Wednesday, 10 July 2013

System Analysis – SRS, DFD, DD & Decision t ables

A data flow diagram (DFD) is a graphical representation of the "flow" of data through an information system, modeling its process aspects. Often they are a preliminary step used to create an overview of the system which can later be elaborated .DFDs can also be used for the visualization of data processing (structured design).

A DFD shows what kinds of information will be input to and output from the system, where the data will come from and go to, and where the data will be stored. It does not show information about the timing of processes, or information about whether processes will operate in sequence or in parallel (which is shown on a flowchart).




DFD:- Data flow diagrams represent the logical flow of data within the system. DFD do not explainhow the processes convert the input data into output. They do not explain how the processing takes place.
DFD uses few symbols like circles and rectangles connected by arrows to represent data flows. DFD can easily illustrate relationships among data, flows, external entities stores.
DFD can also be drawn in increasing levels of detail, starting with a summary high level view and proceeding o more detailed lower level views. Rounded rectangles represent processes that transform flow of data or work to be done. Rectangle represents external agents- the boundary of the system. It is source or destination of data.
The open-ended boxes represent data stores, sometimes called files or databases. These data stores correspond to all instances of a single entity in a data model. Arrow represents data flows, inputs and outputs to end from the processes. A number of guideline should be used in DFD
• Choose meaningful names for the symbols on the diagram.
• Number the processes consistently. The numbers do not imply the sequence.
• Avoid over complex DFD.
• Make sure the diagrams are balanced.


Data Dictionary
The data dictionary is used to create and store definitions of data, location, format for storage and other characteristics. The data dictionary can be used to retrieve the definition of data that has
already been used in an application. The data dictionary also stores some of the description of data structures, such as entities, attributes and relationships. It can also have software to update itself and to produce reports on its contents and to answer some of the queries. Determining the Information Requirement The sole purpose of the MIS is to produce such information which will reduce uncertainty risk in a given situation.
The difficulty to determine a correct and complete set of information is on account of the factors given
below:
1. The capability constraint of the human being as an information processor, a problem solver
and a decision-maker.
2. The nature and the variety of information in precise terms.

3. Reluctance of decision-makers to spell out the information for the political and the
behavioural reasons.
4. The ability of the decision-makers to specify the information. In spite of these difficulties,methods are evolved based on the uncertainty scale, starting from the low to the high level
of uncertainty. If the uncertainty is low, seeking information requirement or needs is easy as against a very high level of uncertainty.

 Decision tables

 Decision tables are composed of rows and columns. Each row corresponds to a single rule, with the columns defining the conditions and actions of the rules.

Decision tables are a precise yet compact way to model complicated logic.
Decision tables, like flowcharts and if-then-else and switch-case statements, associate conditions with actions to perform, but in many cases do so in a more elegant way. 
Use a Decision Table to:

·          show sets of conditions and the actions resulting from them when the logic can be easily expressed in a table format, for example, calculating discount rates,

·          verify completeness and consistency of a process involving different actions under different conditions.

Decision Tables work better than Decision Trees for very complex or extensive sets of conditions.

Method

The Decision Table is divided into four quadrants. 
The upper half lists the conditions being tested, the lower half lists the possible actions to be taken.  Each column represents a certain type of condition or rule.

GUIDELINES FOR CONSTRUCTING A DECISION TABLE

Steps to Develop a Decision Table

To Construct a Decision Table:

1)         Draw boxes for the top and bottom left quadrants.

2)         List the conditions in the top, left quadrant.  When possible, phrase the conditions as questions that can be answered with a Y for yes and an N for no.  This type of Decision Table is known as a limited entry table.  When a Decision Table requires more than two values for a condition, it is known as an extended entry table.

3)         List the possible actions in the bottom, left quadrant.

4)         Count the possible values for each condition and multiply these together to determine how many unique combinations of conditions are present.  Draw one column in the top and bottom right quadrants for each combination.

For example, if there are two conditions and the first condition has two possible values while the second has three possible values, draw six (2 * 3) columns.

5)         Enter all possible combinations of values in the columns in the top, right quadrant of the table.

6)         For each column (each unique combination of conditions), mark an X in the bottom, right quadrant in the appropriate action row.  The X marks the intersection between the required action and each unique combination of condition values.


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