Code coverage indicates how thoroughly your test bench has exercised the source code. The term “functional coverage” refers to how well the design’s functionality has been covered. Finally, branch coverage differs from line coverage in a similar way to which it differs from statement coverage. That is, even if the test cases exercise all lines, that doesn’t mean that it also exercises all possible logical paths. So, while 100% statement coverage necessarily implies 100% line coverage, the opposite isn’t true.
This metric tells you how many of your branches have been executed. If we were to draw the path taken by Test 2_2, it would be a straight line from the read statement down the False exit and through the ENDIF. We could also have chosen other numbers to achieve either the True or False outcomes. Branch coverage and Statement Coverage are form of white box testing techniques. It aids in identifying portions of a source code that might otherwise go untested or discovered by the tests. If our tests call the ‘Add’ function even once in the source code above, we would refer to it as a full Function coverage.
Code Coverage Tutorial (Branch, Statement, Decision, FSM)
But it’s important to note that semi-covered branches are marked as partials and partials are not considered hits when calculating coverage. To measure what percentage of code has been executed by a test suite, one or more coverage criteria are used. These are usually defined as rules or requirements, which a test suite must satisfy. There are several methods to calculate Branch coverage, but pathfinding is the most common method. A decision is an IF statement, a loop control statement (e.g. DO-WHILE or REPEAT-UNTIL), or a CASE statement, where there are two or more outcomes from the statement.
Allows you to validate all of the code’s branches, ensuring that none of them lead to any abnormalities in the program’s execution. Statement coverage is used to derive scenario based upon the structure of the code under test. It helps you determine which logical paths got tested or not, contributing to a more comprehensive test suite. We’ll define line coverage and then it’ll hopefully be clear how they differ. You need to address all lines is branch 1 and branch 2 to get 100% coverage for both LineCoverage and BranchCoverage. Find out the minimum number of paths which will ensure covering of all the edges.
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The test requirements for branch coverage are the branches of the program. In other words, the goal of this coverage is to execute all of the branches in the program. On the other hand, coverage measure is defined accordingly as the number of branches executed by your test cases over the total number of branches in the program. Statement coverage entails running all of the source code’s executable statements at least once. Decision coverage gives the true or false results of each Boolean expression.
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- The difference between line coverage and statement coverage is that the correspondence between statements and lines isn’t always one to one.
- There are other indicators that can help predict the quality of codebases in general—such as rework or code churn, for instance.
- The fact that by testing more thoroughly we have more chances of finding a problem in the code.
- As a result, it’s critical that the software generated be evaluated by the developer and then delivered to the QC team to be extensively tested to guarantee that it has few or no flaws.
- Like decision coverage, it also uses a control flow graph to calculate the number of branches.
A condition or predicate when evaluates to true must execute the next relevant line of code that follows. For a statement like A && (B || C), coverage branch coverage calculation tests each possible combination of results. Conditional statements create branches of code which may not be executed (e.g. if/else).
Test case development
It covers all the possible outcomes of each condition of decision point at least once. Branch coverage technique is a whitebox testing technique that ensures that every branch of each decision point must be executed. In this method, the number of paths of executed branches is used to calculate Branch coverage. Branch coverage technique can be used as the alternative of decision coverage.
If you want to get the most out of your code coverage, you should be using both line and branch coverage. Getting line coverage is important to track that all lines are being https://www.globalcloudteam.com/ run. But tracking branch coverage helps to make sure that you aren’t missing edge cases. Branch coverage is best described in terms of test requirements and coverage measure.
What is Branch Coverage or Decision Coverage? Its advantages and disadvantages
In other words, the tester will be concentrating on the internal working of source code concerning control flow graphs or flow charts. In this example, the login page validation has three possible outcomes. When the login credentials are validated for the correctness, there rise three possible functional flows.
Sometimes the decision structure is easier to see in a control flow diagram (see Figure 4.4). In the above code, 71.5% statement coverage is achieved by test case #1. Among the most popular code coverage tools are Cobertura, JTest, Clover, Emma, and Kalistick. Every result from a code module is tested in the branch coverage.
Black Box Techniques
Test coverage was among the first methods invented for systematic software testing. The first published reference was by Miller and Maloney in Communications of the ACM, in 1963. Let’s suppose that we already have the following test, which gives us 100% statement coverage for code sample 4.3. So what this relation means is that branch coverage is stronger than statement coverage, but also more expensive.
This methodology is a metric that determines if all possible executable statements in source code have been run at least once. It’s a technique for ensuring that each line of source code is tested at least once. Having a comprehensive set of metrics can help smooth out the weakness of individual ones, ensuring you get a net positive result. The best way to get a single source of metrics truth and observability to give you a comprehensive look at cycle time, code churn, rework, branch coverage, and much more? Branch coverage is an important metric in that it can help a team or organization assess whether an application has been tested to completion. A low branch coverage shows that there are scenarios in the application lacking testing.
What is Code coverage?
All these methods focus on covering the most important combinations. It is very much similar to decision coverage, but it offers better sensitivity to control flow. This metric simply tells you the ratio of statements in an application that are currently under testing. Branch coverage, as we’ve seen, is about whether all branches—or paths of execution—in an application are under test. In this case, if 4 cases are written matching the above logic statements, we would see 100% branch coverage. This helps developers from having to explicitly write out all 8 paths.