Fall 2021 Syllabus

CC 410 - Advanced Programming - Fall 2021

Instructor Contact Information

  • Instructor: Russell Feldhausen (russfeld AT ksu DOT edu)
    I use he/him pronouns. Feel free to share your own pronouns with me, and I’ll do my best to use them!
  • Office: DUE 2184, but I mostly work remotely from Kansas City, MO
  • Phone: (785) 292-3121 (Call/Text)
  • Website: https://russfeld.me
  • Virtual Office Hours: By appointment via Zoom. Schedule a meeting at https://calendly.com/russfeld

Preferred Methods of Communication:

  • Email: Students should email cc410-help (cc410-help@KSUemailProd.onmicrosoft.com). We will try to respond within one business day.
  • Chat: You may find instructors online via the CS department Discord server and Microsoft Teams. We will try to respond when we can, but if you don’t get a response please email cc410-help.
  • Phone/Text: Emergencies only! We will do our best to respond as quickly as we can.

Prerequisites

  • CC 315 - Data Structures & Algorithms II

Course Overview

Advanced programming techniques and projects. Concepts from object oriented programming, inheritance and polymorphism. GUI programming and event-driven programming. Software development methodologies, processes, and design patterns. Practical experience with professional communication and collaboration.

Course Description

In this course students gain experience writing programs using a variety of advanced programming techniques. Projects cover a variety of application domains and use a variety of technologies to help students master advanced computer programming concepts.

The goal is not just to write software that compiles without errors, but to develop well-written and maintainable software. This goal demands extra attention to design, documentation, and testing. Additionally, we will explore some of the powerful features of the various languages used, as well as other professional tools like Git.

Major Course Topics

  • Software Development Practices
  • Software Engineering Methodologies
  • Design Patterns and Architectures
  • Computer Security
  • Advanced Object-Oriented Design
  • GUI Programming
  • Event-Driven Programming
  • Professional Communication and Collaboration

Student Learning Outcomes

After completing this course, a successful student will be able to:

  • Develop code following industry best-practices for code style and documentation
  • Develop and execute unit tests that adequately test code for bugs and errors
  • Make use of tools to determine the code coverage of a set of unit tests
  • Make use of source code management tools to maintain and store a code base
  • Create a class library following the object-oriented paradigm that makes effective use of inheritance and polymorphism where appropriate
  • Develop a GUI for a given program that uses event-driven programming to respond to GUI events and manipulate underlying data models
  • Apply common software development methodologies, processes and design patterns to create software that performs a desired task or solves a problem
  • Communicate information about their code effectively with various audiences

Course Structure

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.

A common axiom in learner-centered teaching is “the person doing the work is the person doing the learning.” What this really means is that students primarily learn through grappling with the concepts and skills of a course while attempting to apply them. Simply seeing a demonstration or hearing a lecture by itself doesn’t do much in terms of learning. This is not to say that they don’t serve an important role - as they set the stage for the learning to come, helping you to recognize the core ideas to focus on as you work. The work itself consists of applying ideas, practicing skills, and putting the concepts into your own words.

The Work

There is no shortcut to becoming a great programmer. Only by doing the work will you develop the skills and knowledge to make you a successful computer scientist. This course is built around that principle, and gives you ample opportunity to do the work, with as much support as we can offer.

Tutorials, Quizzes & Examples: Each module will include many tutorial assignments, quizzes, and examples that will take you step-by-step through using a particular concept or technique. The point is not simply to complete the example, but to practice the technique and coding involved. You will be expected to implement these techniques on your own in the milestone assignment of the module - so this practice helps prepare you for those assignments.

Milestone Programming Assignments: Throughout the semester you will be building a non-trivial software project iteratively; every week a new milestone (a collection of features embodying a new version of a software application) will be due. Each milestone builds upon the prior milestone’s code base, so it is critical that you complete each milestone in a timely manner! This process also reflects the way software development is done in the real world - breaking large projects into more readily achievable milestones helps manage the development process.

Following along that real-world theme, programming assignments in this class will also be graded according to their conformance to coding style, documentation, and testing requirements. Each milestone’s rubric will include points assigned to each of these factors. It is not enough to simply write code that compiles and meets the specification; good code is readable, maintainable, efficient, and secure. The principles and practices of Object-Oriented programming that we will be learning in this course have been developed specifically to help address these concerns.

Final Project: At the end of this course, you will design and develop a final project of your choosing to demonstrate your ability. This project can link back to your interest or other fields, and will serve as a capstone project for the Computational Core program.

Grading

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:

  • 15% - Tutorials & Quizzes
  • 15% - Examples
  • 40% - Programming Project Milestones
  • 30% - Final Project

Up to 5% of the total grade in the class is available as extra credit. See the Extra Credit - Bug Bounty & Extra Credit - Helping Hands assignments for details.

Letter grades will be assigned following the standard scale:

  • 90% - 100% → A
  • 80% - 89.99% → B
  • 70% - 79.99% → C
  • 60% - 69.99% → D
  • 00% - 59.99% → F

Submission, Regrading, and Early Grading Policy

As a rule, submissions in this course will not be graded until after they are due, even if submitted early. Students may resubmit assignments many times before the due date, and only the latest submission will be graded. For assignments submitted via GitHub release tag, only the tagged release that was submitted to Canvas will be graded, even if additional commits have been made. Students must create a new tagged release and resubmit that tag to have it graded for that assignment.

Once an assignment is graded, students are not allowed to resubmit the assignment for regrading or additional credit without special permission from the instructor to do so. In essence, students are expected to ensure their work is complete and meets the requirements before submission, not after feedback is given by the instructor during grading. However, students should use that feedback to improve future assignments and milestones.

For the programming project milestones, it is solely at the discretion of the instructor whether issues noted in the feedback for a milestone will result in grade deductions in a later milestones if they remain unresolved, though the instructor will strive to give students ample time to resolve issues before any additional grade deductions are made.

Likewise, students may ask questions of the instructor while working on the assignment and receive help, but the instructor will not perform a full code review nor give grading-level feedback until after the assignment is submitted and the due date has passed. Again, students are expected to be able to make their own judgments on the quality and completion of an assignment before submission.

That said, a student may email the instructor to request early grading on an assignment before the due date, in order to move ahead more quickly. The instructor’s receipt of that email will effectively mean that the assignment for that student is due immediately, and all limitations above will apply as if the assignment’s due date has now passed.

Late Work

Warning

Read this late work policy very carefully! If you are unsure how to interpret it, please contact the instructors via 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. Any assignment submitted late will have that assignment’s grade reduced by 10% of the total possible points on that project for each day it is late. This penalty will be assessed automatically in the Canvas gradebook. For the purposes of record keeping, 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.

Incomplete Policy

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:

  1. Students may receive at most two incompletes in Computational Core courses throughout their time in the program
  2. Students will be given 6 calendar weeks from the end of the enrolled semester’s finals week to complete the course
  3. Any modules in a future CC course which depend on incomplete work will not be accessible until the previous course is finished
  4. For example, if a student is given an incomplete in CC 210, then all modules in CC 310 will be inaccessible until CC 210 is complete
  5. Students understand that access to instructor and GTA assistance may be limited after the end of an academic semester due to holidays and other obligations
  6. If a student fails to resolve an incomplete grade after 6 weeks, they will be assigned an ‘F’ in the course. In addition, they will be dropped from any other Computational Core courses which require the failed course as a prerequisite or corequisite.

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 and Codio. Modules may also contain links to external resources for additional information, such as programming language documentation.

Students will make use of GitHub or GitLab for source code management.

Students may choose to do some development work on their own computer. The recommended software is Visual Studio Code along with access to a system running Ubuntu. For Windows systems, Ubuntu can be installed via the Windows Subsystem for Linux. For Mac systems, Ubuntu can be installed in a virtual machine through VirtualBox.

Subject to Change

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.