The design, implementation, and analysis of abstract data types, data structures and their algorithms. Topics include: data and procedural abstraction, amortized data structures, trees and search ...

Learn when and how to use different data structures and their algorithms in your own code. This is harder as a student, as the problem assignments you'll work through just won't impart this knowledge.

Tour of the most important data structures, fundamental algorithms, and algorithm design techniques: lists, stacks, queues, dynamic arrays, hash tables, priority queues, disjoint set unions, binary ...

An introduction to the analysis and implementation of algorithms and data structures including linear data structures, trees, graphs, hash tables, searching algorithms, sorting algorithms, ...

This will also be an introduction to the role of randomization in algorithm design. Next, we will study hashtables: a highly useful data structure that allows for efficient search and retrieval from ...

“Hash tables are among the oldest data structures we have. And they’re still one of the most efficient ways to store data.” Yet open questions remain about how they work, he said. “This paper answers ...

But in a 1953 internal IBM paper, he proposed a new technique for storing and retrieving information that is now built into just about all computational systems: the hash table. Hash tables are a ...

The graph below shows the total number of publications each year in Bloom Filters and Hash Functions in Data Structures. References [1] eBF: an enhanced Bloom Filter for intrusion detection in IoT .

Tour of the most important data structures, fundamental algorithms, and algorithm design techniques: lists, stacks, queues, dynamic arrays, hash tables, heaps, priority queues, disjoint set unions, ...