Collaborate with your teammates but submit individually. Clearly list the members of your team.
An understanding of the following concepts and techniques:
- algorithmic complexity
- runtime performance
- how to measure
- how it relates to algorithmic complexity
- abstract data types (ADT)
- array-based versus linked lists
- getting started with iterators
- automated unit testing using JUnit
- testing for exceptions
- test fixtures and assertions
The key idea is to think about this lab like a physics experiment! You will set it up and then take measurements.
- Review the code.
- Fix the syntax errors (if any, though there probably aren't any).
- Run the code for various inputs to gain an understanding of what it does.
- Complete the items marked TODO in the code and get the tests to pass.
- Conduct the performance measurements: you will find the running times in the test report.
- Create a markdown document called Answers.md and answer the various questions embedded in the code.
- Make sure you have created a separate project for this activity.
- Include a project-specific readme file including your reflection and any other thoughts or design decisions.
- In IDEA, export your project as a zip file and submit as an attachment.
- 1.5 tests passing and completion of items marked TODO
- 1.5 performance testing for increasing problem sizes
- 2 written part
- 1.5 responses to the questions above
- 0.5 grammar, style, formatting
- 0.5 (optional) DRY in performance testing