Algorithm & Algorithm Analysis

Properties of algorithms, counting time units, best/average/worst case and asymptotic notation.

1. 2.1Algorithms & Their PropertiesAn algorithm is a finite, unambiguous sequence of steps that solves a problem. Learn the 11 properties every correct algorithm must have. 30 mineasy
2. 2.2Measuring EfficiencyEmpirical vs theoretical analysis, qualitative vs quantitative, the three classic avoidable inefficiencies, and the time–space trade-off. 35 mineasy
3. 2.3Counting Time UnitsTurn code into a formula T(n) using the instructor's counting rules. Loops become sums, and nested loops multiply. 50 minmedium
4. 2.4Best, Average & Worst CaseThe same algorithm can be fast or slow depending on the input. We analyse the best, average and worst case, and usually report the worst. 30 mineasy
5. 2.5Asymptotic Notation & Big-O ProofsO, Ω, Θ, o and ω describe how fast T(n) grows for large n. Learn the definitions, the order of growth, and how to prove f(n) = O(g(n)) by finding c and k. 60 minmedium