CIS 3130 Data Structures

Basic Information


Container classes: their design, implementations, and applications. Sequences: vectors, linked lists, stacks, queues, deques, lists. Associative structures: sets, maps and their hash and tree underlying representations. Sorting and searching techniques. Collection frameworks and hierarchies.


Data Structures with C++ Using STL, 2nd ed., by - William H. Ford and William R. Topp, Prentice-Hall. (Example programs and PPT slides are available here)


There will be one homework assignment each week. Unless notified otherwise, the homework is due in one week after it is assigned. Please email your homework to cisc3130 (AT) Please write your name, student ID, and the number of the assignment in the Subject of the email. You are also encouraged to submit your homework on paper in addition to email submissions. Sample answers to the programming questions will be given and selected questions will be reviewed in class. There will be a one-point deduction for each missing homework or late submitted homework. The total deduction will not exceed 10 points.

Exams and Grading

There will be two tests, one midterm exam, and one final exam, all closed-book. Each test counts for 15%, the midterm 30%, and the final 40%.

Course Outline and Homework Assignments

  1. Introduction to Data Structures (What is this Book About? Abstract View of Data Structures. An ADT as a Class. Implementing C++ Classes. Declaring and Using Objects. Implementing a Class with Inline Code. Application Programming Interface(API). Strings.)
  2. Object Design Techniques (Software Design. Handling Runtime Errors. Object Composition. Operator Overloading.)
  3. Introduction to Algorithms (Selection Sort. Simple Search Algorithms. Analysis of Algorithms. Analyzing the Search Algorithms. Making Algorithms Generic. The Concept of Recursion. Problem Solving with Recursion.)
  4. The Vector Container (Overview of STL Container Classes. Template Classes. The Vector Class. Vector Applications.)
  5. Test-1 ( Sample )
  6. Pointers and Dynamic Memory (C++ Pointers. Dynamic Memory. Classes Using Dynamic Memory. Assignment and Initialization. The Minivector Class. The Matrix Class.)
  7. The List Container and Iterators (The List Container. Iterators. General List Insert And Erase Operations. Case Study: Graduation Lists.)
  8. Stacks (The Stack ADT. Recursive Code and the Runtime Stack. Stack Implementation. Postfix Expressions. Case Study: Infix Expression Evaluation.)
  9. Midterm (Sample)
  10. Queues and Priority Queues (The Queue ADT. The Radix Sort. Implementing the Miniqueue Class. Case Study: Time-Driven Simulation. Array Based Queue Implementation. Priority Queues.)
  11. Linked Lists (Linked List Nodes. Building Linked Lists. Handling The Back of the List. Implementing a Linked Queue. Doubly Linked Lists. Updating A Doubly Linked List. The Josephus Problem. The Minilist Class. Selecting a Sequence Container.)
  12. Binary Trees (Tree Structures. Binary Tree Nodes. Binary Tree Scan Algorithms. Using Tree Scan Algorithms. Binary Search Trees. Using Binary Search Trees. Implementing the Stree Class. The Stree Iterator (Optional).)
  13. Test-3
  14. Programming project #43 of Chapter 10, page 581-582.
  15. Associative Containers (Overview of Associative Containers. Sets. Maps. Multisets. Implementing Sets And Maps.)
  16. Advanced Associative Structures (Hashing. Designing Hash Functions. Designing Hash Tables. The Hash Class. Hash Table Performance. 2-3-4 Trees. Red-Black Trees. The Rbtree Class.)
  17. Inheritance and Abstract Classes (Inheritance in C++. The Graphics Hierarchy. The Graphics System. Safe Vectors. Ordered Lists. Polymorphism and Virtual Functions. Abstract Classes.)
  18. Heaps Binary Files and Bit Sets (Array Based Binary Trees. Heaps. Implementing a Priority Queue. Binary Files. Bitsets. Case Study: Huffman Compression.)
  19. Recursive Algorithms (Divide and Conquer Algorithms. Combinatorics. Dynamic Programming. Backtracking: The Eight-Queens Problem.)
  20. Graphs (Graph Terminology. The Graph Class. Graph Class Design. Graph Traversal Algorithms. Graph Traversal Applications. Graph Minimization Algorithms.)
  21. Final Exam (Sample)