AlgoDamp;A_LectureNotes_W1说课.ppt

Design and Analysis of Algorithms;Course Overview;Administrative Details;Staff;Your background;You Are Supposed to Be;Course Representative and Tutors;Course Outline;Syllabus;Sorting ;Searching ;Syllabus;Textbook？;Reference Books;Languages (Lectures and Notes);Languages (Programming);Home Work and Assessment Overview;Assessment;General instructions for assignments;Assignment deadlines;Assignments: general advice;Getting to 1st base;More Legalities;Originality;Plagiarism;Anything left?;Design and Analysis of Algorithms;What is an algorithm ?;Algorithms;Features of Algorithms;Algorithms: Declarations;Algorithms: Decisions;Algorithms: Repetition;Algorithms: Procedures;Program = Algorithm + Data;Algorithm Classifications and Course Coverage ;Why analyzing an algorithm?;Why ;How to analyze an algorithm?;Analyzing an algorithm;Correctness;Correctness;Correctness;Correctness;Correctness;Example;Sequential Search ;Correctness of Sequential Search ;Correctness of Sequential Search ;Correctness of Sequential Search ;Correctness of Sequential Search ;Correctness of Sequential Search ;Correctness of Sequential Search ;;Correctness of Sequential Search ;Correctness of Sequential Search ;Correctness of Sequential Search ;Correctness of Sequential Search ;Correctness;Analyzing an algorithm;Amount of work down;Amount of work down;Amount of work down;Amount of work down;Amount of work down;Amount of work down;Amount of work down;Amount of work down;Amount of work down;Amount of work down;Time Complexity;Time Complexity;Time Complexity;Example;Example ;Example;Example;Example;Example;Comparing Algorithms on T(n);2n2 and 100n;Approximate Running Time ;O (Big-Oh) ;O (Big-Oh);For example;General Rules for calculating Big-oh;General Rules for calculating Big-oh;Tightness of Big-oh;Big-oh Informal Name ;Operations of Big-oh;Some Code Fragment Examples ;O(n);O(n2);O(log2n);O(n2);Asymptotic Complexity;Asymptotic Complexity;Asymptotic Complexity;Asymptotic Complexity;Asymptotic Com