Department of Computer Engineering Lesson Planning

Transcription

1 Department of omputer Engineering Lesson Planning Academic year 01-15(Even Semester) Term Duration: From 05/01/015 to 15/0/015 Pravin Hole 1. Name of the subject: Analysis Of Algorithm. lass/ Semester: SE OMP/VI -B 3. ourse Objective and Outcomes Part A: ourse Objectives: 1. To teach various problem solving methodology. To teach mathematical background for algorithm analysis and of various Strategies ( divide and conquer, Greedy method, Dynamic programming, Backtracking and Branch and bound ) 3. To teach different string matching algorithms.. To teach different sorting and search methods. Part- B: ourse Outcomes: 1. Students will be able to calculate time complexity and space complexity of an algorithm.. Students will be able to select appropriate problem solving strategies.( divide and conquer, Greedy method, Dynamic programming, Backtracking and Branch and bound) 3. Students will be able to analyze different string matching algorithms.. Students will be able to analyze different sorting and searching algorithms

2 Part -: Mapping of ourse Outcomes with Program Outcomes O\PO a b c d e f g h i j Students will be able to calculate time complexity and space complexity of an S S M M M S M S algorithm Students will be able to select appropriate problem solving strategies.( divide and conquer, Greedy method, Dynamic S S S S M S S M S programming, Backtracking and Branch and bound) Students will be able to analyze different string matching algorithms S S S S M S S M S Students will be able to analyze different sorting and searching algorithms S S S S M S S S S S indicates Strong and M indicates Moderate. Pre requisite for teaching the subject.: /++ Language., Data Structure, DIS. 5. Lecture wise Lesson planning Details Wee k No Lect. No. Ten. Date of cond. Unit/ hap No. Topics /01/15 1 Introduction to Analysis of Algorithm and Pos, os. 07/01/15 Decision and analysis fundamentals 3 08/01/15 Performance analysis,space and time complexity 09/01/15 Growth of function Big-Oh, Omega, theta notation 5 13/01/15 Mathematical background for algorithm analysis 6 1/01/15 Randomized and recursive algorithm. 7 15/01/15 Master Method T/ R Book To be used. T Mapping Actual ontent covered Methodo Remark of /O s logy used of Faculty 1, 8 16/01/15 Analysis of Insertion Sort 3 9 0/01/15 Analysis of Selection sort

3 10 1/01/15 Substitution Method 11 /01/15 Recursion Tree Method 1 3/01/15 Divide and onquer : General method 13 7/01/15 Binary search 1 8/01/15 Finding the min and max 15 9/01/15 Merge sort analysis /01/15 Quick sort analysis /0/15 Strassen s matrix multiplication. 18 0/0/15 The problem of multiplying long integers constructing Tennis tournament 19 05/0/15 3 Greedy Method : General method, Knapsack problem. 0 06/0/15 Minimum cost spanning treekruskal algo /0/15 Minimum cost spanning tree prim s algo 11/0/15 Single source shorted path. 3 1/0/15 Job sequencing with deadlines. 13/0/15 Optimal storage on tapes. 7 Unit Test /0/15 Single source shortest path 6 5/0/15 Dynamic Programming : General method 7 6/0/15 Multistage graphs 8 7/0/15 All pair shortest paths /03/15 single source shortest paths 30 0/03/15 Optimal binary search tree (OBST ) 31 05/03/15 0/1 knapsack 10 07/03/15 Technical Festivals to 1/03/ /03/15 Travelling salesman problem (TSP) T T T,,

4 33 18/03/15 Flow shop scheduling 3 19/03/15 5 Backtracking : General Method 35 0/03/15 8 queen problem (N-queen problem) 1 36 /03/15 Sum of subsets. 37 5/03/15 Graph coloring 38 6/03/15 6 String Matching Algorithms : Naïve string Matching Algorithms 39 7/03/15 Rabin Karp Algorithm 13 30/03/15 Unit test- to 01/0/ /0/15 String Matching with Finite automata 1 08/0/15 The knuth-morris-pratt (KMP) algorithm 09/0/15 Longest common subsequence (LS) problem T T /0/1 7 Branch and bound : The General method 15/0/15 15 puzzle 5 Travelling salesman problem (TSP) T Teaching Methodologies: DG class/board, Oral, PPT, GD, Assignment, QA, Live demo. No. of periods/hrs. required for planned Lectures = 5

5 Text(T) Books:. Ellis horowitz, sartaj Sahni, s. Rajsekaran. Fundamentals of computer algorithms University Press. T. T.H.coreman,.E. Leiserson,R.L. Rivest, and. Stein, Introduction to algorithms, nd edition, PHI publication Alfred v. Aho, John E. Hopcroft, Jeffrey D. Ullman, Data structures and Algorithm Pearson education, fourth impression 009 Reference(R) Book:. Michael Gooddrich & Roberto Tammassia, Algorithm design foundation, analysis and internet examples, Second edition, wiley student edition List of experiments Exp. No. Tentative Week 1 Week 1 Week 3 Week 3 Week 5 Week 5 6 Week 6 7 Week 8 8 Week 9 9 Week 11 Experiment Write a program for selection sort/ insertion sort. Write a program for binary search. Write a program for Merge sort. Write a program for Quick sort Write a program for Knapsack Problem. Write a program for Kruskal method Write a program for Prim s method. Write a program for OBST. Write a program for TSP. Type Actual Date of ompletion (Batch wise) Lang/ Tools used. Mapping Remar of O,PO ks by Faculty 1, 1, 1,

6 10 Week 1 11 Week 13 1 Week 1 Write a program for 8 queen problem. Write a program for LS. Write a program for 15 puzzle problem 3 7. List of Assignments (along with O and PO mapping): Que. No Question Os mapped POs mapped Assignment No. 1 Q.1 Describe the various asymptotic notations and uses. 1, a, b, c, d, f, g, h, i, Q. Study of recurrence relations and its use to derive the complexity of given problem., a, b, c, d, f, g, h, i, Q.3 explain greedy method and list applications., a, b, c, d, f, g, h, i, Assignment No. Q.1 Explain Travelling salesman problem (TSP) using dynamic programming. a, b, c, d, f, g, h, i, Q. Explain 15 puzzle problems. 3 a, b, c, d, f, g, h, i, Q.3 Describe knuth-morris-pratt (KMP) algorithm (string matching algorithm). a, b, c, d, f, g, h, i, 8. Observation and Remarks: Date of submission of plan: 01/01/015 Signature of Teacher Approved by AP and HOD Remarks by HOD:

7 Jan: Feb: March: April:

8 S0 Analysis of Algorithm Module Detailed ontent Introduction to analysis of algorithm Decision and analysis fundamentals Performance analysis, space and time complexity Growth of function Big Oh,Omega, Theta notation Mathematical background for algorithm analysis 1 Analysis of selection sort, insertion sort Randomized algorithms Recursive algorithms The substitution method Recursion tree method Master method Divide and onquer General method Binary search Finding minimum and maximum Merge sort analysis Quick sort analysis Strassen s matrix multiplication The problem of multiplying long integers constructing Tennis tournament Greedy Method General Method Knapsack problem Job sequencing with deadlines 3 Minimum cost spanning trees-kruskal and prim s algorithm Optimal storage on tapes Single source shortest path Dynamic Programming General Method Hrs

9 5 6 7 Multistage graphs all pair shortest path single source shortest path Optimal binary search tree 0/1 knapsack Travelling salesman problem Flow shop scheduling Backtracking General Method 8 queen problem( N-queen problem) Sum of subsets Graph coloring String Matching Algorithms The naïve string matching Algorithms The Rabin Karp algorithm String matching with finite automata The knuth-morris-pratt algorithm Longest common subsequence algorithm Branch and bound General method 15 puzzle problem Travelling salesman problem Termwork: Total experiments to be performed are 1 = ( ) 9 Experiments marked * are mandatory. For additional 3 experiments teacher can choose experiments from suggested list. The final certification and acceptance of term work ensures that satisfactory performance of laboratory work and minimum passing marks in term work. Termwork: 5 Marks ( total marks ) = 15 Marks Experiments + 05 Marks Assignment + 5 (Attendance (theory+practical)) Practical Exam will be based on above syllabus