Course Objective:

This course is designed to provide a comprehensive understanding of Java Object Oriented programming concepts and techniques, to develop the ability to logically plan and develop programs using object-oriented programming, recursion, and data structures. Specific OOP topics in Java programming include Classes, Data Abstraction, Inheritance, and Polymorphism. Specific data structures include Linked Lists, Stacks, and Queues, Binary Search Trees, Hash Tables, Tree Sets, Tree Maps, and Hash Maps. Algorithm topics include Searching and Sorting Algorithms and recursion

Learning Outcomes:

• Students develop knowledge of basic data structures for storage and retrieval of ordered or unordered data.
  Data structures include: arrays, linked lists, binary trees, heaps, and hash tables.
• Students develop knowledge of applications of data structures including the ability to implement algorithms for the creation, insertion, deletion, searching, and sorting of each data structure.
• Students will develop applications using OOP.
• Students will implement requiring the use of data structures.

Textbooks etc.

1. Cay Horstmann Big Java, Late Objects, Edition 2, 2017
   publisher: Wiley
   ISBN: 9781119330455
   NOTE: If you wish to use another textbook, please receive approval beforehand. There are other textbooks that are suitable.
2. Eclipse, or an IDE of your choice.

Evaluation:

Test 1: 25%
Test 2: 25%
Test 3: 30%
Homework: 20%




NOTE:

Canvas is used solely as a repository for your submitted work.
Canvas should not be treated as gradesheet for the course.

I. Tests

Three tests will be given during the semester. Dates are shown on the schedule.

II. Homework and Self-Grading

A set of Java programs will be assigned almost every week.
These assignments are be available online at trishcornez.com (see the class schedule).



• Homework Assignments due date

  Homework assignments are due on Mondays by 9:00am (via Canvas).
  Submit your code in Microsoft Word or PDF format and include your execution results.
  Place your name prominently as a comment at the top of each program.
  Format your code and include clear explanations as comments.
  All program must be correct, readible, and written efficienly.
  Late homework will not be accepted.

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• Assignment Solutions and Do-overs

  Solutions to assigned programs will be posted to Canvas on Mondays by noon.
  Note: Solutions will only be provided for programming assignments. Answers to written questions can be found by reading the textbook.
  Students are expected to explore these solutions to gain a better understanding of
  writing efficient code, utilizing data structures and OOP effectively, and improving algorithms.
  After examining the posted solutions, you may correct and resubmit your homework on Wednesdays by 9:00am (via Canvas).

  Do NOT copy code from other students, other sources, or from posted solutions. All work MUST be individual. You are encouraged to clarify concepts and discuss possible approaches with other students in the class. The objective is always to learn the concepts. Keep in mind there is a strong correlation between students' exam scores and the effort put into homework. Cheating on homework or exams will be taken seriously.

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• Self-Grading Responsibilities

  Students are responsible for grading their own homework.
  Students will be asked to fully test their programs and check their execution results.
  An honor system will be used in all homework assignment to aid students in developing strong programming skills.
  The following Self-Grades Options should be entered into Canvas "do-over" for each assignment.
  
  Excellent Student explored, experimented, and fully solved the assignment using well-written algorithms.
  Good Student satisfied the assignment. Work was good, but could have been better.
  Average Student satisfied the assignment, but with problems.
  Poor Student turned in incomplete or poorly executed work.
  
  




Grading Scale:

100 - 93% 92-90% 89-87% 86-83%

4.0 3.7 3.3 3.0

82-80% 79-77% 76-73% 72-70%

2.7 2.3 2.0 1.7

69-67% 66-63% 62-60% below 59%

1.3 1.0 0.7 0.0




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Policies:

• Normal university policies concerning incomplete, etc.
• Make-up for tests requires either 2 weeks of advance notice (in case of planned absence), or a medical statement (in case of unforeseen problem).
• Credit will not be given to homework assignments turned in late.
• No extra credit work will be given during the semester.
• Any academic dishonesty will result in a failing grade.
• If a student has a disability that qualified for accommodations under the Americans with Disabilities Act and Section 504 of the Rehabilitation Act, she/she/they should contact Academic Success & Disability Services (ASDS). ASDS is located on the ground floor of the Armacost Library across from Human Resources and down the hall from the Jones Computer Center; their phone is 909-748-8069. The primary contact person is Amy Wilms.