Page 51 - R2017 Final_BE Biomedical Curriculum and Syllabus - REC
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Department of BME, REC

                   •  To apply the concepts of List ADT.
                   •  To analyze the concepts of tree and graph data structures.
                   •  To be able to incorporate various searching and sorting techniques in real time scenarios.

               UNIT I        BASIC DATA STRUCTURES                                                        9
               Introduction to Data Structure - Classes and Objects in Python – Stack – ADT - Stack Applications
               - Balancing symbols -Evaluating the Postfix expressions – Queue - ADT – Queue Applications -
               Dequeue - Circular Queue

               UNIT II       LINKED LIST                                                                  9
               Linked  List  Implementation  -  Singly  Linked  List-  Circular  Linked  List  -  Doubly  Linked  List  –  All
               operation (Insertion, Deletion, Merge, Traversal) - Applications of lists – Polynomial Manipulation

               UNIT III      TREES                                                                        9
               Basic Tree Terminologies- Binary Tree, Representation of Trees, Tree Traversal, Binary Search
               Tree – Operations, Implementation. Binary Heap- Properties, Heap Operations.

               UNIT IV       GRAPHS                                                                       9
               Graph  Terminologies,  Graph  ADT,  Traversal-  BFS,  DFS,  Directed  Acyclic  Graph-  Topological
               Sorting, Shortest Path- Dijkstra’s Algorithm.

               UNIT V        SEARCHING AND SORTING                                                        9
               Searching- Linear search, Binary search, Hashing- Hash function, Collision resolution techniques-
               Linear probing, Separate chaining. Sorting- Bubble sort, Selection sort, Insertion sort, Shell sort,
               Merge sort, Quick sort.

                                                                                        TOTAL: 45 PERIODS
               OUTCOMES:
               On completion of the course students will be able to
                   •  Analyze the various data structure concepts.
                   •  Apply data structures to solve various problems.
                   •  Understand non-linear data structures.
                   •  Correlate the uses of graphs in real life scenarios
                   •  Apply different Sorting, Searching and Hashing algorithms.

               TEXTBOOKS:
                   1.  Bradley N. Miller, Ranum,   . David L     "Problem Solving with Algorithms and Data Structures
                                                                    nd
                      Using Python", Franklin, Beedle & Associates ,2  Edition, 2013. [Units 1,3,5]
                   2.  Michael  T.  Goodrich , Roberto  Tamassia,       Michael  H.  Goldwasser,  "Data  Structures  and
                      Algorithms in Python" Wiley, 2013 .  [Units 2, 4]

               REFERENCES:
                   1.  Rance D. Necaise , "Data Structures and Algorithms using Python", John Wiley & Sons,
                       2011.
                   2.  David M.Reed and John Zelle, "Data Structures and Algorithms using Python and C++",
                       Franklin Beedle & Associates 2009.







               Curriculum and Syllabus | B.E Biomedical Engineering | R 2017                       Page 51
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