Learn how to evaluate algorithms by quantifying their time and space requirements using Big O, Theta, and Omega notations.

Understand arrays with their contiguous memory storage for fixed-size sequences, supporting constant-time indexing and linear-time insertion or deletion at arbitrary positions. Dynamic Arrays are also discussed at length.

Describe associative arrays that map keys to values via hash functions, enabling average-case constant-time insertions, deletions, and lookups. Learn about how hashing and compression functions work along with utilizing different techniques on how to handle key collisons.

Review techniques such as linear search and binary search for efficiently locating elements within data structures.

Examine algorithms like bubble sort, selection sort, insertion sort, merge sort, quicksort, and heapsort for ordering data based on various performance trade-offs.

Details storage and manipulation of character sequences, including operations for concatenation and substring search.

Learn to operate with singly, doubly, and circular linked lists for dynamic data sequences with constant-time insertions and deletions at known positions.

Use different variants of last-in, first-out (LIFO) structures for managing nested operations, function calls, and undo/redo mechanisms.

Understand first-in, first-out (FIFO) structures for scheduling tasks, buffering data streams, and breadth-first traversal.

Learn a different way to solve problems by utilizing functions that call themselves with smaller inputs, and gain a deeper insight into the analysis of recursion depth and base cases.

Learn different techniques to optimize recursive problems by storing and reusing solutions to overlapping subproblems to achieve polynomial-time solutions.

Explore different hierarchical node-based structures, including definitions, traversals (preorder, inorder, postorder), and common use cases.

Learn about binary trees that maintain the heap order, their variants, operations and how they’re used for efficient priority queue implementations.

Cover ordered binary trees supporting logarithmic-time search, insertion, and deletion in balanced scenarios.

Learn to use prefix trees for storing strings, enabling efficient retrieval and prefix-based operations.

Define vertex and edge representations for modeling networks, directed and undirected graphs, and common storage formats.

Have a deeper understanding of common graph traversal (DFS, BFS), shortest paths (Dijkstra’s, Bellman-Ford), topological sorting(Kahn’s Algorithm), and cycle finding algorithms.

Learn how to implement and use disjoint-set data structures for maintaining element partitions with near-constant-time union and find operations.

Explain and implement algorithms such as Kruskal’s and Prim’s for connecting all vertices with minimal total edge weight.

Describe depth-first search of solution spaces with pruning to solve constraint satisfaction problems.

Learn to utilize low-level operations (AND, OR, XOR, shifts) for efficient arithmetic and algorithmic optimizations.

The book prioritizes active learning as opposed to reading swaths of information. The reading material has been thoughtfully supplemented with interactive diagrams that allow for the reader to actively engage with the concepts discussed. Unlike regular computer science textbooks of the same vein, all of the code fragments and diagrams included in the book can be interacted with.

This book is perfect for several audiences: Students and self-learners can use it to understand fundamental concepts in an engaging manner. Those who are preparing for their techincal interviews, can benefit from a comprehensive but succinct treatment of all topics they might encounter during their interviews. The challenges and their corresponding interactive solution guides will also prove invaluable for those pressed for time. Finally, the book can be also used as a dependable reference for experienced developers and competitive programmers.

For optimal performance the following specifications are recommended:

MacOS : macOS 11.0 (Big Sur) or later, Intel Core i5 processor or Apple M1 chip and later, 8 GB RAM, 1 GB of available disk space.

Windows : Windows 10 (64-bit), Intel Core i5 (4th gen), 8 GB RAM, DirectX 11 compatible GPU,1 GB of available disk space

No. Once you've downloaded the book, you can access it offline!

Yes! Once you purchase the book, you'll have access to all future updates and revisions at no additional cost.

All revisions and updates will be sent to the email address associated with your purchase.

If you encounter any issues or errors in the book, you can submit it here. The bug fix will then be included in the next update, and will be sent to you once available.

Planned updates include additional solved problems and interactive content, dark mode, Improved Quality of life features like notetaking and bookmarking, support for more programming languages and more...