Data Structures Handout 1 & 2 Review
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Questions and Answers

What is a characteristic that distinguishes a priority queue from a standard queue?

  • Elements are processed based on a custom-defined order. (correct)
  • Elements are stored in a set.
  • Elements are processed based on their input time.
  • Elements are accessed in a linear fashion only.
  • Which of the following describes a heap structure?

  • A complete binary tree where each parent node's value is either higher or lower than its children. (correct)
  • A set of ordered pairs without any specific structure.
  • A collection of elements with no repeated values.
  • A complete binary tree with unordered parent-child relationships.
  • What defines the abstract approach of an Abstract Data Type (ADT)?

  • The internal structure is more important than the external operations.
  • The operations allowed are defined without regard to their implementation. (correct)
  • The focus is solely on the data storage mechanism.
  • The data structure implementation must be defined explicitly.
  • Which operation is NOT considered a main operation of an Abstract Data Type (ADT)?

    <p>Sorting</p> Signup and view all the answers

    What is NOT a characteristic of an algorithm as defined in the content?

    <p>Generality</p> Signup and view all the answers

    What characteristic defines a stack data structure?

    <p>It retrieves the last element added first.</p> Signup and view all the answers

    What is the primary feature that distinguishes dynamic programming from divide and conquer algorithms?

    <p>It actively reuses the results of overlapping subproblems.</p> Signup and view all the answers

    Which type of recursion is characterized by a function calling itself multiple times?

    <p>Binary recursion</p> Signup and view all the answers

    What is required for a recursive algorithm to function properly?

    <p>A base case to terminate the recursion.</p> Signup and view all the answers

    In the context of algorithm design paradigms, what does a greedy algorithm ensure?

    <p>It always chooses the optimal solution at each step.</p> Signup and view all the answers

    Study Notes

    Fundamentals of Data Structures and Algorithms

    • Data structures are specialized formats for storing and organizing data.
    • Algorithms provide a step-by-step sequence of instructions for problem-solving.

    Types of Data Structures

    • Linear Data Structures: Elements accessed sequentially.
    • Non-Linear Data Structures: Elements accessed non-sequentially.

    Abstract Data Types (ADT)

    • ADTs specify the logical view of data and operations allowed without implementation details.
    • Two parts of an ADT:
      • Public/External: Operations for adding, accessing, and removing data.
      • Private/Internal: Implementation details representing data structurally.

    Key Data Structures

    • Linked List: Stores elements as separate objects.
    • Stack: Last-In, First-Out (LIFO) structure.
    • Queue: First-In, First-Out (FIFO) structure.
    • Tree: Hierarchical structure represented graphically.
    • Set: Collection of unique elements.
    • Map: Set of ordered pairs, known as keys (identifiers) and values (content).
    • Graph: Consists of vertices (nodes) and edges (relations).

    Characteristics of an Algorithm

    • Finiteness: Must terminate after a specified number of steps.
    • Definiteness: Each instruction must be clear and unambiguous.
    • Input: Should have zero or more well-defined data before execution.
    • Output: Must produce one or more results related to the input.
    • Uniqueness: Each step's result depends on input and prior results.

    Recursive Algorithms

    • Recursive algorithms call themselves to solve problems.
    • Base Case: Condition for terminating recursion.
    • Change of State: Data modification during recursion.

    Types of Recursion

    • Linear Recursion: Function calls itself once (e.g., factorial).
    • Tail Recursion: Last operation is a recursive call (e.g., GCD).
    • Binary Recursion: Function calls itself twice (e.g., Fibonacci series).
    • Mutual Recursion: Functions call each other in pairs (e.g., even/odd checks).

    Recursion vs. Iteration

    • Recursion: A function calling itself requires a base case to terminate.
    • Iteration: Involves repeating instructions; terminates when conditions are met.
    • Recursive calls consume additional memory; iteration does not.
    • Infinite recursion can lead to memory issues, while infinite loops can occur without extra memory constraints.

    Algorithm Design Paradigms

    • Divide and Conquer: Problems are divided into smaller subproblems.
    • Greedy Algorithms: Optimal choices are made at each step.
    • Dynamic Programming: Subproblem results are reused for efficiency on overlapping problems.

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    Description

    This quiz encompasses key concepts from handouts 1 and 2 on Data Structures and Algorithms. It covers essential topics like priority queues and heaps, emphasizing their definitions and structures. Test your understanding of these fundamental data structures and their applications.

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