Multiple Condition Coverage

Predicate coverage aims to test the logical combinations of conditions to ensure that all paths within a decision are exercised. Like condition coverage, predicate coverage is also expressed as a percentage, representing the proportion of unique condition combinations tested. Branch Coverage is a white box testing method in which every outcome from a code module(statement or loop) is tested. The purpose of branch coverage is to ensure that each decision condition from every branch is executed at least once. It helps to measure fractions of independent code segments and to find out sections having no branches.

The meaning of this depends on what form(s) of coverage have been used, as 67% branch coverage is more comprehensive than 67% statement coverage. Predicate coverage is a more fine-grained metric that goes beyond just examining multiple condition coverage branches and focuses on evaluating conditions (predicates) within those branches. It ensures that all combinations of conditions within a decision are tested, including different conditions in complex logical expressions.

Multiple Condition Coverage

The tester has access to the source code and uses this knowledge to design test cases that can verify the correctness of the software at the code level. To satisfy condition coverage, each Boolean expression X,Y and Z in above statement should be evaluated to TRUE and FALSE at least one time. I believe there should be four unit tests for this particular function.

• Code coverage is a measure which describes the degree of which the source code of the program has been tested.
• In this coverage, expressions with logical operands are only considered.
• They both report a coverage metric, measured as a percentage.
• Ultimately, it depends on you(r team), the code and the specific project environment.
• Assume this function is a part of some bigger program and this program was run with some test suite.

This metric is often expressed as a percentage, indicating the proportion of branches executed during testing. Predicate coverage is more thorough but more challenging in practice, especially in code with complex logical expressions. The choice between these coverage metrics depends on the testing objectives and the specific requirements of the software being tested.

Decision Coverage or Branch Coverage

It also creates some test cases to increase coverage and determining a quantitative measure of code coverage. In software engineering, code coverage is a percentage measure of the degree to which the source code of a program is executed when a particular test suite is run. Some of the most basic are the percentage of program subroutines and the percentage of program statements called during execution of the test suite.

Regardless, both are linear in terms of complexity so for modern languages and hardware the difference is moot. Finite state machine coverage is certainly the most complex type of code coverage method. In this coverage method, you need to look for how many time-specific states are visited, transited. It also checks how many sequences are included in a finite state machine. Scenario to calculate Statement Coverage for given source code.

Here we are taking two different scenarios to check the percentage of statement coverage for each scenario. In most cases, code coverage system gathers information about the running program. It also combines that with source code information to generate a report about the test suite’s code coverage. White box testing is also known as structural testing or code-based testing, and it is used to test the software’s internal logic, flow, and structure. The tester creates test cases to examine the code paths and logic flows to ensure they meet the specified requirements. However, this set of tests does not satisfy branch coverage since neither case will meet the if condition.

Three to test each of the conditions in the if statement and ensure it returns false. Both solutions effectively do the same thing and do satisfy «multiple condition coverage» assuming you only want «Hello» to print when both are true. Whether or not one is more efficient than the other depends on the language being used.

Unlike Condition Coverage a) all possible combinations and b) the decision outcomes are considered. The number of possible combinations can ‘explode’ in light of big numbers of conditions. To mitigate this problem the Modified Condition/Decision Coverage metric was created. In any decision, there are some possible number of conditions, which can be examined and evaluated by applying Boolean Expression as expressed above. The statements marked in yellow color are those which are executed as per the scenario.

Condition/decision coverage requires that both decision and condition coverage be satisfied. However, for safety-critical applications (such as avionics software) it is often required that modified condition/decision coverage (MC/DC) be satisfied. This criterion extends condition/decision criteria with requirements that each condition should affect the decision outcome independently.