Code Coverage Tutorial: Branch, Statement & Decision Testing

Since there are only two possible outcomes of a decision , and there are only two outcomes of a conditon, test situations can be created in such a way that only 2 test situations per decision point are needed. Whenever there are two or more possible exits from the statement like an IF statement, a DO-WHILE or a CASE statement it is known as decision because in all these statements there are two outcomes, either TRUE or FALSE. Where the total number of decisions will be the count of the logical decisions identified in the program and the number of decisions implemented out of them will give the Decision Coverage percentage value. Branch Coverage technique involves checking whether every possible path or branch is covered. Branching is actually a jump from one decision point to another.

decision condition coverage example

Eventually, between 2 nd and 3 rd, only C changed of value and decision’s outcome’s value also changed (passing from “true” to “false”). The use of MCDC is in many situations easier and more effective than using decision tables or other techniques. Let us open ourselves up for the techniques and thoughts available in the community, without bothering about barriers that some still try to impose on us. If the number of atomic conditions is higher, you just continue this approach and you will end up with N+1 test cases . If the analyzed relation is combined with the other atomic condition with an “AND”-relation, then we add a “1”, whereas with an “OR”-relation, we would add a “0”, to not change the complex condition outcome. In order to select a coverage method, the tester needs to check the cost of the potential penalty, lost reputation, lost sale, etc.

Example of Branch Coverage

Making statements based on opinion; back them up with references or personal experience.

Branch coverage is like doing TRUE and FALSE, but in decision coverage, you need to go through each condition … Full statement coverage is when you visit every node in the graph at least once, full branch/decision coverage is when you traverse every edge in the graph at least once . Where A, B and C represent atomic boolean expressions (i.e. not divisible in other boolean sub-expressions).

Widen the perspective: White Box’s “condition coverage” for everyone

If the condition X is true, then the decision is already known to be true. Therefore, the conditions Y and Z would not affect the decision outcome. All conditions within decisions have been evaluated to all possible outcomes at least once. Many testers are considering or already using test design techniques, allowing them to reduce the effort in testing and still gain a good insight in the quality of systems and software. Looking at the possibilities and the available literature, often a categorization is made, to ease up technique selection for specific situations.

decision condition coverage example

This criterion extends condition/decision criteria with requirements that each condition should affect the decision outcome independently. Generally, a decision point has two decision values one is true, and another is false that’s why most of the times the total number of outcomes is two. The percent of decision coverage can be found by dividing the number of exercised outcome with the total number of outcomes and multiplied by 100. The last and final step in the Decision Coverage testing process is to evaluate logical decision indications gathered and designed in the previous steps of this testing process. The end points in the various logics are subjected to the necessary validation and verification methods.

Multiple Condition Decision Coverage

This black-and-white differentiation is not a good and definitely not a correct perspective. Categorizations as such provide us some help in that they ease up our conversation and point out our focus in designing test cases, the categorization should definitely not be treated dogmatically. Professional testers nowadays even combine or integrate the corresponding techniques in exploratory testing.

  • In this coverage method, you need to look for how many time-specific states are visited, transited.
  • To fulfil condition coverage, Boolean expression X, Y and Z will be evaluated in TRUE and FALSE form, at least once.
  • The higher the probability that defects will cause costly production failures, the more severe the level of coverage you need to choose.
  • Stack Exchange network consists of 182 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.
  • The guidelines by which avionics gear is certified by the Federal Aviation Administration is documented in DO-178B and DO-178C.

On the other hand, in condition coverage, all possible outcomes of all conditions must be tested at least once. Generally in any software, if we look at the source code, there will https://www.globalcloudteam.com/ be a wide variety of elements like operators, functions, looping, exceptional handlers, etc. Based on the input to the program, some of the code statements may not be executed.

Condition/Decision Coverage

To get 100% statement coverage only one test case is sufficient for this pseudo-code. If you think about your program as a big directed graph with a start node going to one or more end nodes. Each statement in your program is a node on the graph, branches or decisions are edges between nodes. On the other hand, to ensure Modified condition/decision coverage, we should test only the 5 combinations here-before underlined in yellow. Relational boundary code coverage examines code that has relational operations. Relational boundary code coverage metrics align with those for model coverage, as described in Relational Boundary Coverage.

To calculate Branch Coverage, one has to find out the minimum number of paths which will ensure that all the edges are covered. In this case there is no single path which will ensure coverage of all the edges at once. In order to ensure Condition coverage criteria for this example, A, B and C should be evaluated at least one time “true” and one time “false” during testes. This technique aims to cover the various conditions and its consecutive flow.

What is the difference between a Decision and a Condition?

The main purpose of Statement Coverage is to cover all the possible paths, lines and statements in source code. As with any terminology there is no guarantee that everyone means exactly the same thing by the same term. Wikipedia seems to take branch coverage https://www.globalcloudteam.com/glossary/decision-condition-coverage/ to mean modified decision coverage but there are plenty of other sources, as you note, that say they are the same. What we can say more authoritatively is that statement coverage is not the same as branch coverage, and neither are the same as path coverage.

decision condition coverage example

This technique reports true and false outcomes of Boolean expressions. Decision coverage analyzes statements that represent decisions in source code. Decisions are Boolean expressions composed of conditions and one or more of the logical C/C++ operators && or ||. Conditions within branching constructs (if/else, while, and do-while) are decisions. Decision coverage determines the percentage of the total number of decision outcomes the code exercises during execution. Use this type of coverage to determine whether all decisions, including branches, in your code are tested.

Condition coverage vs. branch coverage

Paths within it; loop constructs can result in an infinite number of paths. Many paths may also be infeasible, in that there is no input to the program under test that can cause that particular path to be executed. However, a general-purpose algorithm for identifying infeasible paths has been proven to be impossible . Basis path testing is for instance a method of achieving complete branch coverage without achieving complete path coverage. That’s why there are many different methods of reporting this metric.

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