1 COMP9007 – Algorithms Course page: + Blackboard link Lecturer: M.Reza Hoseiny M.Reza Hoseiny Level 4, Room 412, School of IT Tutors: Joseph Godbehere & Joel A. Gibson Practical Lab time: Tuesday 20: :00, SIT Lab 116 and 117

2 Course book: J. Kleinberg and E. Tardos Algorithm Design Addison-Wesley Outline: 12 lectures 4 assignments 4 quizzes Exam Tutorials: 11 tutorials (immediately after each lecture, except this lecture)

Aims of this unit ›This unit provides an introduction to the design and analysis of algorithms. Its main aims are -(i) learn how to develop algorithmic solutions to computational problem -(ii) develop understanding of algorithm efficiency. ›Assumes basic knowledge of discrete math -graphs -big O notation -proof techniques 3

4 Assessment: Quizzes 20% (4 assignments) Assignments 20% (4 assignments) Exam 60% (minimum 40% required to pass) Assignments submitted via Blackboard. Turnitin will be used to check every submission Collaboration: General ideas – Yes! Formulation and writing – No! Read Academic Dishonesty and Plagiarism.Academic Dishonesty and Plagiarism.

Assignments ›There will be 4 homework assignments ›The objective of these is to teach problem solving skills ›Each assignment represents 5% of your final mark. Late submissions will be penalized by 20% of the full marks per day. 5 For example, say you get 80% on your assignment: If submitted on time = 8.0 Late but within 24 hours = 8.0 * 0.80 = 6.4 Between 24 and 48 hours = 8.0 * 0.60 = 4.8 Between 48 and 72 hours = 8.0 *0.40 = 3.2 Between 72 and 96 hours = 8.0 *0.20 = 1.6 More than 96 hours = 8.0 * 0.0 = 0

Final exam ›The final will be 2.5 hours long. It will consist of 5-6 problems similar to those seen in the tutorials and assignments, plus one challenging problem ›The final will test your problem solving skills ›There is a 40% exam barrier ›The final exam represents 60% of your final mark ›Our advice is that you work hard on the assignments throughout the semester. It’s the best preparation for the final. 6

›Introduction - Julián Mestre Tutorials ›To get the most out of the tutorial, try to solve as many problems as you can before the tutorial. Your tutor is there to help you out if you get stuck, not to lecture. ›We will post solutions to selected exercises 7

Preliminary schedule ›Lecture 1 : Introduction, algorithms and complexity, and stable matching ›Lecture 2 : Algorithms analysis and data structures ›Lecture 3 : Recursive algorithms, Factorial, Greatest common divisor, Towers of Hanoi, Binary search, Order of execution ›Lecture 4 : Tree data structure, Balanced binary trees, Red–black tree, Complexity of Searching ›Lecture 5 : Graph algorithms: BFS and DFS ›Lecture 6 : Greedy algorithms: Interval scheduling, Kruskal's algorithm, Dijkstra's algorithm ›Lecture 7 : Divide and conquer: Recurrences, sorting, integer multiplication, selection ›Lecture 8 : Dynamic programming: weighted interval scheduling, longest increasing subsequence, knapsack and Bellman-Ford ›Lecture 9 : Dynamic programming cont. ›Lecture 10 : Network flows, maxflow mincut theorems, matching ›Lecture 11 : Max-flow and min-cut applications: Disjoint paths, scheduling and resource allocation problem, project section ›Lecture 12 : Advanced topic such as fixed parameter tractability, hashing, other complexity classes, ›Lecture 13 : Recap 8