Lecture Schedule Department of Computer Science Engineering & Information Technology Branch & Section : II B.Tech - I Sem & ECE Regulation : R16 Subject : Data structures Academic Year : 2017 -2018 Name of the Faculty : M. SWAPNA Course Objectives Solve problems using data structures such as linear lists, stacks, queues, hash tables Be familiar with advanced data structures such as balanced search trees, AVLTrees, and B Trees. Course Outcomes: Apply advanced data structure strategies for exploring complex data structures. • Compare and contrast various data structures and design techniques in the area of • Performance. Implement data structure algorithms through C • Incorporate data structures into the applications such as binary search trees, AVL and B Trees • Implement all data structures like stacks, queues, trees, lists and graphs and compare their • Performance and trade offs Topic No. of Classes Unit No Name of the Concept No Required UNIT-I: ARRAYS 1 1 Abstract Data Types 2 1 The Array as an Abstract Data Type 3 1 The Polynomial Abstract Data type Unit - 1 4 2 Polynomial Representation- Polynomial Addition 5 2 Spares Matrices, Introduction- Sparse Matrix Representation Transposing a Matrix- Matrix Multiplication, Representation of 6 4 Arrays. Total number of hours 11 Unit II: STACKS AND QUEUES – 1 3 The Stack Abstract Data Type 2 3 The Queue Abstract Data Type Unit 2 Evaluation of Expressions, Expression- Postfix Notation- Infix to 3 5 Postfix Total number of hours 11 Unit III : LINKED LISTS – 1 1 Single Linked List and Chains 2 1 Designing a Chain 3 2 Chain Manipulation Operations 4 2 Implementing Chains with Linked Lists Available Space Lists, Linked Stacks and Queues, Polynomials, 5 2 Polynomial Representation- Adding Polynomials Unit - 3 6 2 Circular List Representation of Polynomials, Equivalence Classes Matrices, Sparse Matrix Representation- Sparse Matrix Input- 7 3 Deleting a Sparse Matrix, Doubly Linked Lists Generalized Lists, Representation of Generalized Lists- Recursive 8 3 Algorithms for Lists- Reference Counts, Shared and Recursive Lists
Lecture Schedule Department of Computer Science Engineering & Information Technology Branch & Section : II B.Tech - I Sem & ECE Regulation : R16 Subject : Data structures Academic Year : 2017 -2018 Name of the Faculty : M. SWAPNA Course Objectives Solve problems using data structures such as linear lists, stacks, queues, hash tables Be familiar with advanced data structures such as balanced search trees, AVLTrees, and B Trees. Course Outcomes: • Apply advanced data structure strategies for exploring complex data structures. • Compare and contrast various data structures and design techniques in the area of Performance. • Implement data structure algorithms through C • Incorporate data structures into the applications such as binary search trees, AVL and B Trees • Implement all data structures like stacks, queues, trees, lists and graphs and compare their Performance and trade offs Unit No Topic No Name of the Concept No. of Classes Required UNIT-I: ARRAYS Unit - 1 1 Abstract Data Types 1 2 The Array as an Abstract Data Type 1 3 The Polynomial Abstract Data type 1 4 Polynomial Representation- Polynomial Addition 2 5 Spares Matrices, Introduction- Sparse Matrix Representation 2 6 Transposing a Matrix- Matrix Multiplication, Representation of Arrays. 4 Total number of hours 11 Unit – II: STACKS AND QUEUES Unit 2 1 The Stack Abstract Data Type 3 2 The Queue Abstract Data Type 3 3 Evaluation of Expressions, Expression- Postfix Notation- Infix to Postfix 5 Total number of hours 11 Unit – III : LINKED LISTS Unit - 3 1 Single Linked List and Chains 1 2 Designing a Chain 1 3 Chain Manipulation Operations 2 4 Implementing Chains with Linked Lists 2 5 Available Space Lists, Linked Stacks and Queues, Polynomials, Polynomial Representation- Adding Polynomials 2 6 Circular List Representation of Polynomials, Equivalence Classes 2 7 Matrices, Sparse Matrix Representation- Sparse Matrix Input- Deleting a Sparse Matrix, Doubly Linked Lists 3 8 Generalized Lists, Representation of Generalized Lists- Recursive Algorithms for Lists- Reference Counts, Shared and Recursive Lists 3
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