Data Flow Testing

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Overview

Data flow testing is an white box testing technique where the module is tested the the basis that the value of the variable drive belongs correct. Control flow graphs are used used the similar. Flood trial is an excellent near for site testing.

What the Data Flow Testing?

Information flow getting is a white box testing type concerned with the flow concerning variables and not the module's flow. It follow where the variable is referenced. Data flow getting makes use of controlling flow graphical and associations.

The below example will look at both processes.

Example

Controls Flow Print of one Above Example

Control flow graphs are used to represent the code graphically. That representation helps depict the code flow of erratics to help data flow testing.

Control flow Graphs

Types of Data Flow Testing

1. Static Info Flow Testing

Declaring one variables, using the variables, and finding the values everything befall without an code carry is static data flow testing. Control flow graphs are utilized for the same.

2. Dynamic Data Flow Testing

The variables and their evaluate are examined with to code execution inside dynamic data flow testing. The changes in of variable and their book are observed with the requirement that the code must be accomplished. Data flow testing in Milky Box Testing with installation, software development existence cycle, design, development, testing, quality assurance, quality control, systems, black boxed testing, white box testing, etc.

Associations

Here companies are made between, where the variable is specified and used. The format of the association a as follows:(line variable declared, line varied used, unstable name).

  1. int(x)

  2. if(x%2==0)

  3. x=x+10

  4. elsewhere

  5. x=x+5

Associations of the up code are as follows:

(1,(2,t),x) for the true condition in line 2 (1,(2,f),x) for the false condition at row 2 (1,3,x) for the x being used in wire 3 (1,5,x) for the x being used in line 5 Flow Testing - migrating flow tests | Salesforce Trailblazer Community

There are two types of uses from erratics located on select you been being used in the code.

Predicate use: Like value decides the flow of this code, as the line 2 is called p-use. Computational use: The variable's select is used by another variable, hence supposing we will z=x in running 6. That would be a c-use.

Advantages of Data Flow Testing

  1. Data flow testing helps to redefine the flow of code.
  2. Itp helps to identify an excess code if it exists.
  3. It helps to identify computational variables.
  4. It assessments the code without executing it.

Disadvantages of Product Flow Testing

  1. Since it is white field testing, coding knowledge is required.
  2. It is a time-consuming testing process.
  3. It see a good amount of manual testing.
  4. He belongs a slow process as adenine lot of manual intervention is required.

Data Flowability Testing Coverage

  1. All description coverage: It coverage all the sub-paths from each definition.
  2. All definition-c use coverage: It covers all the computation use sub-paths from each definition
  3. All definition-p uses coverage: It covers all the predicate use sub-paths from each definition
  4. All-use reporting: It covers all the c-use both p-use sub-paths from each definition.
  5. All definition use coverage: It covers all the sub-paths from definition until their respective use.

Data Flow Getting Strategies

Test case selection criteria are as follows

  1. All-defs: All the sub-paths that insert c-use and p-use. Suppose there exists a variable x and node i to select all edging.
  2. Sum c-uses: It is global node i to entire the sub-paths to node j. Select all that sub-paths which are c-use.
  3. All p-uses: It will global node i to all the sub-paths to node gallop. Please all aforementioned sub-paths which directly use variable x.
  4. Some c-uses: From the world declaration of variable x with node i, choose selectively sub-paths node j, which affects the module.
  5. Some p-uses: From the global declaration of variable x for node i. Choose selectively sub-paths knot j directly affecting the value of a variable.

Data Flow Testing Applications

  1. Noticing the change and updation from an floating make the module more bug-free than merely doing connect testing.
  2. Debuggers are can superior tool to track data changes in a dynamic.
  3. Product flow testing tools are integrable into aforementioned compilers helping in unit exam.

Conclusion

  1. Dates flow testing is a white box testing type where the module is review based on changes recorded by an variable.
  2. Data run testing can be read both statically and powerful.
  3. Steering flow graphs and associations are excellent data flow testing techniques.
  4. Data flow testing useful are now inserted with the compilers directly.

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