Data Structures in the Wild is a deep dive into the kinds of data structures you won't find in a typical graduate course. These are the structures engineered for the real world—built to work well with modern CPUs, memory hierarchies, and diverse types of data. We’ll study how they achieve the right trade-offs between space and speed, and what it takes to make a data structure fast not just in theory, but in practice.
0.50
Students should have completed a course equivalent to CSC263H1 (Data Structures and Analysis), covering algorithm analysis (worst-case, average-case, amortized, expected), core data structures (e.g., graphs, dictionaries, priority queues) and their implementations (e.g., balanced trees, hashing, heaps). CSC373H1 (Algorithm Design) is strongly recommended for analytical maturity. CSC443H1 (Database System Technology) is also recommended, particularly for familiarity with storage systems and structures such as Bloom filters, LSM-trees, and B-trees.
