Data Flow Diagram(DFD)
Data flow diagram can be of two types:
1. Logical
DFD : This type of DFD focuses on the system
process and the flow of data within the system. For example in banking
software how data is moved within the entities.
2. Physical DFD: This type of DFD shows how the data flow is implemented in the system, and it is more specific and closely related to its implementation.
DFD Components:
DFD can represent the source, destination,
storage, and flow of data using the following set of components.
Entity: Entities are both the
source and destination of informational data. These entities are typically
depicted as rectangular shapes, each with their own unique name or label.
Process: These are the activities
or the action followed by the system to convert input data into required output
data. It is represented by a circle.
Data flow: The
movement of data is depicted using directional arrows, with the base indicating
the source and the head representing the destination.
Data store: Data
stores are storage containers of the data. It is reprinted by parallel lines.
Levels of Data Flow Diagram:
In Software engineering, you can draw a DFD (data flow diagram) to represent a system with different levels of abstractions. DFDs at higher levels are broken down into low levels - hacking more data and functionality. Levels in a DFD are numbered from 0 to 2 or higher. Here we will study only three levels of abstraction i.e. level 0, level 1, level 2.
Level 0 DFD: This is the top-level
DFD. It shows the main processes, data flows and data stores within the system.
However, it does not provide information on the inner workings of these
processes.
It is also known as context diagram and present the whole system as a bubble with the inputs and outputs indicated by the arrows.
Level 1 DFD: This level allows for a deeper understanding of the system by dividing the main processes defined in Level 0 DFD into a sub-process. On Level 1 DFD, each sub-process is represented as a process in its own right. Data flows and data stores are also shown for each sub-process.
Level 2 DFD: This level further
deepens the understanding of the system by dividing sub-processes defined in
Level 1 DFD into sub-processes, each of which is represented as a process on
Level 2 DFD.
Rules of Data Flow Diagram:
Advantages of DFD:
· Easy
to understand.
· Improves
system analysis.
· Support
system design.
· Enable
testing and verification.
· Facilitates documentation.
Disadvantages of DFD:
· Time
consuming.
· Needs
an expert.
· Difficult to keep up to date.
Data Dictionary:
A data dictionary provides a comprehensive listing of all data elements present in the DFD model of a system. It outlines the purpose of each data element and defines any composite data elements in relation to their constituent parts. For example, a data dictionary entry may represent that the data grossPay consists of the components regularPay and overtimePay.
Gross pay = regular pay + overtime pay.
Case tool helps in the maintenance of the data dictionary because it automatically captures the data entries in the DFD to create the data dictionary.
The notations used in the data dictionary
are given in the table below:
Some features of Data Dictionary is given
below:
·
Used for Designing and
testing software in Software Engineering
·
Used to find data items
by using descriptions.
·
Ordered list of a subset
of data items can be created using data dictionary.
· Ordered list of items can be created.
Advantages of Data Dictionary:
·
Data
Integrity
·
Data
quality
·
Consistency and standardization
·
Improved collaboration
· Improved efficiency
Disadvantages of Data Dictionary:
·
Implementation and
maintenance cost
·
System
complexity
·
Resistant to change
·
Data
security
·
Data
governance
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