Reflection Time!!

Wow. CSC148 was nothing like I expected, what started off as fun, turned into a nightmare right after the first test. I knew coming into the course that it would be a bit challenging, but never did I think I would be as challenged as I am feeling now. Looking back into my first week SLOG, I thought the course would be simple, fun and challenging in a sense that after a couple hours of focusing I could accomplish any challenge. But it turns out that computer science just isn't the minor for me.

   It's not that I don't like the course, or I don't like the challenge, its just that I can't think like a computer scientist. I can't see a line of code and create a mental object in my mind, and show what happens to it as you create methods or variables. And since I was taking these courses on the basis of a minor, I can now focus on my Rotman specialist.
 
  But with the horizon just around the corner showing up in the form of a final exam, whether I like the course or not, it's go time and I have to refocus on the concepts to get a good grade, and I have learned more in this course than I ever thought I would coming into the course.

Week 9 Impressions

Binary Search Trees were the topic for the 9th week of classes. Since we were already introduced to tree's, the topic of a binary search tree wasn't too complex of an idea. It actually proved to be an efficient way to search for a value within a tree.

       I know it is irrelevant to post it within a slog, but I feel if anyone is reading this and doesn't know what a Binary Search Tree is now is your chance to learn it in the simplest way. A binary search tree is Tree, and when you have to draw out a search tree it will look in the same shape as a regular tree. What makes a binary search tree so unique is the fact that the node values it contains are sorted with the larger nodes on the right, and the smaller nodes on the left.

   As Professor Horton mentioned in lectures, a binary search tree is faster when you have to look for a value because your first step of comparing whether the root value is greater than the value you are looking for cuts the number of nodes to search in half.
 
   I think a binary search tree is only a fast and efficient if it is balanced, since if there are no numbers smaller than the root, and the value you are looking for is at the bottom of the tree, then you basically have to search the entire tree and every node within it.

   SOOO that was week 9 for me, and it was a pretty laid back week once you understood the main concept of the week.

Week 8 Impressions - LinkedLists

Week 8 was different, if I had to summarize it in one word. LinkedLists was the main topic of the week, and after finishing trees and nodes, and connected forms of data, a LinkedList seemed along the same line of a thought process. The main idea of the LinkedList isn't that complicated when you simply imagine it, but the algorithm was a bit confusing to completely understand. I still have a couple questions...but now that the TA's are on strike Google will have to pass as a sufficient teacher.

I think after looking at the code a couple of times, and tracing through it, I can look at the code for a LinkedList and understand it, but implementing it in my code is a bitttttt further down the path. Professor Horton has done a great job so far when she is explaining the self.front and self.back concepts, and it's much more clear now than it was when they concepts were first presented.

To me a LinkedList is like a group of people holding hands to form a line. With the first person's arm connecting it themselves to the one before, and the person's body being the value, where the person's other arm is what connects him to the last person. You can also see that the first person is equivalent to self.front, and the last person is self.back.

WELLLLL, that was my impression for the 8th week of class, and it was tough, but I can't wait for the next couple of weeks of classes.

Saying NOPE to NODES

Are all Nodes trees? Or are all Trees Nodes? In my opinion--and I'm usually right-- I think all Tree's are nodes, since a tree is a series of nodes connect through a path to a root, wouldn't that simply mean that all tree's are nodes? Week 7 was ALL NODES ALL CLASS, it took a couple minutes to actually realize that nodes were a part of trees, but once I've figured that out, it actually became a bit easier. Another big challenge I faced in class over the week was learning that a node wasn't treated like a Tree, even though both trees and nodes had a left and right child, trees don't necessarily access them, unlike a node. Nodes have present values for the left and right child- usually preset to None. 

And if week 7 wasn't challenging enough with all the new information on nodes thrown at us, we were working on the new concepts of Nodes in our lab as well, and we awesome as my TA is at helping us, its still a tough concept to entirely understand it in just 2 classes and 1 lab. I know this is one of my shorter SLOGs but week 7 wasn't too long of a week for me to rant/reflect upon.