IT310 Java Support Site

Greetings Class!

I'm Kathy Marrs and I'll be your prof for the next several weeks as you learn about data structures and algorithms using Java in IT310 starting on 2013-02-28

Currently I own Marrs & Beyond Technologies, a Web design and consulting company that specializes in database driven Webs using Flash, AJAX, MySQL and PHP. I am working on my PhD (ABD) and have an MS and EdS in computing technology in education.

Now that you know a bit about me, here are some tips to help you ace this course:

1. Read the unit material before seminar each week. This gives you a head start on getting any answers you need and helps you participate more meaningfully.
2. Practice the techniques thoroughly before implementing them into your projects. This will help reveal any gaps in your understanding and minimize the need to troubleshoot later on.
3. Practice some more!
4. Manage your time wisely. Do not let yourself fall behind. Though it is human nature to procrastinate, remember this is about your future and lack of planning on your part does not make an emergency on mine! Be sure to fully understand the late policy outlined in the FAQs.
5. If you cannot attend seminar, it is your responsibility to review the recording so you don't miss vital information relevant to the unit topic and project expectations.

Now please take a few moments to introduce yourself to the class by posting a brief bio in Unit 1 discussion board. It would be helpful if you let me know of any specific learning goals you may have related to the subject and help your classmates learn of any interests you may have in common.

Also be sure to read the syllabus and any announcements I’ve posted. As you do, jot down any questions or concerns you have and bring them with you to seminar or post them in the Virtual Office. Remember, too, I'm only a few clicks away via email at kmarrs@kaplan.edu .

NOTE: If you do not receive a response to an email within 24 hours (except Saturday and Sunday) check your junk or spam folder. If you can't find it there, let me know in the Virtual Office.

I've designed this weekly newsletter to help you ACE the course! In it you'll find tips and other resources along with answers to frequently asked questions and best of all, specifics about how to maximize your points on your weekly projects.

The frequently asked questions (FAQs) to the right provide you with details on course expectations as well as what resources and software you need to succeed. The project due dates section helps you plan your schedule, so be sure to mark your calendars.

We'll be discussing all of these things in our first seminar, so be sure to bring your questions and concerns with you.  Hope you can all attend!

Warm Regards,
Kathy

Q: When are office hours?
A: Saturday & Sunday 3-4 PM ET

Q: What book do I need?
A: Data Structures and Algorithms in Java)
Author: Adam Drozdek
ISBN: 0-534-49252-5
Publisher: Cengage Learning

Q: What software do I need?
A: Java SDK Compiler - Free Download

An IDE, such as jGRASP, NetBeans, or Jcreator (you can download the SDK and NetBeans package from the above link).

Q: What is the late policy?
A: 1-7 days late = 20% penalty
8-14 days late = 30% penalty
No projects will be accepted after the last day of the term.

You MUST email me to notify me of any project submitted after the grading period for that unit has been completed. With rare exception, projects more than 14 days late will not be accepted.

Q: When are projects due?
A: See schedule below.

• Unit 1: 03-06-2013
• Unit 2: 03-13-2013
• Unit 3: 04-03-2013
• Unit 4: 04-03-2013
• Unit 5: 04-10-2013
• Unit 6: 04-17-2013
• Unit 7: 04-24-2013
• Unit 8: 05-01-2013
• Unit 9: 05-08-2013
• Unit 10: 05-15-2013

Q: How can I get help?
A: You have several options depending on what you need help with as follows:

1. Go to the Java Support Site (currently a work in progress). There you will ultimately find:
• Links to the weekly announcements, including newsletters and seminar recordings
• Seminar agendas
• Project demos and sample code
• Tutorials
• Help Ticket Application - use to get my help troubleshooting your code
2. Join me for office hours (see schedule above)
3. Post course related questions in the Virtual Office (I look there first and frequently)
4. For issues of a more personal nature, use email
5. If this isn't enough, check out Kaplan's Technology Center for tutoring options!

Greetings Class!

If you have taken a sneak preview at your reading assignment for this week, you already know that it's a DOOZY (I suspect it is for most of you anyway)! Please don't let it scare you and know that you don't have to do any math (leave that to the mathematicians - for now anyway). Your primary focus in this class needs to be on writing compilable code.

Of course you do need to understand the underlying point to doing complexity analysis and its importance when the projects you develop must handle large volumes of data. For now, let me simplify it to provide you with a sufficient foundation so you can move forward.

In a nutshell, typically there are many ways to solve a given problem, some more efficient than others. In the context of algorithms, two factors impact a program's performance: 1) time and 2) space. Time refers to the time it takes to perform the indicated steps, and space may be either space in RAM or disk space. If a program takes excessively long, or locks up due to lack of space, it will never be adopted by users (and can be quite embarrassing). For our purposes we're concerned only with time complexity for this unit (number of steps involved).

Consider an algorithm that all of you learned in grade school, namely basic multiplication, though you may not think of it as an algorithm. The greater the number of digits in the problem, the greater the number of steps it requires, and thus, the longer it takes to solve:

Now, assuming you memorized your multiplication tables like the dutiful student you were back then and didn't have to rely on fingers and toes, theoretically the second calculation took approximately 5 times longer to do than the first (including the addition) while the third calculation took approximately 10 times longer.

In terms of bits and bytes, time complexity is not just about math and applies equally to other characters and symbols (though the computer interprets them numerically). For example, the word "A" is 8 bits or 1 byte, while the word "antidisestablishmentarianism" consists of about 28 times more data and would take a correspondingly longer amount of time to process (note these times are not mathematically precise, but rather approximations).

While algorithms are generally designed to work with inputs of varying length, they also commonly must process entire data sets (e.g. arrays) and have special functionality (i.e. search, sort, loop, make decisions, etc). These conditions typically add to the time complexity by significantly increasing the growth rate and thus the resource requirements. They are also dependent on the power and efficiency of the platform on which they run. For all of these reasons, you should make it a point to familiarize yourself with typical use cases and the common algorithms that can handle the needs of your programs and use those that are best-suited to those needs.

Please see the FAQs and other resources on the support site for more!

Warm Regards,
Kathy

Q: What is Big-Oh?
A: In the context of algorithm analysis, you can think of big-oh (O) as the order of magnitude. Put simply, O refers to the smallest upper bound that a function will grow. Though not a complete list, common time complexities are stated as:

• O(1) - time is constant (no growth or number of operations is 1 regardless the value of n)
• O(n) - time is linear (grows with n when n doubles)
  • n = 1, number of operations = 1
  • n = 2, number of operations = 2
  • n = 4, number of operations = 4
• O(n²) - time is quadratic (grows twice as fast as n when n doubles)
  • n = 1, number of operations = 1
  • n = 2, number of operations = 4
  • n = 4, number of operations = 16
• O(n³) - time is cubic (grows three times as fast as n when n doubles)
  • n = 1, number of operations = 1
  • n = 2, number of operations = 8
  • n = 4, number of operations = 64

Q: What are common Java functions (algorithms) and their time complexity stated in Big-Oh?
A: Again an incomplete list, but some basic ones to get your started are:

• Loop that counts up to or down to n - O(n) or linear
• Linear search of an array, ArrayList, or LinkedList - O(n) or linear
• Search a hash table - O(1) or constant
• BubbleSort - O(n) or linear
• Selection Sort - O(n²) or quadratic

Q: What are common symbols used in algorithmic analysis?
A: Common symbols used in algorithmic analysis (besides O discussed above) include:

• Θ = theta (used to restrict the possible Ω lower bounds and O upper bounds)
• Ω = omega (big-omega refers to the largest lower bound of a function)
• Σ = sigma (sum)
• ms = millisecond (1/1000 of a second)
• µs or µsec = microsecond (1 millionth of a second)
• ns = nanosecond (1 billionth of a second)
• ∞ = infinity

Q: When is Unit 2 due?
A: 03-13-2013

Q: How can I get help?
A: You have several options depending on what you need help with as follows:

1. Go to the Java Support Site. There you will find:
• Links to the weekly announcements, including newsletters and seminar recordings
• Seminar agendas
• Project demos and sample code
• Tutorials
• Help Ticket Application - use to get my help troubleshooting your code
2. Join me for office hours
3. Post course related questions in the Virtual Office (I look there first and frequently)
4. For issues of a more personal nature, use email
5. If this isn't enough, check out Kaplan's Technology Center for tutoring options!

Greetings Class!

In this unit you'll learn about linked data structures and some of their applications. This technique along with recursion (covered in the next unit) relate to the idea of defining something in terms of itself.

Consider that a reference to one object can be stored in an instance variable of another object. You can build complex data structures by linking objects in such a way. Specifically, you'll learn to create a linked list, a common linked structure that consists of a chain of objects of the same type, linked together by pointers from one object to the next.

Linked lists are commonly constructed out of objects belonging to the node class, so you can think of such a structure as a collection of nodes each of which stores data and links to other nodes. There are several types (see FAQs for definitions):

• Singly linked list;
• Doubly linked list;
• Circular list;
• Skip list;
• Self-organizing list;
• Sparse table.

You'll try your hand at working with linked lists in this unit by creating a flight reservation application. I hope you enjoy the flight!

Warm Regards,
Kathy

Q: What is a singly linked list?
A: A linked list where each node in the list has a link only to its successor.

Q: What is a doubly linked list?
A: A linked list where each node in the list has two reference fields, on to the successor and one to the predecessor.

Q: What is a circular list?
A: A linked list where the nodes from a circle and each node has a successor (no null pointers).

Q: What is a skip list?
A: A skip list is a variant of the ordered linked list that makes a nonsequential search possible.

Q: What are the methods for ordering a self-organizing list?
A:

• Move-to-front method – after the desired element is located, put it at the beginning of the list
• Transpose method – after the desired element is located, swap it with its predecessor unless it is at the head of the list
• Count method – order the list by the number of times elements are being accessed
• Ordering method – order the list using certain criteria natural for the information under scrutiny
• Optimal static ordering - all the data are already ordered by the frequency of their occurrence in the body of data so that the list is used only for searching, not for inserting new items

Q: What is a sparse table?
A: A table that is populated sparsely by data and most of the cells are empty.

Q:When is Unit 3 due?
A: 04-03-2013

Q: How can I get help?
A: You have several options depending on what you need help with as follows:

1. Go to the Java Support Site. There you will find:
• Links to the weekly announcements, including newsletters and seminar recordings
• Seminar agendas
• Project demos and sample code
• Tutorials
• Help Ticket Application - use to get my help troubleshooting your code
2. Join me for office hours
3. Post course related questions in the Virtual Office (I look there first and frequently)
4. For issues of a more personal nature, use email
5. If this isn't enough, check out Kaplan's Technology Center for tutoring options!

Greetings Class!

In the last unit you learned how to implement linked lists, a special type of data structure useful for when your application needs to allow for constant-time insertions or deletions and sequential access. As you should know, linked lists are better than arrays when it's necessary to be able to add or delete from the list as doing so with the latter structure can impact memory requirements significantly.

This week we'll cover related data structures including stacks and queues. Stacks and queues are abstract data types (ADT), which refers to a set of possible values without specifying how those values will be represented and a set of possible operations, without specifying how they will be implemented. A program that depends only on the ADT definition can typically use different linked implementations interchangeably making the program easier to debug and maintain.

A classic example of use of stacks is the game "Towers of Hanoi", which consists of a stack of disks of various sizes, piled on a base in order of decreasing size. The object is to move the stack from one base to another and has two rules: Only one disk can be moved at a time and no disk can be placed on a smaller disk. A third base is provided for storing "spares."

You can think of a queue as standing in line at the checkout, or the playlist in your favorite media player or jukebox. The primary difference between a stack and a queue is that a stack uses a last-in first-out (LIFO) policy while a queue is first-in first-out (FIFO) - or better known to most people as first-come first-served.

For your project this week, you'll use the Java Stack class and a recursive algorithm to calculate the distance of the routes from one city to four other cities to visit. You'll use geocode lattitude and longitude data to determine the distances. Here a couple useful resources to help you:

http://geocoder.us/

http://www.melissadata.com/lookups/geocoder.asp

Warm Regards,
Kathy

Q: What is meant by a "recursive" subroutine?
A: A recursive subroutine is simply one that calls itself ether directly or through a chain of calls involving other subroutines.

Q: What are the three operations on a "stack?"
A: Push - adds the specified item to the top of the stack. Pop - removes the top item of the stack and returns it. isEmpty - a boolean value that returns true if there ar no items in the stack (TIP: before doing a push or pop, check if the stack is empty, because if it is you will get an error).

Q: What are queue operations?
A: Enqueue adds an item to the back of the line. Dequeue removes the item at the front of the line.

Q: When is Unit 4 due?
A: 04-03-2013

Q: How can I get help?
A: You have several options depending on what you need help with as follows:

1. Go to the Java Support Site. There you will find:
• Links to the weekly announcements, including newsletters and seminar recordings
• Seminar agendas
• Project demos and sample code
• Tutorials
• Help Ticket Application - use to get my help troubleshooting your code
2. Join me for office hours
3. Post course related questions in the Virtual Office (I look there first and frequently)
4. For issues of a more personal nature, use email
5. If this isn't enough, check out Kaplan's Technology Center for tutoring options!

Greetings Class!

Previously you learned about linked data structures and abstract data types including stacks and queues. In this unit you'll learn about binary trees, which are more complex yet very useful linked structures. You can envision such a structure by picturing an upside down tree where the root is at the top and each node has two pointers that branch to other nodes or children. With the exception of the root, which has no parent, every other node has exactly one parent and a parent that has no children is a leaf.

Java's TreeNode class defines the structure as being comprised of a root node, a left subtree (2,4,5), and a right subtree (3,6). I'm sure you can imagine how complex tree structures can become and it should be no surprise that developers commonly use recursive subroutines to process them.

You'll try your hand at creating a tree structure in this week's project by creating a ClubMember class that represents members of a fitness club. More specifically you'll use a binary search tree structure that stores and displays members by their ID number. Be sure to review the project details to know what you need to do to maximize your score and don't forget to check out the resources located in Unit 5. Have fun!

Warm Regards,
Kathy

Q: When would use of a breadth-first transversal of a tree structure be better than the more common depth-first transversal?
A: When the tree represents a command structure (e.g. who is in charge), or a timed game like chess. In the latter case, your time is better spent exploring your possible next move first and your opponent's responses rather than exploring one move infinitely before exploring another move.

Q: When is Unit 5 due?
A: 04-10-2013

Q: How can I get help?
A: You have several options depending on what you need help with as follows:

1. Go to the Java Support Site. There you will find:
• Links to the weekly announcements, including newsletters and seminar recordings
• Seminar agendas
• Project demos and sample code
• Tutorials
• Help Ticket Application - use to get my help troubleshooting your code
2. Join me for office hours
3. Post course related questions in the Virtual Office (I look there first and frequently)
4. For issues of a more personal nature, use email
5. If this isn't enough, check out Kaplan's Technology Center for tutoring options!

Greetings Class!

This week you'll study Dijkstra's algorithm, which is used to calculate the shortest route between a departure and a destination point no matter how many possible routes exist. In short, Dijkstra's algorithm (as you will no doubt discover on Wikipedia) is analogic to a road map that shows the possible routes and intersections between given start and end points.

In technical terms, intersections are known as vertices (see Java's Vertex class), roads, routes, or paths are called edges, while the map itself is a graph (the Vertex class is an extension of the Graph class). The calculated shortest path is referred to as the length, weight, cost, or distance of the traversal depending on your language perspective.

In addition to learning about how to implement Dijkstra's aglorithm, you'll learn some basics about using Swing, a popular Java GUI development environment. Hopefully you'll find it a refreshing change from working with raw code.

This and more in seminar!

Warm Regards,
Kathy

Q: When is Unit 6 due?
A: 04-17-2013

Q: How can I get help?
A: You have several options depending on what you need help with as follows:

1. Go to the Java Support Site. There you will find:
• Links to the weekly announcements, including newsletters and seminar recordings
• Seminar agendas
• Project demos and sample code
• Tutorials
• Help Ticket Application - use to get my help troubleshooting your code
2. Join me for office hours
3. Post course related questions in the Virtual Office (I look there first and frequently)
4. For issues of a more personal nature, use email
5. If this isn't enough, check out Kaplan's Technology Center for tutoring options!

Greetings Class!

In this unit you'll study common sorting algorithms. A simple Java implementation of a merge sort is the sort algorithm, which is a polymorphic algorithm that comes from the Collections class. It operates on a List as follows:

import jav.util.*;

public class Sort {
   public static void main(String[] args) {
      List<String> list = Arrays.asList(args);
      Collections.sort(list);
      System.out.println(list));
  }
}

I encourage you to feed it a few words and test it out.

For your project this week, you'll implement selection, insertion, bubble, quick, and merge sort, the goal being to compare the performance of each when sorting random integers on data sets that vary in size.

I'll demo one simple approach to get you started. As a special treat, I'll show you how to easily generate random numbers of any size set, write them to a text file and read the file contents into an array that I'm sure will spark some ideas. Happy sorting!

Warm Regards,
Kathy

Q: When is Unit 7 due?
A: 04-24-2013

Q: How can I get help?
A: You have several options depending on what you need help with as follows:

1. Go to the Java Support Site. There you will find:
• Links to the weekly announcements, including newsletters and seminar recordings
• Seminar agendas
• Project demos and sample code
• Tutorials
• Help Ticket Application - use to get my help troubleshooting your code
2. Join me for office hours
3. Post course related questions in the Virtual Office (I look there first and frequently)
4. For issues of a more personal nature, use email
5. If this isn't enough, check out Kaplan's Technology Center for tutoring options!

Greetings Class!

HashSets and HashMaps are implemented using a hash table data structure and are a great solution to solving search problems. Like a HashMap, a hash table stores key/value pairs. Use a HashSet as opposed to a TreeSet when the elements in the set are not comparable or when the order of the elements is unimportant.

Hash tables store their data in an array, however, the index, or hash code is computed from the key using the hash function.To find a particular key, you simply compute its hash code.

For your project this week, you'll implement a hash table and code methods to add, delete, and view elements in the table. As usual, I'll demo an approach to get you started. Have a great week!

Warm Regards,
Kathy

Q: When is Unit 8 due?
A: 10-18-2011

Q: How can I get help?
A: You have several options depending on what you need help with as follows:

1. Go to the Java Support Site. There you will find:
• Links to the weekly announcements, including newsletters and seminar recordings
• Seminar agendas
• Project demos and sample code
• Tutorials
• Help Ticket Application - use to get my help troubleshooting your code
2. Join me for office hours
3. Post course related questions in the Virtual Office (I look there first and frequently)
4. For issues of a more personal nature, use email
5. If this isn't enough, check out Kaplan's Technology Center for tutoring options!

Greetings Class!

This week involves an exploration of human expression and culture and specifically as it relates to how digital technology influences people from a social perspective. The digital age has resulted in the advent of social networking sites, blogs, wikis and other digital tools that has changed how people interact and how people have shifted from being consumers of information to creators who can share, remix, and distribute information along a myriad of channels.

Your goal this week is to write a research paper on the topic of human expression and culture from a digital perspective. Your paper should be in APA format and should synthesize your research and be supported by credible primary resources. Please see the project area on the support site for suggested topics.

Warm Regards,
Kathy

Q: When is Unit 9 due?
A: 05-08-2013

Q: How can I get help?
A: You have several options depending on what you need help with as follows:

1. Go to the Java Support Site. There you will find:
• Links to the weekly announcements, including newsletters and seminar recordings
• Seminar agendas
• Project demos and sample code
• Tutorials
• Help Ticket Application - use to get my help troubleshooting your code
2. Join me for office hours
3. Post course related questions in the Virtual Office (I look there first and frequently)
4. For issues of a more personal nature, use email
5. If this isn't enough, check out Kaplan's Technology Center for tutoring options!

Greetings Class!

This is the final unit - WOOHOO! It's been a pleasure helping all of you achieve your goals and I hope you found it a great educational experience.

Your goal this week is two-fold.

1. Develop an application of your choice (fully documented).
2. Write a paper describing what you've learned in the class and how you will use your Java skills

Please see the project area for details.

Best wishes to all of you!

Warm Regards,
Kathy

Q: When is Unit 10 due?
A: 05-15-2013

Q: How can I get help?
A: You have several options depending on what you need help with as follows:

1. Go to the Java Support Site. There you will find:
• Links to the weekly announcements, including newsletters and seminar recordings
• Seminar agendas
• Project demos and sample code
• Tutorials
• Help Ticket Application - use to get my help troubleshooting your code
2. Join me for office hours
3. Post course related questions in the Virtual Office (I look there first and frequently)
4. For issues of a more personal nature, use email
5. If this isn't enough, check out Kaplan's Technology Center for tutoring options!