- #Basics of java with data structures and algorithms how to#
- #Basics of java with data structures and algorithms code#
The Stack class implements a last-in-first-out (LIFO) stack of elements. The nice thing about using the Vector class is that you don't have to worry about setting it to a specific size upon creation it shrinks and grows automatically when necessary.įor more details about this class, check The Vector. Like an array, elements of a Vector object can be accessed via an index into the vector.
The Vector class is similar to a traditional Java array, except that it can grow as necessary to accommodate new elements. This class is very useful in cases where you need to keep up with a set of Boolean values you just assign a bit to each value and set or clear it as appropriate.įor more details about this class, check The BitSet. The BitSet class implements a group of bits or flags that can be set and cleared individually. To have more detail about this interface, check The Enumeration. The Enumeration interface defines a means to retrieve successive elements from a data structure.įor example, Enumeration defines a method called nextElement that is used to get the next element in a data structure that contains multiple elements. The Enumeration interface isn't itself a data structure, but it is very important within the context of other data structures. These data structures consist of the following interface and classes −Īll these classes are now legacy and Java-2 has introduced a new framework called Collections Framework, which is discussed in the next chapter. By completing this module, you will be able to implement both these data structures efficiently from scratch.The data structures provided by the Java utility package are very powerful and perform a wide range of functions.
#Basics of java with data structures and algorithms code#
We will see again how simple and natural ideas lead to an implementation that is both easy to code and very efficient. We will then switch to disjoint sets data structure that is used, for example, in dynamic graph connectivity and image processing. We will see that these implementations are based on a beautiful idea of storing a complete binary tree in an array that allows to implement all priority queue methods in just few lines of code. For this reason, priority queues have built-in implementations in many programming languages, including C++, Java, and Python. We start this module by considering priority queues which are used to efficiently schedule jobs, either in the context of a computer operating system or in real life, to sort huge files, which is the most important building block for any Big Data processing algorithm, and to efficiently compute shortest paths in graphs, which is a topic we will cover in our next course.
You will also learn how services like Dropbox manage to upload some large files instantly and to save a lot of storage space! What are good strategies to keep a binary tree balanced?
#Basics of java with data structures and algorithms how to#
How to implement a hash table so that the amortized running time of all operations is O(1) on average?Ĥ. How priority queues are implemented in C++, Java, and Python?ģ.
What is a good strategy of resizing a dynamic array?Ģ. You will also learn typical use cases for these data structures.Ī few examples of questions that we are going to cover in this class are the following:ġ. This will help you to understand what is going on inside a particular built-in implementation of a data structure and what to expect from it.
You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments. In this online course, we consider the common data structures that are used in various computational problems. A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently.
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