Advanced Data Structures and Algorithms: 20132014
Lecturer 

Degrees 
Schedule S1(CS&P) — Computer Science and Philosophy Schedule S1 — Computer Science 
Term 
Hilary Term 2014 (16 lectures) 
Overview
This course builds on the firstyear Design and Analysis of Algorithms course. It introduces students to a number of highly efficient algorithms and data structures for fundamental computational problems across a variety of areas. Students are also introduced to techniques such as amortised complexity analysis. As in the firstyear course, the style of the presentation is rigorous but not formal.Learning outcomes
On successful completion of the course students will:
 Be able to understand and analyse some fundamental data structures, such as binary search trees, disjoint sets, and selfadjusting lists
 Understand the implementation and complexity analysis of fundamental algorithms such as RSA, primality testing, max flow, discrete Fourier transform
 Have been exposed to algorithmic issues in a variety of areas, including linear programming and gametheory
 Have some familiarity with randomised algorithms and approximation algorithms
Syllabus
 Amortised analysis
 Disjoint sets / unionfind
 Binary search trees (RedBlack trees)
 Splay trees
 Selfadjusting lists
 Number theoretic algorithms + RSA
 Primality testing
 Fast Fourier transform
 Linear programming
 Max flow in networks
 Randomized algorithms
 Approximation algorithms
 Stable matching and game theory
Reading list
The main text used in the course is:
 Thomas Cormen, Charles Leiserson, Ronald Rivest and Clifford Stein, Introduction to Algorithms, MIT Press, 2009 (third edition).
Other usefull textbooks that cover some of the material are
 S. Dasgupta, C.H. Papadimitriou, and U.V. Vazirani, Algorithms, McgrawHill, 2006.
 J. Kleinberg and E. Tardos, Algorithm Design, AddisonWesley, 2006.