Syllabus

The topics to be covered in the lecture can be divided into several parts (depending on the time and progress):

• Part 1: Basic Concepts and Abstract Data Types
• What are data structures?
• Why do we study data structures?
• What is an abstract data type(ADT)?
• Relationship between data structures and ADTs
• Classification of data structures
• Algorithms and performance analysis
• Complexity and asymptotic notations
• Part 2: OO and C++ Review
• Object orientation
• Object-oriented programming(OOP)
• C++ review
• C++ templates
• Data structures in C++
• OOP with C++
• Part 3: Linear Data Structures
• Arrays and strings
• Array ADT
• Polynomial ADT
• Sparse matrices
• String ADT
• Stacks and queues
• Stack ADT
• Queue ADT
• Maze
• Expression Evaluation
• Linked lists
• Singly linked lists
• Circular lists
• Doubly linked lists
• Lists applications
• Part 4: Non-linear Data Structures
• Trees
• Tree ADT
• Binary trees
• Threaded binary trees
• Heaps
• Binary search trees
• Selection trees
• Graphs
• Graph ADT
• Graph operations
• Minimum cost spanning trees
• Shortest paths and transitive closure
• Graph search
• Part 5: Sorting
• Internal sorting (insertion sort, quick sort, merge sort, heap sort, radix sort)
• External sorting
• Part 6: Hashing
• Associative arrays
• Hash functions
• Hash tables and dictionaries
• Part 7: Priority Queues**
• Priority queues
• Double-ended priority queues
• Part 8: Search Structures**
• AVL trees
• Red-black trees
• B-Trees
• B+-Trees
• Digital search structures
• Part 9: Advanced Data Structures**
• Advanced lists
• Trie
• Data structures for spatiotemporal data
• Data structures for big data
• Data structures for streaming data
• Data structures for social network analysis(SNA)