Study Materials

Here are resources to help you prepare for exams. You may also want to see the class notes, class code, the in class examples that were distributed via git-keeper, and the recordings of class sessions on Microsoft Stream.

Exam 2 Topics

The format of this exam will be similar to Exam 1. It will take place on Moodle here. The exam will open at 8 AM EDT on Saturday, April 3 and will close at 11:59 PM EDT on Monday, April 5. Once you have begun the exam you will have a 2 hour time limit to complete it.

• Web APIs
  • JSON
• Python Exceptions
• Software Development Lifecycle
  • Roles involved
  • Steps involved
  • Waterfall vs iterative models
• Requirements
  • User stories
• Design Principles
  • Separation of Concerns
  • Single Responsibility Principle
  • Cohesion
• Abstraction
• Git
  • Branches
  • Merging (you may want to review this section from the git book)
    • Fast-forward vs. a merge commit
  • Rebasing (relevant section from the git book)
    • Compared to merging
  • Remotes
• Python Iterable Implementation
  • Classes
  • Generators

Exam 1 Overview

The exam will take place on Moodle here. The exam will open at 8 AM EST on Sunday, February 21 and will close at 11:59 PM EST on Monday, February 22. Once you have begun the exam you will have a 2 hour time limit to complete it. The length of the exam will be the same as an exam that I would give during the length of our normal class period, so I anticipate that most students should be able to complete the exam within 1 hour.

The exam will consist of multiple choice questions and short essay-style questions that will require written answers. For the written questions you will be asked to answer questions with explanations, comment on Python and Kivy code, and discuss UML diagrams.

Exam 1 Topics

• Ways to measure “good” software
• Python
  • References
  • Modules
  • Classes
  • Decorators
• Kivy
  • App class
  • Widget tree, layouts, and the role of composition and inheritance
  • Input events, button callbacks, etc.
  • KV files
• Object oriented programming
  • Inheritance
  • Abstract base classes
  • Polymorphism
  • Composition
• UML
  • You will be asked to interpret UML, but not to create any diagrams
• Design patterns
  • Motivation for use
  • Strategy pattern
  • Observer pattern
• Coupling
• GitHub workflow
  • Forks
  • Pull requests