CS 473/573 - Algorithms I

Due to covid-19 outbreak, lectures and exams will be online. Please refer to the Distance Learning and Assessment Guidelines shared by the Instructor for any course information. Do not use this web page any longer!

Semester: Spring, 2019-2020
Text Book: T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, Introduction to Algorithms, Mit Press and McGraw-Hill, 2009.
Instructor: Ugur Dogrusoz (EA522)
Assistants: M. Ozan Karsavuran (EA505), Nabil Abubaker (EA505), Mustafa Duymus (EA507)
Syllabus: 2020 Spring Syllabus

Lecture Hours:
Section 1: Classroom: B-Z05 Wednesday 08:40-10:30, Friday 10:40-12:30
Section 2: Classroom: B-Z02 Tuesday 10:40-12:30, Friday 08:40-10:30

Office Hours:
Ugur Dogrusoz: Tuesday 09:30-10:30, Wednesday 10:30-11:30 Weekly Schedule
Ozan Karsavuan: Wednesday 13:30 - 14:30
Nabil Abubaker: Thursday 13:30 - 14:30
Mustafa Duymus: Monday 14:00 - 15:00

Check this page regularly for announcements.

Exams:
Note that all midweek exams are open book,
but all other resources are strictly forbidden (including course slides and personal notes).
Your books must be CLEAN. Proctors will check your books during the exam and
ANY written notes will be considered as cheating.
If your book is old (bought or borrowed from another person), it is your responsibility
to check every page of the book and clean any existing notes before entering the midweek exam.
Midterm and final exams are closed books/slides.

Midweek exam #2: March 2, 17:40
Coverage:
Divide and Conquer Design Paradigm (Lecture 04)
Quicksort (Lecture 05)
Analysis of Quicksort (Lecture 06a)
Randomized Quicksort (Lecture 06b)
Exam rooms according to last name:
EE-03: Abdulkhaligli - Kaynak
EE-04: Kiliç - Zerener

Midweek Exam #1: Febuary 17, 17:40 - 19:20
Coverage:
Introduction to Analysis of Algorithms (Lecture 01)
Asymptotic Notation (Lecture 02)
Solving Recurrences (Lecture 03)

TOPICS & SLIDES

Lecture 01: Introduction: analysing algorithms, designing algorithms. (pdf) (pptx)
Lecture 02: Asymptotic Notation. (pdf) (pptx)
Lecture 03: Solving Recurrences. (pdf) (pptx)
Lecture 04: Divide and Conquer Design Paradigm. (pdf) (pptx)
Lecture 05: Quicksort. (pdf) (pptx)
Lecture 06a: Analysis of Quicksort. (pdf) (pptx)
Lecture 06b: Randomized Quicksort. (pdf) (pptx)
Lecture 07: Medians and Order Statistics. (pdf) (pptx)
Lecture 08: Heapsort. (pdf) (pptx)
Lecture 09: Sorting in Linear Time. (pdf) (pptx)
Lecture 10: Dynamic Programming. (pdf) (pptx)
Lecture 11: Greedy Algorithms. (pdf) (pptx)
Lecture 12a: Amortized Analysis. (pdf) (pptx)
Lecture 12b: Dynamic Tables. (pdf) (pptx)
Extra examples for dynamic programming. (pdf) (pptx)
Lecture 12: Graphs. (pdf) (ppt)
Lecture 13: BFS. (pdf) (ppt)
Lecture 14: DFS. (pdf) (ppt)
Lecture 14b: Topological Sort. (pdf) (ppt)
Lecture 15: SCC. (pdf) (ppt)
Lecture 16: MST. (pdf) (ppt)
Lecture 17: Kruskal Prim. (pdf) (ppt)
Lecture 18: Disjoint Set Operations. (pdf) (ppt)

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