tools of structured analysis
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Prestige Institute
of
Management & Research, Indore
Tools Of Structured Analysis
Submitted To:
Prof. Bhavna Sharma
Submitted By:
Ankit Kumar Gupta
Rakesh Goliya
Sanjay Chouhan
Ish KumarMBA(FT) 2nd Sem. Sec. B
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In this session
Structured Analysis
Data Flow Diagram
Data Dictionary
Decision Trees
Decision Tables
InputProcess - Output
Hierarchy plus InputProcess - Output
Information System Planning Process
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Structured Analysis
The Word STRUCTURED In Structured Analysis Means:
The method attempt to structure the requirements determination process ,beginning with documentation of the existing system.
The process is organized in such a way that it attempts to include all relevant details
that describe the current system.
It is easy to verify when relevant details that describe the current system.
The identification of requirements will be similar among individual analysts and will
include the best solutions and strategies for systems development opportunities.
The working papers produced to document the existing and proposed systems are
effective communication devices.
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Meaning Of Structured Analysis
Structured analysis is a set of techniques and graphical tools that allow the
analyst to develop a new kind of system specification that are easily
understandable to the user.
Structured analysis is a development method for the analysis of existing
manual or automated systems, leading to the development of specifications
for a new or modified system. When systems analysts approach an unfamiliar
situation, there is always a question of where to begin the analysis. Structured
analysis allows the analysts to learn about a system or process(activity) in a
manageable and logical way while providing a basis for ensuring that pertinent
details do not get overlooked.
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Characteristics Of Structured
Analysis
Graphical with supporting text.
Allow system to be viewed in a top-down and
partitioned fashion.
Minimum redundancies.
Reader should be able to predict system
behavior.
Easy to understand by user.
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Components Of Structured
Analysis
Graphic Symbols:Icons and conventions for identifying and describing the components of a
system and the relationships among these components.
Data Dictionary:Descriptions of all data used in the system. Can be manual or automated (may
be included in a larger project dictionary that also contains descriptions
of processes making up the system.
Procedure and Process Description:
Formal statements using techniques and language that enable analysts todescribe important activities that make up the system.
Rules:Standards for describing and documenting the system correctly and
completely.
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Goals Of Structured Analysis
Improve Quality and reduce the risk of system
failure.
Establish concrete requirements specifications
and complete requirements documentation.
Focus on Reliability, Flexibility, and
Maintainability of system.
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Tools Of Structured Analysis
Data Flow Diagram
Data Dictionary
Decision Trees
Decision Tables
InputProcess - Output
Hierarchy plus InputProcess - Output
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Data Flow Diagrams
A graphic tool used to describe and analyze the movement of data through a
system - manual or automated including the process, stores, of data and delays
in the system.
A Data Flow Diagram (DFD) is a graphical representation normally designed by asystem analyst and is used as a reference point by the programmer which
portrays the "flow" of data through an information system. It is primarily used
for the visualization of data processing for the structured design of an
information system. It is common practice for a database designer to begin the
process by drawing a context-level DFD, which shows the interaction between
the system and outside entities.
A Data Flow Diagrams also known as a Bubble Chart, has the purpose of
clarifying system requirements and identifying major transformations that will
become programs in system design. A DFD consists of a series of bubbles joined
by lines. The bubbles represent data transformations and the lines represent
data flows in the system.
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Types Of Data Flow Diagrams
Physical Data Flow Diagrams
An implementation-dependent view of the current system, showing what
tasks are carried out and how they are performed.
Physical characteristics include:Name of the people.
Form and document names or numbers.
Names of Departments.
Logical Data Flow Diagrams
An implementations-independent view of a system, focusing on the flow of
data between processes without regard for the specific device, storage
locations or people in the system.
Example : computer , file cabinets etc.
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Data Flow Diagrams 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.
Open rectangle is a data store, or data at
rest, or a temporary repository of data
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Constructing a Data Flow
Diagram
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 eachword capitalized.
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Advantage & Disadvantages Of
DFD
Advantages:
Represents data flows.
May be used at high or low level of analysis.
Provides good system documentation.
Process bubbles can be hierarchically decomposed into sub-DFDs;
the inputs and outputs must match at all levels of decomposition, so
the design has validation.
Disadvantages:
Weak in its display of input and output details.
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Example Of Data Flow Diagram
General Model Of Publishers Present Ordering System
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DataDictionary
A Data Dictionary is a catalog - a repository of the elements in a system.
Although we give descriptive names to the data flows, process and data stores in a
DFD, it does not give the details. Hence to keep the details of the contents of data
flows, process and data stores we also require a Data Dictionary.
The three classes to be defined are:
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 locationwhere data structure are temporarily located.
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Continued
Data Dictionary
Data Elements
Data Structures
Data Flow Data Store
Smallest Unit of
Data
Group of Data
Elements
Groups of Data
Structures
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Advantages Of DataDictionar
Managing Detail:Large systems have huge volumes of data flowing through them in
the form of documents, reports and even conversations. Similarly , many
different activities take place that use existing data or create new details.
Quite frankly , it is impossible for system analysts to remember it all. So , weuse data dictionaries to store huge volume of data into the best organized
and most effective way.
Communicate Meaning:
Data Dictionaries assist in ensuring common meanings for systemelements and activities. Data dictionaries record additional details about the
data flow in a system so that all persons involved can quickly look up the
description of data flows, data stores or processes.
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Continued
Document System Features:Documenting the features of an information system is the third
reasons for using data dictionaries. Features include the parts or components
and the characteristics that distinguish each.
Facilitate Analysis:
The fourth reason for using data dictionaries is to determine
whether new features are needed in a system or whether changes of any
type are in order.
Locate Errors and Omissions:
Having system in a dictionary about these system characteristics
transactions , inquiries , data and capacity will tell you a great deal about a
system and allow you to evaluate it.
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Decision Trees
A Decision tree is a diagram that presents conditions and
actions sequentially and thus shows which conditions to
consider first, which second and so on. It is also a method of
showing the relationship of each condition and its permissible
actions.
A structure that can be used to divide up a large collection
of records into successively smaller sets of records by applying
a sequence of simple decision rules.
A decision tree model consists of a set of rules for dividing a
large heterogeneous population into smaller, more
homogeneous groups with respect to a particular target
variable.
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Advantages Of Decision Tree
Easy to understand.
Map nicely to a set of business rules.
Applied to real problems.
Make no prior assumptions about the data.
Able to process both numerical and categorical data.
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Disadvantages Of Decision Tree
Output attribute must be categorical.
Limited to one output attribute.
Decision tree algorithms are unstable.
Trees created from numeric datasets can be
complex.
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Example Of Decision Tree
Bookstores get a trade discount of 25%; for
orders from libraries and individuals, 5%
allowed on orders of 6-19 copies per booktitle; 10% on orders for 20-49 copies per
book title; 15% on orders for 50 copies ormore per book title.
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Type Of Customer DiscountSize Of Order
Discount
Policy
Bookstore
Libraries or
Individuals
6 or More
Less than 6
50 or More
20 - 49
6 - 19
Less than 6
25%
NIL
15%
10%
5%
NIL
Continued
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Decision Tables
A decision table is a table of contingencies for defining a problem and
actions to be taken. It is a single representation of the relationships
between conditions and actions.
Decision Tables are a graphic method for describing the logic of
decisions. The decision table lists a set of conditions plus a set ofactions and identifies different combinations of decision which lead to
different combinations of actions. These Different combinations are
termed rules. A decision table is simply a table showing the various
actions to be taken for different combinations of conditions.
Decision tables are a precise yet compact way to model complicated
logic. Decision tables, like if-then-else and switch-case statements,
associate conditions with actions to perform.
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Decision Tables Characteristics
The decision table is made up of four sections :
Conditions Statements:
The condition statements identifies the relevant condition.
Conditions Entries:Condition entries tell , which value , if any , applies for a particular
situation.
Action Statements:
Action Statements list the set of all steps that can be taken when acertain conditions occurs.
Action Entries:
Action Entries show what specific actions in the set to take when
selected conditions or combinations of conditions are true.
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Steps To Create a Decision Table
Determine the most relevant factors to be considered in
making a decision.
Determine the most feasible steps or activities under
varying conditions. This identifies the actions.
Study the combinations of conditions that are possible.
Fill the table with decision rules.
Mark action entries with X to signal actions to take ,
leave cell blank or mark with a dash to show that no action
applies to that row.
Examine the table for redundant rules or for
contradictions within rules.
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Advantages Of Decision Table
Decision tables are normally used in place of flowcharts because of the
following reason:
They provide concise descriptions of logically complex situations.
They are easier to draw and change than flowcharts.
They provide more compact documentation. A small table can replace
several pages of flowcharts.
It is also easier to follow a particular path down one column than throughseveral flowcharts pages.
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Disadvantages Of Decision Table
Large decision tables can become incomprehensible and difficult to
modify.
Flowcharts are better able to express the total sequence of events
needed to solve a problem.
Flowcharts are more familiar to, and are preferred by, many
programmers and beginners.
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Input Process Output Chart
The IPO diagram is a visual representation of a process or activity. It
lists input variables and output characteristics.
It is useful in defining a process and recognizing the input variables
and responses or outputs.
Input Process Output is what you put in, what you use both input and
output for, and also what you get out.
For example you might put in your monthly expenditure and income
(input) , then you can work out your average (process) and then
finally create a graph (output).
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Continued
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Hierarchy Plus Input Process
Output Chart
HIPO is a forms-driven technique in that standard forms are used to
document the information. It consists of a hierarchy chart and an
associated set of input/process/output charts.
HIPO captures the essence of top down decomposition; it describes
the data input and output from processes and define the data flow
composition.
A HIPO model consists of a hierarchy chart that graphically represents
the programs control structure and a set of IPO (Input-Process-
Output) charts that describe the inputs to, the outputs from, and the
functions (or processes) performed by each module on the hierarchy
chart.
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Steps To Create a HIPO Chart
Begin at the highest level of abstraction and define the inputs to the
system and the outputs from it in aggregate terms.
Identify the processing steps by those that convert input into
output.
Document each element using HIPO diagram notation and the
associated treelike structure.
Identify sub processes and their respective inputs and outputs.
Continue decomposition until the processes cannot be decomposed
any further.
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An overview diagram for the payroll processing module,''Calculate Each Employee's Pay,'' is shown in the Figure below.
Example..
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ThankYou
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