Course Syllabus

CS 4349.003 Advanced algorithm design and analysis; Spring 2018; Tue/Thu 1:00-2:15 PM; ECSS 2.412

Class URL: https://www.utdallas.edu/~rbk/teach/2018/4349.html


Professor Contact Information

Balaji Raghavachari; (972) 883-2136; rbk@utdallas.edu; ECSS 4.225

Office hours: Tue/Thu 11:20-11:55 AM, 2:20-3:00 PM. Wed 9:00 AM - 1:00 PM, or by appointment.


Course Pre-requisites, Co-requisites, and/or Other Restrictions

CS 3345 or equivalent (Data structures and algorithms): Analysis of algorithms. Stacks, queues, and trees, including B-trees. Heaps, hashing, and advanced sorting techniques. Disjoint sets and graphs.


Course Description

Topics: Algorithm design techniques: divide-and-conquer, dynamic programming, greedy algorithms; Sorting and searching; Graph algorithms; Running time analysis; Proofs of correctness.

* Running time analysis of algorithms, order notation

* Mathematical background: sums of sequences, Logs and polynomials, recurrences, amortized cost

* Correctness of algorithms: loop invariants, proof by induction

* Divide and conquer: merge/quick sort, binary search, kth smallest and median, convex hull, n-bit multiplication

* Counting, radix, bucket sorts, sorting lower bound

* Dynamic programming: rod cutting, matrix-chain multiplication, activity selection, LCS, optimal binary search tree

* Greedy algorithms: activity selection, Huffman coding

* Graphs, encoding of graphs, DFS and its applications

* Minimum spanning trees: implementation and correctness of Prim/Kruskal

* Shortest paths: BFS, Bellman-Ford, DAG-shortest path, Dijkstra, Floyd-Warshall

* Max-flow problem: Ford-Fulkerson, Edmonds-Karp, max-flow min-cut theorem

* NP-completeness.


Student Learning Objectives/Outcomes

Study efficient algorithms for a number of fundamental problems, learn techniques for designing algorithms, prove correctness and analyze running times.

  1. 1.Ability to understand asymptotic notations, recurrences, algorithm analysis

  2. 2.Ability to understand divide and conquer algorithms

  3. 3.Ability to understand greedy algorithms

  4. 4.Ability to understand dynamic programming algorithms

  5. 5.Ability to understand graph algorithms


Required Textbooks and Materials

Introduction to Algorithms, 3rd ed., Cormen, Leiserson, Rivest, and Stein. MIT Press.


Assignments & Academic Calendar

Homework assignments and programming projects will be assigned almost every week.

Quiz 1: Feb 6 (Tue); Mid-term Exam: Feb 22 (Thu); Quiz 2: Mar 22 (Thu); Final exam: May 3 (Thu), 2:00-4:00 PM.


Grading Policy:

Score minimum requirement in each category to earn a grade: (1) weighted average of exams/quizzes, (2) homework assignments, (3) programming projects. Cut off scores:

A+:

90%

A:

87.5%

A-:

82.5%

B+:

77.5%

B:

70%

B-:

65%

C+:

62.5%

C:

60%

C-:

57.5%

D+:

55%

D:

52.5%

D-:

50%


Course & Instructor Policies

See also UTD's policies at https://go.utdallas.edu/syllabus-policies