1. Mohammed I DAABO COURSE CODE: CSC 355 COURSE TITLE: Data Structures

2. The Need for Data Structures Data structures organize data  more efficient programs. More powerful computers  more complex applications. More complex applications demand more calculations. Complex computing tasks are unlike our everyday experience.

3. Organizing Data Any organization for a collection of records can be searched, processed in any order, or modified. The choice of data structure and algorithm can make the difference between a program running in a few seconds or many days.

4. Efficiency A solution is said to be efficient if it solves the problem within its resource constraints. Space Time The cost of a solution is the amount of resources that the solution consumes.

5. Selecting a Data Structure Select a data structure as follows: 1. Analyze the problem to determine the resource constraints a solution must meet. 2. Determine the basic operations that must be supported. Quantify the resource constraints for each operation. 3. Select the data structure that best meets these requirements.

6. Some Questions Are all data inserted into the data structure at the beginning, or are insertions interspersed with other operations? Can data be deleted? Are all data processed in some well-defined order, or is random access allowed?

7. Data Structure Philosophy Each data structure has costs and benefits. Rarely is one data structure better than another in all situations. A data structure requires: space for each data item it stores, time to perform each basic operation, programming effort.

8. Each problem has constraints on available space and time. Only after a careful analysis of problem characteristics can we know the best data structure for the task. Bank example: Start account: a few minutes Transactions: a few seconds Close account: overnight Data Structure Philosophy cont..

9. Goals of this Course 1. Reinforce the concept that costs and benefits exist for every data structure. 2. Learn the commonly used data structures. These form a programmer's basic data structure ``toolkit.'‘ 3. Understand how to measure the cost of a data structure or program. These techniques also allow you to judge the merits of new data structures that you or others might invent.

10. Objectives At the end of the study, the student should be able to:  Define a data structure.  Define basic elementary data structures (arrays, records sets and files).  Define an array as a data structure and how it is used to store a list of data items.  Understand sequential and link representations of: stacks, queues, tables, binary trees and graphs. Sorting and searching algorithms.  Understand data abstraction and its computer representation: concepts, data models, and levels of abstraction.  Define the Big O notation and Recursion  Distinguish between the name of an array and the names of the elements in an array.  Describe operations defined for an array.  Define a record as a data structure and how it is used to store attributes belonging to a single data element.  Distinguish between the name of a record and the names of its fields.  Define a linked list as a data structure and how it is implemented using pointers.  Understand the mechanism through which the nodes in an array are accessed.  Describe operations defined for a linked list.  Compare and contrast arrays, records, and linked lists.  Define the applications of arrays, records, and linked lists.

11. Abstract Data Types Abstract Data Type (ADT): a definition for a data type solely in terms of a set of values and a set of operations on that data type. Each ADT operation is defined by its inputs and outputs. Encapsulation: Hide implementation details.

12. Data Structure A data structure is the physical implementation of an ADT. Each operation associated with the ADT is implemented by one or more subroutines in the implementation. Data structure usually refers to an organization for data in main memory. File structure is an organization for data on peripheral storage, such as a disk drive.

13. Metaphors An ADT manages complexity through abstraction: metaphor. Hierarchies of labels Ex: transistors  gates  CPU. In a program, implement an ADT, then think only about the ADT, not its implementation.

14. Logical vs. Physical Form Data items have both a logical and a physical form. Logical form: definition of the data item within an ADT. Ex: Integers in mathematical sense: +, - Physical form: implementation of the data item within a data structure. Ex: 16/32 bit integers, overflow.

15. Data Structures A data structure is a scheme for organizing data in the memory of a computer. Some of the more commonly used data structures include lists, arrays, stacks, queues, heaps, trees, and graphs. Binary Tree

16. Data Structures The way in which the data is organized affects the performance of a program for different tasks. Computer programmers decide which data structures to use based on the nature of the data and the processes that need to be performed on that data. Binary Tree

17. Example: A Queue A queue is an example of commonly used simple data structure. A queue has beginning and end, called the front and back of the queue. Data enters the queue at one end and leaves at the other. Because of this, data exits the queue in the same order in which it enters the queue, like people in a checkout line at a supermarket.

18. Example: A Binary Tree A binary tree is another commonly used data structure. It is organized like an upside down tree. Each spot on the tree, called a node, holds an item of data along with a left pointer and a right pointer. Binary Tree

19. Example: A Binary Tree The pointers are lined up so that the structure forms the upside down tree, with a single node at the top, called the root node, and branches increasing on the left and right as you go down the tree. Binary Tree

20. Choosing Data Structures By comparing the queue with the binary tree, you can see how the structure of the data affects what can be done efficiently with the data.

21. Choosing Data Structures A queue is a good data structure to use for storing things that need to be kept in order, such as a set of documents waiting to be printed on a network printer..

22. Choosing Data Structures The jobs will be printed in the order in which they are received. Most network print servers maintain such a print queue..

23. Choosing Data Structures A binary tree is a good data structure to use for searching sorted data. The middle item from the list is stored in the root node, with lesser items to the left and greater items to the right.

24. Choosing Data Structures A search begins at the root. The computer either find the data, or moves left or right, depending on the value for which you are searching. Each move down the tree cuts the remaining data in half.

25. Choosing Data Structures Items can be located very quickly in a tree. Telephone directory assistance information is stored in a tree, so that a name and phone number can be found quickly.

26. Choosing Data Structures For some applications, a queue is the best data structure to use. For others, a binary tree is better. Programmers choose from among many data structures based on how the data will be used by the program.

27. Data Structures in Alice Alice has two built-in data structures that can be used to organize data, or to create other data structures: Lists Arrays

28. Lists A list is an ordered set of data. It is often used to store objects that are to be processed sequentially. A list can be used to create a queue.

29. Arrays An array is an indexed set of variables, such as dancer [1], dancer [2], dancer [3],… It is like a set of boxes that hold things. A list is a set of items. An array is a set of variables that each stores an item.

30. Arrays and Lists You can see the difference between arrays and lists when you delete items.

31. Arrays and Lists In a list, the missing spot is filled in when something is deleted.

32. Arrays and Lists In an array, an empty variable is left behind when something is deleted.

33. Lists A list is created in Alice by checking the make a list box when creating a new variable. Make a list box

34. Lists The For all in order and For all together tiles can be used to work with lists. They are at the bottom of the editor area.

35. Arrays Arrays can be created in a similar manner, but more often they are created using the array visualization object from the Alice local gallery. The Array Visualization object has special properties and methods for manipulating the elements in an array.

36. Arrays Alice has a set of built-in functions that can be performed on arrays.