Data Structures and Algorithms in Java
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  • Preface
    • Syllabus
    • Schedule
  • 0. Getting Started
    • 0.1. Environment Setup
    • 0.2. Quiz
  • 1. Java Essentials
    • 1.1. Abstraction
    • 1.2. Implementation
    • 1.3. Unit Testing
    • 1.4. Quiz
  • 2. Priority Queues
    • 2.1. Simple Priority Queues
    • 2.2. Binary Heap
    • 2.3. Unit Testing
    • 2.4. Benchmarking
    • 2.5. Quiz
  • 3. Sorting Algorithms
    • 3.1. Abstraction
    • 3.2. Comparison-based Sort
    • 3.3. Divide & Conquer Sort
    • 3.4. Distribution-based Sort
    • 3.5. Quiz
    • 3.6. Homework
  • 4. Binary Search Trees
    • 4.1. Binary Search Trees
    • 4.2. Balanced BST
    • 4.2. AVL Trees
    • 4.3. Red-Black Trees
    • 4.4. Quiz
  • 5. Tries
    • 5.1. Concept
    • 5.2. Implementation
    • 5.3. Quiz
    • 5.4. Homework
  • 6. Disjoint Sets
    • 6.1. Concept
    • 6.2. Implementation
    • 6.3. Quiz
  • 7. Graphs
    • 7.1. Implementation
    • 7.2. Cycle Detection
    • 7.3. Topological Sorting
    • 7.4. Quiz
  • 8. Minimum Spanning Trees
    • 8.1. Abstraction
    • 8.2. Prim's Algorithm
    • 8.3. Kruskal’s Algorithm
    • 8.4. Edmonds' Algorithm
    • 8.5. Quiz
    • 8.6. Homework
  • 9. Network Flow
    • 9.1. Flow Network
    • 9.2. Ford-Fulkerson Algorithm
    • 9.3. Simplex Algorithm
    • 9.3. Quiz
  • 10. Dynamic Programming
    • 10.1. Fibonacci Sequence
    • 10.2. Tower of Hanoi
    • 10.3. Longest Common Subsequence
    • 10.4. Quiz
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  • Tower of Hanoi
  • Longest Common Subsequence
  • Extra Credit

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  1. 10. Dynamic Programming

10.4. Quiz

This section provides exercises for better understanding in dynamic programming.

Previous10.3. Longest Common Subsequence

Last updated 2 years ago

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Tower of Hanoi

Write a report quiz9.pdf that includes answers to the followings.

  • As n increases from 1 to 10, how many times does the auxiliary solve() method get called recursively in and ?

  • Is there clear patterns between n and the number of the method calls made by these classes? Explain the patterns if exist.

Longest Common Subsequence

Include answers to the followings in quiz9.pdf:

  • Explain what the values of the dynamic table mean in the class.

  • LCSDynamic pre-populates the dynamic table before making any recursive calls. Is it possible to find a LCS with dynamic programming by populating the dynamic table while making recursive class.

You may need a different type of a dynamic table to populate it while making recursive calls.

Extra Credit

  • Create the class under the package.

  • Update the solveAll() that returns all longest common subsequences between two strings.

HanoiRecursive
HanoiDynamic
LCSDynamic
LCSQuiz
dynamic.lcs