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Introduction to Data Structures and Algorithms Exam
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In computer science, a data structure is a data organization, management, and storage format that enables efficient access and modification, whereas, an algorithm is a finite sequence of well-defined, computer-implementable instructions, typically to solve a class of problems or to perform a computation. Algorithms are always unambiguous and are used as specifications for performing calculations, data processing, automated reasoning, and other tasks.

Good knowledge about the theory of Data Structures and Algorithms can not only help you have more confidence to enter Competitive Programming Contests, or Coding Interviews, but also help you solve many real-world challenges.

Rules:
- Maximum number of tests: 99
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Or practice with each objective below

Data Structures Fundamental

Weight: 20%

Questions (En):147

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Questions (Vi):69


  • Array List
  • Linked List
  • Stack
  • Queue
  • Heap
  • Tree
  • Hash Table
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Basic Algorithm Design Strategies

Weight: 20%

Questions (En):68

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Questions (Vi):0


  • Brute Force
  • Greedy
  • Recursion
  • Backtracking
  • Divide and Conquer
  • Branch and Bound
  • Dynamic Programming
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Analyzing Algorithms

Weight: 15%

Questions (En):43

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Questions (Vi):0


  • Computational Complexity
  • Space Complexity and Time Complexity
  • Big-O notation
  • Using Big-O notation to characterize the computational complexity of algorithms
  • Analyzing the run time of the algorithms
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Sorting Algorithms

Weight: 15%

Questions (En):106

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Questions (Vi):37


  • Bubble Sort
  • Insertion Sort
  • Selection Sort
  • Merge Sort
  • Heap Sort
  • Quick Sort
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Binary Tree

Weight: 15%

Questions (En):53

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Questions (Vi):0


  • Introduction to Binary Tree
  • Complete Binary Tree
  • Balanced Binary Tree
  • Binary Search Tree
  • Self-balancing Binary Search Tree
  • AVL Tree
  • Red-black tree
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Graph Data Structures and Algorithms

Weight: 15%

Questions (En):62

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Questions (Vi):0


  • Introduction to Graph
  • Graph Cycle
  • Connected Graph and Disconnected Graph
  • Directed graph and Undirected Graph
  • Weighted and Unweighted Graph
  • Graph Traversals
  • Depth-First Search vs Bread-First Search
  • Shortest paths between nodes in a Graph (Dijkstra Algorithms)
  • Minimum spanning tree for a weighted undirected graph (Prim Algorithms)
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