CS112 final project guide

CS112 culminates in a final project. This project is to be completed over the last weeks of the semester in groups of 1-3 students. The goal is to demonstrate your understanding of the concepts we’ve learned over the semester and to have some fun exploring a computer science project of your choice!

Timeline

  • Project group signups due Thursday, April 30 at 9pm
    • Sign up here.
    • You can work with anyone you’d like, including your previous project partners.
    • Class will be canceled on Wednesday, April 29. Instead, Doug will hold extended office hours from 10am-2pm to discuss project ideas.
  • Project document due Monday, May 11 at 9pm
    • You’ll also hand in your code at this time.
  • Project presentations on Monday, May 11
    • These are mandatory for groups of 2-3 and optional for people doing the project individually.

Project document

The project document should be around 2-5 pages long. It should present a complete summary of your project–we’ll ask you to hand in your code as well, but it should be possible to understand what you’ve done based solely on the document. It should include at least the following sections:

Goal
This section should describe, in your own words, the goal of your project. What are you trying to accomplish? This section can include things you wanted to do but weren’t able to complete.
Implementation
This section should describe the actual implementation of your project. What design decisions did you make? What data structures did you use? What functions, classes, and methods did you develop?
Results
This section should describe the results of your hard work. Include any measurements you did, example program inputs and outputs, or screenshots. This is also the place to tell us about testing: how did you ensure that your code is correct?
Challenges
Describe any challenges you faced. What was difficult? Did you have any false starts in implementing your project? If you had goals that you weren’t able to accomplish, tell us why!
Future work
If you had as much time as you wanted to keep working on this project, what would you try to do? Be creative!

Project presentation

We will do project presentations over Zoom. Doing a presentation is mandatory for groups of 2-3 and optional for those doing the project individually. The presentations will be informal (i.e., don’t make slides)–you will just be walking through your project with Doug (and possibly one or more TAs). All group members should be prepared to answer questions about any aspect of the project. Presentations will be scheduled for 15 minutes each. We will schedule as many presentations as possible for our scheduled final exam slot (9am-12pm on May 11), but some presentations may end up at a different time on that day.

Project suggestions

We have come up with a number of suggested projects. You can implement one of these ideas as written, implement a modified version, or work on some other project of your choice. Regardless, we recommend looking over the suggestions to get a sense of how to scope your project.

We’ve included a suggested group size range for each project. We expect more from larger groups. If you work in a group of 3 on a project designed for 1-2 people, you should extend it in some way; conversely, if you work alone on a project designed for a group of 2-3, you should feel free to scale it back somewhat.

All of our suggestions are extensions or modifications to one of the three other course projects.

Project 1 extensions

A novel dataset (1-2 people)

Use your classifier from project 1 with a new dataset of your choosing (one from another class, or collected via a web API). The bulk of this project will likely consist of reformatting the data so that you can use it with your classifier.

Testing project 1 (2-3 people)

In Project 1 you built a genre classifier, but didn’t evaluate its effectiveness. For classifiers like the one you built in Project 1, a standard way to evaluate accuracy is to divide your data into a “training set” and a “test set.” Instead of computing your tf-idf model from all of your data, you’d compute it from a subset of your data–say, 80% of the songs; this is called the training set. You’d then measure its accuracy on the remaining 20% of songs; this is the test set. You’d need to calculate how often it identifies the correct answer, and compare your results against a reasonable baseline (say, always guessing the most common genre).

Project 2 extensions

Local temperatures (1-2 people)

In the Project 2 climate simulation, each country’s temperature was a simple function of the total BaD in the atmosphere. For this project, you could add a second type of pollution that affects polluting countries more than other countries. You’d need to track each country’s emissions separately and calculate each country’s temperature based on both the global BaD total and the local and global totals of this new molecule.

Project 3 extensions

Twitter-lite (1-2 people)

Project 3 works “like Facebook”–the underlying graph is undirected. Modify the project to instead work “like Twitter,” with a directed graph. You will need to modify the friend suggestions, hobby suggestions, and most popular users. For instance, if user A follows user B, they might want to follow users who user B’s other followers follow.

Better suggestions (1 person)

The hobby suggestions in Project 3 only suggest hobbies based on hobbies of friends. We could instead imagine suggesting hobbies related to a user’s existing hobbies: if a high percentage of users with hobby A also have hobby B, we should suggest hobby B. Improve the hobby suggestion algorithm to suggest related hobbies, based on the hobbies of every user in the graph.

A group of 3 could work on a project combining this suggestion and the previous one.

Something completely different

Do you have a dataset that can be represented as a graph, maybe from your other coursework or independent research? Could you simulate some natural phenomenon in code? Do you have a hobby that could benefit from a particular computer program? We highly encourage final projects related to your own interests–if it involves writing a program to solve a problem, it’s probably a great project!