughts, perspectives and experiences, and honors your identities (including race, gender, class, sexuality, religion, ability, etc.). To help accomplish this:
I, like many people, am still in the process of learning about diverse perspectives and identities. If something was said in class, by anyone, that made you feel uncomfortable, please talk to me about it. Again, anonymous feedback is always an option.
Note
This is our personal policy and not a required syllabus statement from K-State. It has been adapted from this statement from K-State Global Campus, and the Recurse Center Manual. We have adapted their ideas to fit this course.
Online communication is inherently different than in-person communication. When speaking in person, many times we can take advantage of the context and body language of the person speaking to better understand what the speaker means, not just what is said. This information is not present when communicating online, so we must be much more careful about what we say and how we say it in order to get our meaning across.
Here are a few general rules to help us all communicate online in this course, especially while using tools such as Piazza:
As a participant in course discussions, you should also strive to honor the diversity of your classmates by adhering to the K-State Principles of Community.
All student activities in the University, including this course, are governed by the Student Judicial Conduct Code as outlined in the Student Governing Association By Laws, Article V, Section 3, number 2. Students who engage in behavior that disrupts the learning environment may be asked to leave the class.
Kansas State University is committed to providing a safe teaching and learning environment for student and faculty members. In order to enhance your safety in the unlikely case of a campus emergency make sure that you know where and how to quickly exit your classroom and how to follow any emergency directives. To view additional campus emergency information go to the University’s main page, www.k-state.edu, and click on the Emergency Information button, located at the bottom of the page.
K-State has many resources to help contribute to student success. These resources include accommodations for academics, paying for college, student life, health and safety, and others found at www.k-state.edu/onestop.
To protect the health and safety of the K-State community, students, faculty, staff and visitors must wear face coverings over their mouths and noses while on K-State campuses in all hallways, public spaces, classrooms and other common areas of campus buildings, and when in offices or other work spaces or outdoor settings when 6-feet social distancing cannot be maintained. In addition, all students, faculty, and staff are required to take the COVID-19 and Face Mask Safety training. Employees who need reasonable accommodations and assistance related to required face coverings may contact the ADA coordinator at charlott@k-state.edu, and students needing accommodations may contact the Student Access Center at accesscenter@k-state.edu. In classrooms, faculty have the right to deny a student entry into the room if the student is not wearing a face covering.
Kansas State University is a community of students, faculty, and staff who work together to discover new knowledge, create new ideas, and share the results of their scholarly inquiry with the wider public. Although new ideas or research results may be controversial or challenge established views, the health and growth of any society requires frank intellectual exchange. Academic freedom protects this type of free exchange and is thus essential to any university’s mission.
Moreover, academic freedom supports collaborative work in the pursuit of truth and the dissemination of knowledge in an environment of inquiry, respectful debate, and professionalism. Academic freedom is not limited to the classroom or to scientific and scholarly research, but extends to the life of the university as well as to larger social and political questions. It is the right and responsibility of the university community to engage with such issues.
© The materials in this online course fall under the protection of all intellectual property, copyright and trademark laws of the U.S. The digital materials included here come with the legal permissions and releases of the copyright holders. These course materials should be used for educational purposes only; the contents should not be distributed electronically or otherwise beyond the confines of this online course. The URLs listed here do not suggest endorsement of either the site owners or the contents found at the sites. Likewise, mentioned brands (products and services) do not suggest endorsement. Students own copyright to what they create.