Data-flow Diagrams Chapter 17. Elements of data-flow diagrams  There are four basic elements of data flow diagrams: Data Transforms: where data is filtered,

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Presentation transcript:

Data-flow Diagrams Chapter 17

Elements of data-flow diagrams  There are four basic elements of data flow diagrams: Data Transforms: where data is filtered, formatted or synthesized. Information sources and sinks: essentially inputs and outputs to the system. Information stores: where information is kept for the duration of system activity. Information Flows: data that is passed into and out of transforms, information stores.

Information flows  Information flows represent the information being passed into or out of a transform, source, sink or store. It is represented as a labeled arrow: Taxable Income

Data transforms  Data transforms labeled circles with one or more incoming and outgoing information flows: Calculate Tax Taxable Income Tax Tables Tax owed

Information sources and sinks  Information sources and sinks are information that come into the system, or leave the system, and are represented by squares: Rate Hours Pay Check Pay Stub Payroll System

Information stores  Information Stores represent locations where information can be store for the duration of the system activity: Total Payroll Expense

Refining DFDs  DFDs are “refined” (decomposed) to the point that they contain only “primitive” transforms. They are refined by drawing another DFD as if they were a system in themselves!  A “primitive” transform has only one input flow or only one output flow (note that it can have multiple input flows or multiple output flows, but not both!)

Heritage numbers  Refinement of DFDs leads to a problem in larger systems: we have a large number of diagrams! When we look at a diagram by itself the only way we can tell what it represents is by looking at the parent diagram.  Heritage numbers allow this. A data transform numbered is the child of DFD number 2.4 which is the child of DFD 2 in the level 1 DFD diagram.

The data dictionary  As the data is defined in the DFD (the flows), definitions should be entered in the ‘data dictionary’.  The ‘data dictionary’ is a reference that allows us to determine the type of the named data (int, float, struct, whatever.)  This will be essential during the programming phase, when knowing what variable names to use.

Checking DFDs - CASE tools  Since DFDs are a formal method, tools have been developed that allow automated drawing of the DFDs, and management of refined DFDs.  Since this can be automated, checking DFDs can also be automated (such as ‘Process Analyst’).

Structure charts  Translation of a DFD to a ‘structure’ chart is a mechanical procedure (see the book.)  The procedure involves ‘isolating’ the central transform area, which is independent of the format transforms and the validation transforms.  Structure charts also provide a schematic showing the flow of the data in a control diagram!  Now we have a complete picture: DFDs show how the data flows, and structure charts show how control is passed!

Payroll System Employee Records Employee Timecards Accounting Reports Paychecks and Stubs Calculate Gross Pay Calculate Withholding Validate Timecard Format Accounting Format Paycheck Input/output stream At highest abstraction Central transform

Payroll System Validate TimecardCalculate Net PayFormat PaycheckFormat AccountingGet Imployee InfoCalculate Gross Pay Calculate Withholding

Implementing a DFD  Once we have a structure chart, the actual implementation also becomes mechanical. An essential pre-defined form becomes apparent for implementing structure charts. An example using C is available in the book.