Data Flow Testing

Data Flow Testing is a structural testing method that examines how variables are defined and used throughout a program. It uses control flow graphs to identify paths where variables are defined and then utilized, aiming to uncover anomalies such as unused variables or incorrect definitions. By focusing on the flow of data, it helps ensure that variables are properly handled and used in the code.

Table of Content

• What is Data Flow Testing?
• Types of Data Flow Testing
• Advantages of Data Flow Testing:
• Disadvantages of Data Flow Testing
• Control flow graph of above example:
• Define/use of variables of above example:
• Conclusion
• Frequently Asked Questions on Data Flow Testing – FAQs

What is Data Flow Testing?

Data Flow Testing is a type of structural testing . It is a method that is used to find the test paths of a program according to the locations of definitions and uses of variables in the program. It has nothing to do with data flow diagrams. Furthermore, it is concerned with:

• Statements where variables receive values,
• Statements where these values are used or referenced.

By analyzing control flow graphs, this technique aims to identify issues such as unused variables or incorrect definitions, ensuring proper handling of data within the code. To gain a deeper understanding of Data Flow Testing and enhance your testing skills, explore the Complete Guide to Software Testing & Automation by GeeksforGeeks . This course provides detailed insights into Data Flow Testing, including its types, advantages, and practical applications, helping you implement effective testing strategies and improve software quality.

To illustrate the approach of data flow testing, assume that each statement in the program is assigned a unique statement number. For a statement number S-

DEF(S) = 
USE(S) =

If a statement is a loop or if condition then its DEF set is empty and the USE set is based on the condition of statement s. Data Flow Testing uses the control flow graph to find the situations that can interrupt the flow of the program. Reference or defined anomalies in the flow of the data are detected at the time of associations between values and variables. These anomalies are:

• A variable is defined but not used or referenced,
• A variable is used but never defined,
• A variable is defined twice before it is used

Types of Data Flow Testing

1. Testing for All-Du-Paths: It Focuses on “All Definition-Use Paths. All-Du-Paths is an acronym for “All Definition-Use Paths.” Using this technique, every possible path from a variable’s definition to every usage point is tested.
2. All-Du-Path Predicate Node Testing: This technique focuses on predicate nodes, or decision points, in the control flow graph.
3. All-Uses Testing: This type of testing checks every place a variable is used in the application.
4. All-Defs Testing: This type of testing examines every place a variable is specified within the application’s code.
5. Testing for All-P-Uses: All-P-Uses stands for “All Possible Uses.” Using this method, every potential use of a variable is tested.
6. All-C-Uses Test: It stands for “All Computation Uses.” Testing every possible path where a variable is used in calculations or computations is the main goal of this technique.
7. Testing for All-I-Uses: All-I-Uses stands for “All Input Uses.” With this method, every path that uses a variable obtained from outside inputs is tested.
8. Testing for All-O-Uses: It stands for “All Output Uses.” Using this method, every path where a variable has been used to produce output must be tested.
9. Testing of Definition-Use Pairs: It concentrates on particular pairs of definitions and uses for variables.
10. Testing of Use-Definition Paths: This type of testing examines the routes that lead from a variable’s point of use to its definition.

Advantages of Data Flow Testing:

Data Flow Testing is used to find the following issues-

• To find a variable that is used but never defined,
• To find a variable that is defined but never used,
• To find a variable that is defined multiple times before it is use,
• Deallocating a variable before it is used.

Disadvantages of Data Flow Testing

• Time consuming and costly process
• Requires knowledge of programming languages

Example:

1. read x, y;
2. if(x>y)
3. a = x+1
else
4. a = y-1
5. print a; 

Control flow graph of above example:

Define/use of variables of above example:

Conclusion

Data Flow Testing effectively identifies issues related to variable definitions and usages, such as unused variables or multiple definitions before use. While it provides valuable insights into variable handling, it can be time-consuming and requires a good understanding of programming. Overall, it helps improve code quality by addressing potential data flow issues early in the development process.

Frequently Asked Questions on Data Flow Testing – FAQs

1. Is data flow testing black or white?

Data-flow testing is a white box testing technique.

2. What are strategies in data flow testing?

Data Flow Testing strategies involve testing every path from a variable’s definition to its use, and examining all instances where variables are defined or used. It also includes focusing on potential uses, computation uses, and paths from external inputs to outputs.

3. What is Data Flow Test Tools?

Data flow test tools help automate and manage the process of testing how data flows through a program. Some popular tools include: IBM Rational Purify, Microsoft Visual Studio Test.