Agenda/topics:

  • Finish Sec 3.2 / 3.3:
    • review mathematical definitions (and intuitive understanding) of
      • “big-O” notation (upper bound)
      • “big-Ω” (big-Omega) notation (lower bound)
      • “big-Θ” (big-Theta) notation (both upper and lower bound)
      • “Big-O gives an upper bound on the growth of a function, while Big-Omega gives a lower bound. Big-Omega tells us that a function grows at least as fast as another.”
    • look at relevant video lectures/slides from Coursera Algorithms course
    • HW#4 exercises from Sec 3.2 & Sec 3.3

To Do:

  • hand in Quiz #3: take-home quiz re linear search
  • continue working on HW#4! due next Monday (May 16)

Boardshots:

TBA