Work in teams of two but submit individually (see details below)

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.

1. Review the code.
2. Fix the syntax errors (if any, though there probably aren't any).
3. Run the code for various inputs to gain an understanding of what it does.
4. Complete the items marked TODO in the code and get the tests to pass.
5. Conduct the performance measurements: you will find the running times in the test report.
6. Create a markdown document called Answers.md and answer the various questions embedded in the code.

Please submit the following deliverables:

• Shared GitHub Classroom lab3 repository where you worked on this project as a group (there should be commits from all group members)
• Individual Sakai submission under "Lab 3":
  • URL of shared GitHub team repository
  • Brief description of your collaboration style and summary of your individual contributions to this team project

• 1 submission via GitHub
• 1 tests passing and completion of items marked TODO
• 1 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

5 points TOTAL