Course pages 2015–16
Mon-Wed-Fri 1000-1100 in Mill Lane Lecture Room 9, from Fri 2016-01-15 to Wed 2016-03-09 inclusive (12 with FMS + 12 with TMS = 24 lectures).
2016-02-12 Fri (5.1 Amortized Analysis)
Handout: pages 88-92
Distributed during the first lecture. It will be to your advantage to bring your handout to every lecture, together with a notebook with non-detachable pages and a few coloured pens. Further printed copies of the handout are available from the student administration office in the William Gates Building. An electronic copy is also available. Write to the author if you discover any errors and you'll be credited in the next edition.
A printed copy of the slides for Lectures 13-24 in condensed format has been distributed in Lecture 13. An electronic copy is also available. Write to the author if you discover any errors and you'll be credited.
Negative lines counted from bottom of page.
|34||3..4||One, like Quicksort itself, has linear cost in the average case, but has a quadratic worst-case cost.||One has linear cost in the average case but, like Quicksort itself, has a quadratic worst-case cost.||2016-01-21||Simone Teufel|
Please use the online Otter system, which is still somewhat experimental, and help us make it work for you by providing constructive feedback on how it could be improved. We are aware that there may be teething problems but please support us. To smooth out the transition, here is a legacy exercise sheet in pdf but new exercises will only be added to Otter from now on.
Past exam questions for Algorithms I, Algorithms II, Data Structures and Algorithms and Algorithms may be of interest. If you want to own this material rather than just memorize it, attempt the questions as seriously as if you were taking the exam yourself and do not open the solution notes until after having irrevocably committed (no more changes) to your own solution. The best students already understand the wisdom of this advice; for the others, yeah, the pressure is high, the temptation is strong, the flesh is weak...
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