Midterm Exam Study Guide: Java 9
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Questions and Answers

What are the two types of complexity discussed for assessing algorithms?

  • Time complexity and Computational complexity
  • Time complexity and Network complexity
  • Time complexity and Space complexity (correct)
  • Space complexity and Memory complexity

If a method's Big-O is stated as O(1) and it also contains a loop, what does this imply about the loop?

  • The loop runs proportionally to the input size.
  • The loop never executes.
  • The loop runs a fixed number of times regardless of input size. (correct)
  • The loop complexity cancels out other complexities in the method.

Which statement accurately describes 'best case', 'worst case', and 'average case' Big-O?

  • Best case describes scenarios with no constraints, worst case assumes maximum constraints, and average case uses random inputs.
  • Best case describes the least efficient algorithm execution, while worst and average cases provide other performance metrics.
  • Best case optimally utilizes resources, worst case results in resource exhaustion, and average case reflects typical scenarios.
  • Best case considers minimum resources, worst case considers maximum resources, and average case is the overall mean. (correct)

What is the formal definition of Big-O?

<p>T(n) is O(F(n)) if there are positive constants c and n0 such that, when n &gt;= n0, T(n) is less than or equal to c * F(n). (A)</p> Signup and view all the answers

When converting functions to Big-O, what is the Big-O of the expression $10n + O(lg(n))$?

<p>O(n) (D)</p> Signup and view all the answers

Which of the following data structures allows for dynamic resizing?

<p>Dynamic Array (B)</p> Signup and view all the answers

What is the primary focus of Section 20.1-20.2?

<p>Hashing Basics (D)</p> Signup and view all the answers

Which option describes a characteristic of a stack data structure?

<p>LIFO (Last In, First Out) principle (B)</p> Signup and view all the answers

Which of the following is NOT a common method of handling collisions in hashing?

<p>Direct Addressing (A)</p> Signup and view all the answers

In tree data structures, what is the purpose of tree traversals?

<p>To visit all nodes systematically (D)</p> Signup and view all the answers

What is a property of a binary tree?

<p>Each node can have at most two children (C)</p> Signup and view all the answers

What is the main concept behind priority queues?

<p>Elements are processed based on priority (C)</p> Signup and view all the answers

Which section discusses recursion in relation to trees?

<p>Section 7.1-7.3 (B)</p> Signup and view all the answers

What is required to bring to the exam in addition to a photo ID?

<p>One side of an 8.5&quot;x11&quot; sheet of handwritten notes (D)</p> Signup and view all the answers

Which coding language should students be comfortable coding in for the exam?

<p>Java 9 or higher (A)</p> Signup and view all the answers

What kind of questions might the non-coding portion of the exam include?

<p>Definitions and readings of code (D)</p> Signup and view all the answers

What should a student do if they do not have a suitable photo ID at the time of the exam?

<p>Take a picture at the exam location that will be required later (C)</p> Signup and view all the answers

What is one suggested method to prepare for the exam?

<p>Make up your own problems (D)</p> Signup and view all the answers

Which type of exam question format is not mentioned as being part of the exam?

<p>Essay (D)</p> Signup and view all the answers

Regarding algorithm analysis, what is expected of students?

<p>Understand the theorems without proof (C)</p> Signup and view all the answers

What is an essential resource mentioned for exam preparation?

<p>Relevant sections of the textbook (D)</p> Signup and view all the answers

Study Notes

Midterm Exam Study Guide

  • Exam Information:

    • The exam will test knowledge of definitions, terminology, code reading, and writing.
    • Expect True/False, multiple-choice, short answers, and coding questions in Java 9 or higher.
    • Code-reading questions may involve understanding code execution flow, determining the status of data structures, and predicting output.
  • Required Materials:

    • Photo ID (GMU ID preferred, but other forms like driver's license, state ID, passport are acceptable)
    • One-sided handwritten note sheet (8.5"x11") or a blank sheet of paper for scratch work
  • Preparation Strategy:

    • Review Examples/Exercises/Warm-ups questions from class
    • Practice exercises from the textbook
    • Create your own practice problems
  • Reading List for Review:

    • Big-O:
      • Chapter 5: Algorithm Analysis
      • Section 5.3: Understand the theorems, but not necessarily their proofs.
    • Lists:
      • Section 6.1-6.3, 6.5: General Lists
      • Chapter 15: Dynamic Array / Array List
      • Chapter 17: Linked List
    • Stacks / Queues / Priority Queues:
      • Section 6.6: Stack/Queue Concepts
      • Chapter 16.1-16.3: Stack/Queue Implementation
      • Section 6.9: Priority Queues
    • Hashing:
      • Section 20.1-20.2: Hashing Basics and Hash Functions
      • Section 20.5: Separate Chaining
      • Section 20.3-20.4: Open Addressing
      • Section 20.6-20.7: Comparisons and Applications
    • Trees:
      • Section 18.1: Tree Basics, Binary Trees
      • Section 7.1-7.3: Recursion
      • Section 18.3-18.4: Tree Recursions, Tree Traversals
  • Purpose of the Study Guide:

    • Self-assess your knowledge by identifying strengths and weaknesses.
    • Use provided resources (notes, textbook) to fill knowledge gaps and review forgotten details.
    • Judge your understanding by comparing your answers to past examples, assignments, and textbook exercises.
  • Importance of self-learning:

    • The study guide is not meant to provide answers, but to facilitate the learning process.
    • Focus on understanding the material, not just memorizing answers.
    • The provided resources offer a wealth of questions and answers. This guide helps you self-assess and identify areas for improvement.
  • Sample Review Questions (not exhaustive):

    Big-O

    • What are the two types of complexity for algorithm analysis?
    • Describe time/space complexity with a real-life example.
    • Convert functions into Big-O notation.
    • Compute time complexity and Big-O for your own code samples, explaining variables.
    • Describe a loop within a method with O(1) Big-O.
    • Explain the difference between best case, worst case, and average case Big-O.
    • Provide the formal definition of Big-O notation.

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Prepare for your Midterm Exam in Java 9 with this comprehensive study guide. It includes key exam information, required materials, and effective preparation strategies. Focus on algorithm analysis, code reading, and problem-solving to excel in your exam.

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