Data Structures Dr. Saeed Arif Shah Data Structures & Algorithms •Schedule • When S • oWednesday, Thurday: 11:00 – 12:30 •Venue 1 oDCS&IT, King Abdullah Campus (KAC) 2• 3 Office Hours •0 Tuesday •1 : 09:00AM – 10:30AM Course Outline • Introduction • Data structures, Algorithms, Abstract Data Type (ADT), Complexity Analysis, Big-O notation. • Arrays • One dimensional arrays and their representation in memory, searching an unsorted array, binary search for sorted arrays, Two dimensional arrays, Multidimensional arrays • Linked Lists • Representation of linked list, operations on linked list, Types of linked lists, doubly linked list, circular linked list • Sorting Algorithms • Quadratic Sorting (Bubble sort, selection sort, insertion sort), Logarithmic Sorting (merge sort, quick sort) • Recursion and analyzing recursive algorithms Course Outline • The Stack • Operation performed on stacks, Stacks implementation (using arrays and linked lists), Applications of stacks, converting infix to postfix notations, Evaluating postfix expressions. • The Queue • Operations on queue, dequeuer, circular queue priority queues (linked and array implementations of queues), Applications of queues. • The Trees • Basic Terminologies, binary trees, binary tree representation, operations on binary tree, traversing binary trees recursively, traversing binary tree non-recursively, binary search trees, balanced trees. • Graphs • Basic terminologies, representation of graph, operations on graph, breadth first search, depth first search, minimum spanning tree, shortest Path • Hashing and Indexing • General idea, hash function, separate chaining, hash tables with linked lisk, rehashing. Recommended Books • Text Book • Data Structures, Algorithms And Applications In C++, By Sartaj Sahni, 2nd Edition • Reference Books • Data Structures and Algorithm Analysis in C++ by Mark Allen Weiss, 4th Edition. • Data Structures using C++, By D. S. Malik, 2nd Edition. • Principles of Data Structures Using C and C++ By Vinu V Das • Schaums Outline Of Data Structures with C++ by J R Hubbard What is Data? oA collection of facts from which a conclusion may be drawn oExample: •Temperature is 35 degrees Celsius •Conclusion: It is HOT! •Types of data: oTextual: for example • » Your name (Muhammad) oNumeric: for example • » Your id (090254) oAudio: for example, • » Your voice What are Data Type? • Data Type: • Built-in construct of any programming language to manipulate “basic types of data” • Basic Types of Data • Character • Integer • Real or Floating point number • Example (Data Type): • int, char, double etc ; What are Data Structures? • Data Structure: • A particular way of storing and organizing data in a computer so that it can be used efficiently • It is a group of data elements stored together under one name • It is also referred as “Abstract Data Type (ADT)” • Example: • An array of integers • int examGrades[30]; Importance of Data Structures • Goal: • We need to organize data • For what purpose? • To facilitate efficient storage of data • retrieval of data • manipulation of data • Design Issue: • The challenge is to select the most appropriate data structure for the problem • Such is one of the motivations for this course List of Data Structures C • Arrays • Linked List • Stack • Queue • Tree Classification of Data Structures • Based on Existence: • Physical data structures • Actually, meant for storing the data in the memory. • Can be created independently • Array • Linked List • Logical data structures • Performing operations stored data • Can’t be created independently • stack, queues, trees, graphs Classification of Data Structures • Based on Memory Allocation: • Static (or fixed sized) data structures • Such as arrays • int marks [30] • Dynamic data structures (change size as needed) • Such as Linked Lists Classification of Data Structures • Based on Representation • Linear data structures • Arrays • Linked lists • Stack • Queues • Non-linear data structures • Trees • Graphs Operations on Data Structures • Traversing • Accessing/visiting each data element exactly once so that certain items in the data may be processed • Searching • Finding the location of a given data element (key) in the structure • Insertion: • Adding a new data element to the structure • Deletion • Removing a data element from the structure • Sorting • Arrange the data elements in some logical fashion • ascending or descending • Merging • Combining data elements form two or more data structures into one
