A reading that introduces foundational data structures (such as arrays, linked lists, trees, and hash tables) and explains how they underpin real-world computing systems like social networks, file systems, and blockchains, serving as a conceptual starting point for learners entering the module.
Topics
This module covers 5 topics. Open a topic to see its subtopics and the materials made for it.
Module Content
12 items of 3 types: Topic Detail, Topic Videos, Readings. Your instructor made most of them with CourseBuilder+, a program that uses AI to draft course material; each type says how its items were made.
Topic Detail (5)
A detailed reading for each topic, covering its subtopics in order with explanations and examples — reading only, no videos (for the reading with videos, see Topic Detail with Video). Drafted with AI from the module's topics, subtopics and learning outcomes.
-
-
A reading that explains how blockchain technology is constructed from linked lists, cryptographic hash functions, and Merkle trees to create a tamper-resistant distributed ledger, helping learners understand the computer science principles behind blockchain architecture.
-
A reading that covers how digital currencies like Bitcoin and Ethereum use data structures and cryptography to achieve decentralized, tamper-resistant transaction records, enabling learners to understand the technical foundations of cryptocurrency systems.
-
A reading that explains how social networks are modeled as graphs, covers key graph data structures and traversal algorithms, and shows how these are applied to real-world problems such as friend recommendations and network analysis.
-
A reading that examines how complex software systems combine multiple data structures together, explains the reasoning behind those design choices, and analyzes the trade-offs and consequences of good versus poor structural decisions, helping learners think holistically about system design.
Topic Videos (6)
Videos for each topic: a short introduction to the topic, then up to three YouTube videos embedded, each with what it covers and why it is worth watching. The videos were found by an AI search of YouTube (well viewed, with captions where possible), and the page was written with AI.
-
A foundational reading that reframes hash tables, trees, and graphs as components that real systems layer and combine (such as a database pairing a hash index with a tree-based structure), which learners study first to shift from isolated implementations toward system-level design thinking.
-
A reading that dissects blockchain as a data structures problem — a linked list chained by cryptographic hash digests, with each block holding a Merkle tree of transactions summarized by a root — used by learners to connect pointer-based structures and hashing to real ledger design and tamper detection.
-
A reading that maps cryptocurrency components onto familiar structures, covering wallets as key-value stores, mempools as priority-ordered holding areas for pending transactions, and related node operations, so learners can analyze digital currency systems in terms of data structure choices.
-
A reading on modeling social platforms as graphs with users as vertices and relationships as edges, addressing questions like degrees of separation, centrality, and community structure, used by learners to apply traversal and graph-analysis techniques to network problems.
-
A capstone reading showing how blockchain nodes, payment networks, and social platforms stitch together hash tables, linked structures, trees, and graphs, helping learners reason about trade-offs when multiple structures must cooperate in one system.
-
A consolidated single-page version of the full module that compiles all five topic readings — foundations, blockchain architecture, digital currency, graphs and social networks, and combined systems — for continuous reading, review, or printing.
Readings (1)
Reading for this module: drafted with AI from the module's topics, or brought in from the course's own files.
-
A reading that examines how complex software systems combine multiple data structures together, explains the reasoning behind those design choices, and analyzes the trade-offs and consequences of good versus poor structural decisions, helping learners think holistically about system design.