CINF4324_Chapter 7

No process can have only outputs. It would be making data from nothing (a miracle). If an object has only outputs, then it must be a source.

No process can have only inputs (a black hole). If an object has only inputs, then it must be a sink.

• A process has a verb phrase label.
•      “Update” Something
•       Transform Something

Data cannot move directly from one data store to another data store. Data must be moved by a process.

• Data cannot move directly from an outside source to a data store. Data must be moved by a process that receives data from the source and places the data into the data store.
• Aka Data cannot be entered directly by a source

• Data cannot move directly to an outside sink from a data store. Data must be moved by a process.
• Aka Data cannot be given directly to a sink

• A data store has a noun phrase label.
•       Non-phrase label
•       “Something”

• Data cannot move directly from a source to a sink. It must be moved by a process if the data are of any concern to our system. Otherwise, the data flow is not shown on the DFD.
• AKA Source cannot go directly to sink.

• A source/sink has a noun-phrase label.
•      Noun-Phrase Label
•       Someone
•       Something

• A data flow has only one direction of flow between symbols. It may flow in both directions between a process and a data store to show a read before an update. The latter is usually indicated, however, by two separate arrows because these happen at different times.
• AKA: Arrow (no double ended arrow)

• A fork in a data flow means that exactly the same data goes from a common location to two or more different processes, data stores, or sources/sinks (this usually indicates Different copies of the same data going to different locations).
• AKA: Fork means EXACTLY the same data is flowing to multiple places.

• A join in a data flow means that exactly the same data come from any of two or more different processes, data stores, or sources/sinks to a common location.
• AKA: A join means exactly the same data could have come from either places

• A data flow cannot go directly back to the same process it leaves. There must be at least one other process that handles the data flow, produces some other data flow, and returns the original data flow to the beginning process.
• AKS: Data cannot flow directly from where it came; must go through a process.

A data flow to a data store means update (delete or change).

A data flow from a data store means retrieve or use.

• A data flow has a noun phrase label. More than one data flow noun phrase can appear on a single arrow as long as all of the flows on the same arrow move together as one package.
• AKA: Noun-phrase label (it is a “thing”)

• overview of an organizational system that shows.
•      ○ the system boundaries
•      ○ external entities that interact with the system
•      ○ major information flows between the entities and the system
•      ○ should only one process symbol (0, which represents the whole system), and no data stores shown.
• Remember just b/c it has a 0 on the data process symbol it is not a level-0 diagram

• DFD that represents a system’s major processes, data flows, and data stores at a high level of detail.
• Processes are labeled 1.0, 2.0,3.0,4.0 etc. these will be decomposed into more primitive (lower-level) DFDs.

graphic that illustrates the movement of data between external entities and the processes and data stores within a system.

data at rest, which may take the form of many different physical representations.

A data store might contain data about customers, students, customer orders, or supplier invoices

work or actions performed on data so that they are transformed, stored, or distributed.

When modeling the data processing of a system, it does not matter whether a process is performed manually or by a computer.

origin and/or destination of data.

result of decomposition of a Level-0 diagram.

iterative process of breaking the description of a system down into finer and finer detail.

• conservation of inputs and outputs to a DFD process when that process is decomposed to a lower level
• To “balance” means to have the same number of inputs as outputs on lower level DFDs
• Balanced means:
•       ○ Number of inputs to lower level DFD equals number of inputs to associated process of higher-level DFD.
•        ○ Number of outputs to lower level DFD equals number of outputs to associated process of higher-level DFD.

• when a higher level is split with different paths to a lower level DFD
•      ○ Resulting DFD remains balanced, just split in two

• ○ Reduce each process to a single decision, calculation, or database
• ○ Each data store represents data about a singe entity
• ○ When system user does not need to see any more detail
• ○ When each data flow does not need to be split any further
• ○ When each business form, transaction is shown as a single data flow
• ○ When there is a separate process for each choice on lowest level

matrix representation of the logic of a decision; it specifies the possible conditions for the decision and the resulting actions.

part of a decision table that lists the conditions relevant to the decision.

part of a decision table that lists the actions that result for a given set of conditions.

part of a decision table that specifies which actions are to be followed for a given set of conditions.

in a decision table, a condition whose value does not affect which actions are taken for two or more roles.

• 1. Name the condition and the values that each can assume
•         For example:
•               Employee type = salary and hourly 
•               Pay type = regular, overtime and missed 
• 2. List all possible rules
•        To determine the number of rules, multiply the number of         values for each condition by the number of values for                every other condition.
•            For example:
•                Employee type = salary(1) and hourly(2), so 2 values
•                Pay type = regular(1), overtime(2) and missed(3), so 3 values
•                      2*3=6 rules
• 3. Name all possible actions that can occur
• 4. Define the actions for each rule
• Simplify the table