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Branch Coverage Testing in SDLC
In this article, I am going to discuss Branch Coverage Testing in SDLC. Please read our previous article where we discussed Control Flow Testing. At the end of this article, you will understand the following important pointers which are related to Branch Coverage Testing in SDLC.
- What is Branch Coverage Testing?
- What Is the Process of Branch Coverage Testing?
- Why is Branch Coverage Testing Important?
- Why do we need Branch Coverage Testing?
- How are branch coverage tests carried out?
- How to Calculate Branch Coverage?
- What are the Advantages of Branch Coverage Testing?
- What are the Disadvantages of Branch Coverage Testing?
What is Branch Coverage Testing in SDLC?
Branch coverage testing is a white-box testing technique that assesses the efficacy of test cases by counting the number of branches or decision points that were actually taken during the testing process. It’s a measure that shows how much of the source code has been put through its paces by various test cases being run. When performing white-box testing, testers can create test cases based on the logic and structure of the code because the internal organization and implementation details of the product are known. The control flow of the program is the focus of branch coverage, in particular the decision points that lead to branching, such as if statements, switch statements, and loops.
The objective of branch coverage testing is to make certain that each potential branch of the code is tested at least once. This implies that both the true and false branches should be evaluated for each decision point. Testers can detect problematic portions of code that are not sufficiently tested while also increasing confidence in the stability of the product by attaining high branch coverage.
What Is the Process of Branch Coverage Testing?
A software testing technique called branch coverage testing, often referred to as branch testing or decision coverage testing and assesses the degree to which the branches or decision points found in a program’s source code have been executed throughout testing. Branch coverage testing seeks to confirm that every program’s feasible branch has been run at least once. Branch coverage testing operates as follows:
- Identifying Branches: To find branching or decision points, the source code is first examined. A branch is a place in the code where, depending on a condition or choice, the program can take one of several potential pathways.
- Test Case Generation: The creation of test cases allows for the testing of various code branches. To cover all potential circumstances, it may be necessary to run multiple test cases for each branch. The goal is to develop test cases that can cover every code decision point.
- Executing the test cases: The created test cases are run in opposition to the under-test program. The testing tool or framework keeps track of the branches that are crossed during execution.
- Coverage Measurement: Branch coverage is measured by the testing tool or framework, which also maintains track of the executed branches. The fraction of branches that have been executed during testing is indicated by branch coverage, which is frequently given as a percentage.
- Analyzing coverage results: To find any untested branches, the coverage results are reviewed. Untested branches hint that there may have been gaps in the testing process and that some areas of the code may not have received enough testing.
Why is Branch Coverage Testing Important?
Testing branch coverage is essential since it ensures the accuracy and dependability of software testing. Branches are decision points in code, such as if-else statements or loops, where various courses of action are chosen depending on specific circumstances. We can calculate the proportion of branches that have been executed during testing by assessing branch coverage. This measure demonstrates how well our test suite explores various logical avenues, revealing perspective code sections that have not yet been checked. A considerable amount of the code has been tested, reducing the possibility of undiscovered flaws and raising the level of software quality overall. This is indicated by high branch coverage. It improves code stability, and maintainability, and develops more trust in the functionality of the software.
Why do we need Branch Coverage Testing?
To assure the dependability and accuracy of the code, branch testing is crucial in the development of software. It addresses a program’s conditional statements or branches specifically. Branch testing helps find potential mistakes and vulnerabilities that can go undiscovered using other testing techniques by exercising both the true and false results of each branch. It offers a thorough analysis of the code’s behavior, boosting trust in its operation and lowering the chance that flaws will find their way into the final result. Developers can find and fix problems earlier by extensively testing every branch, which results in more reliable and robust software systems.
How are branch coverage tests carried out?
- Each and every section of the code that branches is subjected to branch coverage testing. For instance, the program’s conditional and loop instructions can each provide more than one possible outcome when run. Therefore, the first step in putting Branch Coverage Testing into practice is identifying the branches.
- The next step is to create a list of the outcomes or results of each code branch. If a branch is discovered to be an “if” conditional, it may have two or three possible outcomes; if it is discovered to be a “switch case” conditional statement, it may have more than that. It is crucial in this procedure to not overlook any prospective branches or the outcomes of those branches.
- The last stage of branch coverage testing is to verify test execution across all branches and retrieve the results. The ‘expected results’ column in the test script documentation created for the Branch Coverage Testing procedure should match these results. Any disparity merely indicates that the functionality is defective and needs to be recorded to comply with the specification put forward by the client or the business analyst.
- This process of quality assurance is an essential component of code validation since the test cases cover both the software application’s positive and negative functional flows. If not, the system won’t know how to react when something unexpectedly negative happens. An application’s login screen, for instance, requires the user to input their login name and password. The program has to inform the user of what went wrong and prompt them to fix it in situations like an erroneous or blank login and password. Therefore, the conditional statement is required in the code to account for such failure possibilities. To make sure these gaps are properly filled, branch coverage testing is a crucial activity.
How to Calculate Branch Coverage?
Pathfinding is the most popular way to compute Branch coverage, although there are other approaches as well. This method calculates Branch coverage by counting the pathways taken by branches that have been executed. Decision coverage can be replaced with the branch coverage technique. Although it is not officially specified as a tactic anywhere, decision coverage is different from it and is required to test each branch of the control flow graph. Let’s use an illustration to clarify it:
Read A
Read B
IF A+B > 50 THEN
Print “Large”
ENDIF
If A + B<50 THEN
Print “Small”
ENDIF
We used variables A and B along with two conditions to create the basic code structure. Print “Large” if the first condition is true; if it is false, move on to the second condition. If the second criterion is true, print “Small.” Below is the control flow graph for the above source code:
The control flow diagram for the aforementioned code is shown. Edges 1, 2, 4, 5, and 8 are covered in the first case’s path, which follows the “Yes” option, but edges 3 and 7 are not. The path is X1-Y2-Z4-P6-R8. We must cross over the “No” decision if we are to cover these edges. The path is X1-Y3-5-P7 with 3 and 7 covered edges in the “No” decision scenario. Therefore, by following these two routes, all branches have been reached.
Path 1 – X1-Y2-Z4-P6-R8
Path 2 – X1-Y3-5-P7
Branch Coverage (BC) = Number of paths =2
Case | Covered Branches | Path | Branch Coverage |
Yes | 1, 2, 4, 5, 6, 8 | X1-Y2-Z4-P6-R8 | 2 |
No | 3, 7 | X1-Y3-5-P7 |
What are the Advantages of Branch Coverage Testing?
The following benefits of branch coverage testing in software development:
- Comprehensive Testing: It makes sure that all viable code branches are tested, improving the chances of seeing potential problems and lowering the chance of defects going undetected.
- High branch coverage makes it possible to find conditional statement flaws and guarantees that all possible execution routes have been thoroughly tested, making for more dependable and stable software.
- Branch coverage encourages code quality and adherence to coding standards by encouraging disciplined programming practices, which raises the software’s overall stability and maintainability.
- Effective Debugging: When problems occur, strong branch coverage enables developers to identify untested branches and concentrate their debugging efforts on certain areas, aiding quicker bug resolution.
- Customer Satisfaction: Branch coverage testing results in better software quality, fewer problems, and increased stability, all of which increase customer satisfaction and faith in the product.
What are the Disadvantages of Branch Coverage Testing?
Although useful, branch coverage testing has certain drawbacks.
- Insufficient Branch Coverage: Because of the scale and complexity of software systems, it is frequently impossible to achieve 100% branch coverage, leaving some branches untested.
- Focus on Code Structure: Branch coverage places more emphasis on code structure than on output accuracy, potential logical flaws, or bugs.
- Limited Range: Branch coverage by itself does not ensure thorough test coverage of essential elements like boundary conditions, error handling, or performance testing.
- Resource-Intensive: For large and complicated codebases, achieving high branch coverage is unfeasible because it takes a lot of time and effort.
- Maintenance Overhead: Code modifications may render outdated branch coverage tests invalid, requiring ongoing maintenance and updating.
In the next article, I am going to discuss Statement Coverage Testing. Here, in this article, I try to explain Branch Coverage Testing in SDLC. I hope you enjoy this SDLC Branch Coverage Testing article.