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Chapter : Tools of Structured Analysis, PPT, Semester, Engineering - Computer Science Engineering (CSE) PDF Download

Tools of Structured Analysis

 

 

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Structured Analysis

•It is a set of techniques and graphical tools that allow the analyst to develop a new kind of system that is understandable to the user

 

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Why do we use these tools?

•Use graphics whenever possible to help communicate better with the user.
•Differentiate between logical and physical system
•Build a logical system model to familiarize the user with system characteristics and interrelationships before implementation

 

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Data Flow Diagram

•It was first developed by Larry Constantine as a way of expressing system requirements in a graphical form.
•It is also known as Bubble Chart

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DFD Symbols

•Square defines a source or destination of data.
•Arrow identifies data flow, means the data in motion. It is a pipeline through which information flows.

 

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Continued…

•Circle or a bubble represents a process that transforms incoming data flow into outgoing data

Chapter : Tools of Structured Analysis, PPT, Semester, Engineering - Computer Science Engineering (CSE)

 

•Open rectangle is a data store, or data at rest, or a temporary repository of data

 

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Constructing a DFD

•Processes should be named and numbered for easy reference
•The direction of flow is from top to bottom and from left to right
•Data flow from the source to destination, although they may flow back to a source
•When a process is exploded into lower level details, they are numbered
•The names of data stores, sources, and destinations are written in capital letters. Process and data flow names have the first letter of each word capitalized

 

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Data Dictionary

•A structured place to keep details of the contents of data flows, processes, and data store.
•It is a structured repository of data about data.
•It is a set of definitions of all DFD elements

 

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Advantages of Data Dictionary

•Documentation- it is a valuable reference in any organization.
•It improves analyst/user communication by establishing consistent definitions of various elements, terms and procedures
•It is important step in building a database

 

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Items to be defined in Data Dictionary

•Data Elements- smallest unit of data that provides for no further decomposition.
For example: date consists of day, month and year
•Data Structure- a group of data elements handled as a unit.
For example: phone is a data structure consisting of four data elements: area-code-exchange-number-extension.
•Data Flows and Data Stores- data flows are data structures in motion, whereas data stores are data structures at rest. A data store is a location where data structures are temporarily located.

 

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Data Dictionary

Chapter : Tools of Structured Analysis, PPT, Semester, Engineering - Computer Science Engineering (CSE)

 

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Data Elements

•For e.g.
Author Name:
First
Middle
Last Alias
The Description of Data Element should include:
1.Name
2.Description &
3.An Alias (Synonym)

 

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Data Elements

•Whether or not Data Element has the following:
–A Different Name:
•For e.g. A Purchase Order may exist as Pur. Order, Purchase Ord., or P.O. We will record all these in Data Dictionary under Definition of Purchase Order.
–Usage Characteristics
•Range of Values or Frequency of use or both.
•2 types:
–Value within Range: For e.g. Payroll between 1000 and 10000 = Continuous Value.
–Specific Value: For e.g. Depts. In a Firm coded 100 (Accounting), 110 (HR), 111 ( Operations) etc.

 

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Data Elements

•Control Information
–Such as Source, Date of Origin, Users, or Access Authorization.
For e.g. Looking for Properties of Word Doc.
•Physical Location
–In terms of Record of File or Database.
For e.g. Where Storage is done C Drive, D Drive, CD ROM etc.

 

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Data Structures

•It is the Group of Elements .

For e.g.
Data Structures: Book Details
Data Elements: Author Name (M)
Title of the Book (M)
ISBN (Optional)
Publisher Name (M)
Quantity Ordered (M)
Some Element are Mandatory whereas others are Optional

 

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Data Flows and Data Stores

•Data Flows = Data Structures in Motion
•Data Stores = Data Structures at Rest
For e.g.
Data Flow/Store Comments
Book Details From ABC Book Store
Edition 4th
Quantity 10 Copies
Customer Details

 

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Decision Tree

•Once the data elements are defined in the data dictionary, we begin to focus on the processes.
•For example:
Bookstores get a trade discount of 25%; for orders from libraries and individuals, 5% allowed on orders of 6-19 copies per book title; 10% on orders for 20-49 copies per book title; 15% on orders for 50 copies or more per book title

 

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Structured English

•Structures English is like structured programming, it uses logical construction and sentences designed to carry out instructions
•Designs are made through IF, THEN, ELSE, and SO statements

 

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An Example

IF order is from Bookstore and-IF order is for 6 copies or more per book title
THEN: Discount is 25%
ELSE (order is for fewer than 6 copies per book title)
SO: no discount is allowed
ELSE (order is from libraries or individuals)

 

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Continued…

ELSE (order is from libraries or individuals)
SO-IF order is for 50 copies or more per book title
Discount is 15%
ELSE IF order is for 20 to 49 copies per book title
Discount is 10%
ELSE IF order is for 6 to 19 copies per book title
Discount is 5%
ELSE (order is for less than 6 copies per book order)
SO: no discount is allowed

 

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Decision Tables

•It is a table of possibilities foe defining a problem and the actions to be taken
•It is a single representation of the relationships between conditions and actions
•It consists of two parts: stub and entry
•The stub part is divided into an upper quadrant called the condition stub and a lower quadrant called the action stub
•The entry part is also divided into an upper quadrant, called the condition entry and a lower quadrant called the action entry

 

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Chapter : Tools of Structured Analysis, PPT, Semester, Engineering - Computer Science Engineering (CSE)

 

 

 

 

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FAQs on Chapter : Tools of Structured Analysis, PPT, Semester, Engineering - Computer Science Engineering (CSE)

1. What are the tools used in Structured Analysis?
Ans. The tools used in Structured Analysis include Data Flow Diagrams (DFDs), Entity Relationship Diagrams (ERDs), Data Dictionaries, Structure Charts, and Decision Trees. These tools help in understanding and representing the flow of data, the relationships between entities, the structure of the system, and the decision-making process.
2. How does a Data Flow Diagram (DFD) help in structured analysis?
Ans. A Data Flow Diagram (DFD) helps in structured analysis by visually representing the flow of data within a system. It shows how data moves from one process to another, how it is transformed, and how it interacts with external entities. DFDs provide a clear and concise representation of the system's functionality, making it easier to analyze, understand, and communicate.
3. What is the role of a Data Dictionary in structured analysis?
Ans. A Data Dictionary plays a crucial role in structured analysis by providing a centralized repository of data definitions and attributes. It documents the data elements used in the system, their descriptions, data types, and relationships. The Data Dictionary ensures consistency and accuracy in data usage throughout the system and serves as a reference for developers, analysts, and stakeholders.
4. How does a Structure Chart contribute to structured analysis?
Ans. A Structure Chart is a graphical representation of the system's structure and hierarchy. It shows the modules or components of the system, their relationships, and the flow of control between them. Structure Charts help in decomposing a complex system into manageable modules, facilitating modular design, code development, and testing. They also assist in identifying dependencies and understanding the overall system architecture.
5. What is the significance of Decision Trees in structured analysis?
Ans. Decision Trees are used in structured analysis to model decision-making processes within a system. They represent a series of decisions and their corresponding outcomes or actions. Decision Trees help in understanding the logic and conditions that govern the system's behavior, enabling effective analysis, design, and implementation. They are particularly useful for capturing complex decision rules and ensuring that all possible scenarios are considered.
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