# Analysis of Algorithms. D & A of Algorithms Design & Analysis of Algorithms ?

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• Slide 1
• Analysis of Algorithms
• Slide 2
• D & A of Algorithms Design & Analysis of Algorithms ?
• Slide 3
• CMSC 441 Section 0201 Design & Analysis of Algorithms Instructor: Dr. Lomonaco Grading Policy: Course Grade = (25% Ex1)+(25% Ex2)+(25% Hwk)+ (25% Fin) Course Grade = (25% Ex1)+(25% Ex2)+(25% Hwk)+ (25% Fin) There are no make-up exams !!! There are no make-up exams !!! Hwk Avg for wkly hwk = Lowest 1 (or 2) hwks dropped, and remaining hwks averaged Hwk Avg for wkly hwk = Lowest 1 (or 2) hwks dropped, and remaining hwks averaged Late homework will not be accepted !!! Late homework will not be accepted !!! http://www.csee.umbc.edu/~lomonaco/
• Slide 4
• The Big Picture The Software Challenge: Create even larger more efficient algorithms: Design & Analysis of Algorithms Create even larger more efficient algorithms: Design & Analysis of Algorithms Create programs that meet design specs: Program Verification Create programs that meet design specs: Program Verification Create readable & understandable programs: Program Documentation Create readable & understandable programs: Program Documentation Create platform independent programs: Portability Create platform independent programs: Portability
• Slide 5
• The Big Picture High Level Mathematics High Level Mathematics High Level Physics High Level Physics High Level Analytical Thinking High Level Analytical Thinking To be and to stay competitive, we need learn to think ahead of the curve This means continually learning how to use more sophisticated approaches to the software challenge. Those who choose not to continue learning new more sophisticated approaches to programming will quickly become obsolete, and be easily Out Sourced !!! Shudder !!!
• Slide 6
• Course Objectives Design efficient algorithms Design efficient algorithms Analyze the efficiency of algorithms Analyze the efficiency of algorithms Our course objectives are to learn how to: Consider an algorithm A for solving a problem P : Algorithm A InputOutput Problem Instance Solution How efficient is the algorithm ? How efficient is the algorithm ? What do we mean by efficiency ? What do we mean by efficiency ?
• Slide 7
• Asymptotic Notation Asymptotic Upper Bound Big-O Notation Asymptotic Lower Bound Big- Notation Tight Asymptotic Bound Big- Notation