We have been talking about Object-oriented programming since the start of this semester. Over the time, with lots of examples and practice on it, I feel much more comfortable with this way of coding. Actually it is just what it sounds like. Object oriented programming (OOP) is based on creating on objects and writing methods to create data structures that store and manipulate data. With OOP, you are not limited to default object types built in to a language, for instance, lists, strings in python. It has a clear structure, make it possible for everyone to understand what your code does and use them on their own, which makes our real-world jobs more efficient.
Until this week, we have been told 3 types of Abstract Data Types. And here I will give a brief summary on each of them.
1. stack
Until this week, we have been told 3 types of Abstract Data Types. And here I will give a brief summary on each of them.
1. stack
A stack contains items of various sorts. It stores data in an order that new
items are pushed on to the top of the stack, and items may only be removed from the top of the
stack. Thus, an abbreviation LIFO which stands for ''last in first out'' is used to describe it. When the stack is empty, you can no longer ''pop'' it. With stack, we can check for balanced parentheses which was displayed during lecture(refer to class notes), and the application gives a better understanding on the implementation and uses of stack. Basically, a stack is like a pile of books, every time you add or remove one from the top, and you can tell what the top item is and how big the entire stack is.
2. queue
In comparison with stack, queue stores data in the way of ''first in first out'' (FIFO).
We practiced implementing queue in the lab. Similar to stack, queue has methods of adding and removing items called ''enqueue'' and ''dequeue''.
And it also has a basic method to check if queue is empty. Besides these
three basic methods, queue could be implemented with other methods depending on the specific situation.
3. tree
Tree is a great way of manipulating data, it can represent hierarchical relationships. A tree is a set of nodes connected by edges. There are children nodes and parent nodes. Each node has exactly one parent, except the root. In this picture, root is the node containing value 1. And
node with no children is called a leaf. As is shown, the node containing value of 6 is a leaf.
Trees are made of recursions! A tree contains several sub-trees within it, round and round, just like recursion.To illustrate, in the picture shown in the right, we have a tree with the root 1, but we also have a subtree with root 2, and so on and forth. For me, one important thing is to understand the basic structure, never overthink about it! Sometimes drawing a picture helps a lot.
2. queue
In comparison with stack, queue stores data in the way of ''first in first out'' (FIFO). We practiced implementing queue in the lab. Similar to stack, queue has methods of adding and removing items called ''enqueue'' and ''dequeue''.
And it also has a basic method to check if queue is empty. Besides these
three basic methods, queue could be implemented with other methods depending on the specific situation.
3. tree
Tree is a great way of manipulating data, it can represent hierarchical relationships. A tree is a set of nodes connected by edges. There are children nodes and parent nodes. Each node has exactly one parent, except the root. In this picture, root is the node containing value 1. And
node with no children is called a leaf. As is shown, the node containing value of 6 is a leaf.
Trees are made of recursions! A tree contains several sub-trees within it, round and round, just like recursion.To illustrate, in the picture shown in the right, we have a tree with the root 1, but we also have a subtree with root 2, and so on and forth. For me, one important thing is to understand the basic structure, never overthink about it! Sometimes drawing a picture helps a lot.
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