Lecture notes Data structures and Algorithm (EKT 224)

Introduction 1.1 History of Algorithms 1.2 Definition, Structure and Properties of Algorithms 1.3 Development of an Algorithm 1.4 Data Structures and Algorithms 1.5 Data Structure- Definition and Classification 2. Analysis of Algorithms 2.1. Efficiency of Algorithms 2.2. Apriori Analysis 2.3. Asymptotic Notations 2.4. Time Complexity of an Algorithm using O (big-O) notation 2.5. Polynomial Vs Exponential Algorithms 2.6. Average, Best and Worst Case Complexities 2.7. Analyzing Recursive Programs 3. Arrays 3.1. Introduction 3.2. Array Operations 3.3. Number of Elements in an Array 3.4. Representation of Arrays in Memory 3.5. Applications 4. Stacks 4.1. Introduction 4.2. Stack Operations 4.3. Applications 5. Queues 5.1. Introduction 5.2. Operation of Queues 5.3. Circular Queues 5.4. Other types of Queues 5.5. Applications 6. Linked Lists 6.1. Introduction 6.2. Singly Linked Lists 6.3. Circular Linked Lists 6.4. Doubly Linked Lists 6.5. Operations on Linked Stack and Linked Queue 6.6. Dynamic Memory Management and Linked Stacks 6.7. Implementation of Linked Representations 6.8. Applications 7. Trees and Binary Trees 7.1. Introduction 7.2. Trees: Definition and Basic Terminologies 7.3. Representation of Trees 7.4. Binary Trees: Basic Terminologies and typesPage 4 7.5. Representation of Binary Tree 7.6. Binary Tree Traversals 7.7. Applications 8. Graphs 8.1. Introduction 8.2. Definition and Basic Terminologies 8.3. Representation of Graphs 8.4. Graph Traversal 8.5. Applications 9. Hash Table 9.1. Introduction 9.2. Structure 9.3. Functions 9.4. Linear open addressing 9.5. Chaining 9.6. Applications 10. Searching 10.1. Introduction 10.2. Linear Search 10.3. Transpose sequential Search 10.4. Interpolation Search 10.5. Binary Search 10.6. Other Search Techniques 11. Sorting (2 weeks ) 11.1. Introduction 11.2. Bubble Sort 11.3. Insertion Sort 11.4. Selection Sort 11.5. Merge Sort 11.6. Quick Sort 11.7. Other Sorting Techniques