The coverage of a program is the number of executed statement blocks and condition combinations divided by their total number in the program. One of the standout features of TestCompass is its change impact analysis capability. Let us understand how change impact analysis works and how it helps you find the right testing direction with TestCompass. This would seem to indicate that Multiple Condition Coverage, as the name suggests, only applies to conditionals with multiple statements. To fulfil condition coverage, Boolean expression X, Y and Z will be evaluated in TRUE and FALSE form, at least once.
- This technique requires the coverage of all conditions that can affect or determine the decision outcome.
- In the MCC coverage metric, all statements must be executed and all combinations of truth values in each decision must occur at least once to reach full coverage.
- As a result, a Boolean expression written as a single complex statement will yield test cases that are more likely to overcome masking than when the expression is written as series of simple statements.
- One of the standout features of TestCompass is its change impact analysis capability.
- Bytecode-MCC should produce test obligations that—when satisfied—are more likely to reveal faults in the program logic than tests providing coverage of existing criteria over the simplified bytecode.
According to this explanation, there are 4 test cases for 2 conditions.
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To mitigate this problem the Modified Condition/Decision Coverage metric was created. To illustrate how TestCompass works, let’s walk through an example of creating a model for the login functionality of an e-commerce application. Unlike Condition Coverage a) all possible combinations and b) the decision outcomes are considered.
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Multiple Condition Decision Coverage
The transformation from source code to bytecode requires simplifying code elements, introducing the risk of masking. Bytecode-MCC should produce test obligations that—when satisfied—are more likely to reveal faults in the program logic than tests providing coverage of existing criteria over the simplified bytecode. This is closely related to decision coverage but has better sensitivity to the control flow. However, full condition coverage does not guarantee full decision coverage. In the MCC coverage metric, all statements must be executed and all combinations of truth values in each decision must occur at least once to reach full coverage.
This technique requires the coverage of all conditions that can affect or determine the decision outcome. Masking occurs when one condition prevents another condition from influencing the output of a Boolean expression. Logic-based adequacy criteria such as Multiple Condition Coverage (MCC) are designed to overcome masking at the within-expression level, but can offer no guarantees about masking in subsequent expressions. As a result, a Boolean expression written as a single complex statement will yield test cases that are more likely to overcome masking than when the expression is written as series of simple statements. Many approaches to automated analysis and test case generation for Java systems operate not on the source code representation of code, but on the bytecode.
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Condition coverage is correlated to decision coverage as whenever any decision is to be taken, focus will be on number of possible conditions. However, Bytecode-MCC is more difficult to achieve than Branch Coverage, and means of increasing coverage are needed to truly test the fault-detection potential of this technique. We propose methods of improving Bytecode-MCC coverage through automated generation that we will explore in future work. We strive to explore and co-create better software testing practices. The image below shows how TestCompass prompts you to run an impact analysis after you change the model.
When using the White Box method of testing called https://www.globalcloudteam.com/, do we take all conditional statements or just the ones with multiple conditions? TestCompass runs the impact analysis and shows you a new set of cases on the left of the screen. I might be missing something here but, the way you wrote the code in your question, conditions A and B are completely independent of each other. You therefore won’t cover all of the code unless you test both conditionals. In any decision, there are some possible number of conditions, which can be examined and evaluated by applying Boolean Expression as expressed above. The number of possible combinations can ‘explode’ in light of big numbers of conditions.
