Data Structures and Analysis
Algorithm analysis: worst-case, average-case, and amortized complexity. Expected worst-case complexity, randomized quicksort and selection. Standard abstract data types, such as graphs, dictionaries, priority queues, and disjoint sets. A variety of data structures for implementing these abstract data types, such as balanced search trees, hashing, heaps, and disjoint forests. Design and comparison of data structures. Introduction to lower bounds.
Prerequisites & course information
Prerequisite: CSC236H1 / CSC240H1 / CSC236H5 / CSCB36H3 ; STA237H1 / STA247H1 / STA255H1 / STA257H1 / STAB57H3 / STAB52H3 Prerequisite for Faculty of Applied Science and Engineering students: APS105H1 / APS106H1 / ESC180H1 ; ECE302H1 / STA286H1 / CHE223H1 / CME263H1 / MIE231H1 / MIE236H1 / MSE238H1 / ECE286H1; Prerequisite:; Exclusion: CSC265H1 , CSC263H5 , CSCB63H3 , MIE245H1; Exclusion:
Sources
- Course catalogue ↗2026-2027