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

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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 Python

A `SLList` can only implement `Stack` operations, not `Queue` operations.

A `SLList` can implement both `Stack` and (FIFO) `Queue` operations in constant time per operation.

A `SLList` can implement only `Deque` operations.

A `SLList` cannot implement any of the `List` interface operations in constant time.

Which statement about a `SLList` having `head` and `tail` is *true*?

Which statement about a <code>SLList</code> having <code>head</code> and <code>tail</code> is true?

The use of a `dummy` node eliminates the need to handle special cases for adding or removing elements at the beginning or end of the list.

Finding the node with a particular index in a `DLList` with a `dummy` node can be done in $O(1 + min\{i, n - i\})$ time.

A `DLList` with a `dummy` node allows for nodes to be linked in a cycle, with the `dummy` node acting as both the first and last node in the list.

The `getNode()` method in a `DLList` with a `dummy` node always starts at the `head` of the list and works forward to find the node with the given index.

Which statement about a `DLList` with a `dummy` node is _false_?

Which statement about a <code>DLList</code> with a <code>dummy</code> node is false?

Each node in a `SEList` stores only one element.

A `SEList` is parameterized by a block size $b$, and each individual node stores a block that can hold up to $b - 1$ elements.

The data structure used for `Deque` operations in each block of a `SEList` is an `ArrayDeque`.

The space-overhead of a `SEList` can approach the lower bound of $\sqrt n$ by choosing a value of $b$ within a constant factor of $\sqrt n$.

Which statement is *true* about `SEList`, a space-efficient linked list?

Which statement is true about <code>SEList</code>, a space-efficient linked list?

Finding the block containing a particular element is similar to a singly linked list.

Each block in a `SEList` contains at most $b-1$ elements.

The algorithm to find an element with index `i` in a `SEList` takes $O(1+min\{i,n-i\}/b)$ time.

The time to locate an item with index `i` in a `SEList` is dominated by the time it takes to add an element to the list.

Which statement is *true* about finding an element in a `SEList`?

Which statement is true about finding an element in a <code>SEList</code>?

What is the time complexity of the `add(i, x)` and `remove(i)` operations in an `SEList` data structure with block size `b`?

What is the time complexity of the <code>add(i, x)</code> and <code>remove(i)</code> operations in an <code>SEList</code> data structure with block size <code>b</code>?

Test yourself on what you've learned about linked lists.

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 Linked Lists