Comprehensive Guide to Computer Science Final Exam Topics

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Get ready for your computer science final exam with this detailed overview of topics such as data structures, object-oriented design, time efficiency analysis, recursion, trees, balanced trees, and hash tables. Prepare with sample questions and key concepts to ace your exam.

  • Computer Science
  • Final Exam
  • Data Structures
  • Object-oriented Design
  • Recursion

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Presentation Transcript


  1. Saturday, April 20, 8:30-11:00am in B9201 Similar in style to written midterm exam May include (a little) coding on paper About 1.5 times as long as midterm See sample final via email Final exam is cumulative More weight on latter half Closed-book, etc.

  2. Exam will cover almost all material in assignments and labs Except templates, operator overloads Exam will cover almost all material in lecture slides Details of exceptions to follow

  3. Abstract Data Types Data Structures Stacks Queues Array and Linked List implementations Dynamic (heap) versus Static (stack) memory

  4. Object-oriented design principles Basics of classes Pointers Memory management Dangling pointers Memory leaks

  5. Methods for analyzing time efficiency O-notation And others Best, worst, average case Sorting Insertion sort Selection sort Quicksort

  6. Thinking recursively Formulating recursive solutions to problems Writing recursive functions Efficiency of recursive functions MergeSort

  7. Definitions Trees, perfect trees, complete trees Tree traversals In-order, pre-order, post-order Binary search tree Insertion, deletion, search algorithms

  8. Balanced trees Definition of red-black tree Properties of red-black trees No proofs, but you should have intuitive understanding Tree rotations Red-black tree algorithms Don t need full algorithm in your head, but you should be able to follow the examples in the slides

  9. Hash tables Hash functions Resolving collisions Open addressing Linear probing, quadratic probing, double hashing Separate chaining

  10. ADT priority queue Heap data structure Heap algorithms Insertion, removal BubbleUp and BubbleDown Heap implementation using an array Heapsort

  11. Disk access versus memory access Algorithms focus on minimizing disk accesses NOT: M-way trees, B-trees External sorting Mergesort Why are other algorithms slow?

  12. Thanks for all your hard work this term! Good luck on the exam

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