Data structures and algorithms are vital elements in many computing applications. When programmers design and build applications, they need to model the application data.

Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, ...

How to recognize and use array and list data structures in your Java programs. Which algorithms work best with different types of array and list data structures. Why some algorithms will work ...

Data structures and algorithms constitute the foundational pillars of computer science. They provide the systematic methods for organising, storing and manipulating data, and offer step-by-step ...

I see it time and again in Google interviews or new-grad hires: The way data structures and algorithms — among the most important subjects in a proper computer science curriculum — are learnt ...

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

Introduction to the fundamental principles of data structures and algorithms and their efficient implementation. Developing algorithmic thinking. Basic toolkit for the design and analysis of ...

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 ...

The rapid evolution of persistent memory (PM) technologies has spurred a significant shift in how data structures and algorithms are designed and implemented. Persistent memory, offering non ...

What makes some good software developers good at building large scale software but weak at data structures and algorithms? This question was originally answered on Quora by Gayle Laakmann McDowell.