This course introduces data structures and algorithms, focusing on practical implementation in Java.

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Java

Java-1

Data structures and algorithms are essential in computer science since they play a crucial role in efficient information retrieval and processing, dealing with files, storing contacts on phones, social networks and web searches.

In this course, you’ll learn about the array-based implementation of various linear data structures, stack, and queues. You’ll also learn about linked list-based implementation. Next, you’ll explore advanced data structures like skiplists and hashing. You’ll learn how to implement a variety of trees and graphs, and data structures related to bits of an integer. Toward the end of the course, you’ll learn the implementation of structures based on external storage.

After completing this course, you’ll be able to create reusable programs with template-based collections that can efficiently analyze how to optimize the storage and retrieval of very large amounts of data. Overall, this course will enhance your productivity and performance as a software developer.

Data Structures with Generic Types in Java

`BinaryHeap` is a type of binary search tree.

`BinaryHeap` can only be implemented using flexible binary trees.

The implementation of `BinaryHeap` using an array is the basis of one of the fastest known sorting algorithms.

`BinaryHeap` only supports the `add(x)` operation.

What is true about <code>BinaryHeap</code>?

Which data structure is a special kind of binary tree that can be thought of as a "disorganized pile"?

Which data structure is a special kind of binary tree that can be thought of as a “disorganized pile”?

The underlying binary tree in a `MeldableHeap` has a fixed shape like in `BinaryHeap`.

The `add(x)` operation in `MeldableHeap` takes $O(\log(n))$ expected time.

The `remove()` operation in `MeldableHeap` requires changing the shape of the underlying binary tree.

`MeldableHeap` cannot implement any operation other than `add(x)` and `remove()` in $O(\log(n))$ expected time.

What is true about <code>MeldableHeap</code>?

Meldable heaps are implemented using a binary tree structure.

Meldable heaps do not support the `merge()` operation.

Meldable heaps have a worst-case time complexity of $O(\log n)$ for the `add(x)` and `remove()` operations.

Meldable heaps are a specialized data structure used for sorting algorithms.

What is a key characteristic of meldable heaps?

What is a key characteristic of meldable heaps?

Test yourself on what you've learned about heaps.

Overview

Array-Based Lists

Linked Lists

Skiplists

Hash Tables

Binary Trees

Random Binary Search Trees

Scapegoat Trees

Red-Black Trees

Heaps

Sorting Algorithms

Graphs

Data Structures for Integers

External Memory Searching

Wrap Up

Quiz on Heaps