All Things You Need To Know About Exhaustive Testing
Everyone knows exhaustive testing is impossible, or at least impractical to do. Or is it? Take a look at this explanation and some examples.
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Exhaustive testing, which is also known as complete testing, occurs when all the testers in your team are exhausted and when all the planned tests have been executed. It is a quality assurance testing technique in which all scenarios or data is tested for testing. In a more understandable way, exhaustive testing means ensuring there are no undiscovered faults at the end of the test phase. Testing everything (all combinations of inputs and preconditions) is not feasible except for trivial cases. As testers, we often say, “Well I just never have enough time for testing.” Even if you had all the time in this world, you still wouldn’t have enough time to test all the possible input combinations and output combinations.
Strategies for Exhaustive Testing
We know that one of the 7 testing principles of software testing says that exhaustive testing is not possible. Now the question is that, as exhaustive testing is not possible, how we are supposed to get enough coverage to tell that the application under test is tending to not having any defects?
Instead of trying to test everything with what we tend to do and that we want to apply some helpful approaches, we use risk and priorities to focus testing efforts. We may do techniques such as pairwise testing to reduce the number of combinations, or things like cause-effect graphing and do more of a logic-based approach to optimize our testing. Here are basic and fundamental strategies that one can definitely include in their test plan:
- Impact on Business: This not the only one but is one of the most important parameters to understand the risk. Testers should question that if a certain functionality of a module being tested fails, how much risk will it will bring to the entire module. Testers should constantly work with the business analyst of the module to understand the threat brought by the failure of each functionality so that it can be prioritized high up in the testing.
- Probability of failure: This parameter also plays a major role in understanding the health of a functionality. Some functionalities can have a high probability of failure compared to other functionalities. For example, let’s consider an e-commerce site which will have one functionality of logging in as a user and other to determine the users browsing history and correctly give the user more options to look at (cross sell/upsell). As a tester, we can identify that the second functionality has a higher probability of breaking because it contains a lot of business algorithms to be implemented compared to a login page which might have less probability of failure.
- Regression: Testers should look at this parameter by identifying functionalities which have to be regressed more often when there is a change or addition to certain areas of the AUT. Correct impact analysis should be done to determine the areas correctly. Impact analysis should always involve developers, QA, and the Business Analyst team to get a correct understanding of the impacted areas.
- Recovery: If a functionality breaks how fast can it be recovered or the recovery time taken. QA personnel can get the inputs from developers on the recovery time for each functionality of the application under test.
Why Exhaustive Testing Is Impractical and Impossible
It is not possible to perform complete testing or exhaustive testing. For most systems, it is near impossible because of the following reasons:
- The domain of possible inputs of a program is too large to be completely used in testing a system. There are both valid inputs and invalid inputs.
- The program may have a large number of states. There may be timing constraints on the inputs, that is, an input may be valid at a certain time and invalid at other times. An input value which is valid but is not properly timed is called an inopportune input. The input domain of a system can be very large to be completely used in testing a program.
- The design issues may be too complex to completely test. The design may have included implicit design decisions and assumptions. For example, a programmer may use a global variable or a static variable to control program execution.
- It may not be possible to create all possible execution environments of the system. This becomes more significant when the behavior of the software system depends on the real, outside world, such as weather, temperature, altitude, pressure, and so on.
Exhaustive Testing Examples
Example 1:
The IE Tools > Advanced Options window:
53 binary conditions
1 condition with 3 options
1 condition with 4 options
2^53 = 9,007,199,254,740,992 x 12 = 108,086,391,056,891,904 possible combinations of conditions
At one second per test execution:
108,086,391,056,891,904 / 360 = 300,239,975,158,033.067 hours (12,509,998,964,918.04 days or 34,273,969,766.9 years) to test all possible combinations.
Example 2:
Let's take an e-commerce site which has the following functionalities:
- Login
- Choose a product
- Filter product with color
- Filter a product with price.
- Add to Cart
- Buy the product (payment portal)
On the basis of risk identifying parameters, users can create a matrix to include in the test plan. Each parameter can be given scores so that we can have a correct way to identify high-risk areas.
- Impact on Business: 1-10
- Probability of Failure: 1-10
- Regression: 1-5
- Recovery: 1-5
As per the above-mentioned method areas with the score above 25 should be considered as an extremely high-risk area and a near-exhaustive testing needs to be done. So for the above example "Add to Cart" should implement in-depth testing for all test types and exhaustive testing should be done.
Let’s create a matrix for the above example:
Functionality | Impact on Business | Probability of Failure | Regression | Recovery |
Login | 10 | 3 | 1 | 1=15 |
Choose a product with color filter | 5 | 5 | 2 | 2=14 |
Choose a product with price filter | 8 | 5 | 2 | 2=17 |
Add to Cart | 10 | 8 | 3 | 4=25 |
Buy the product | 10 | 7 | 2 | 2=21 |
So as per the score we have “Add to cart” functionality as the foremost contender for the "highest risk area" so now we can prioritize the testing. We can also determine for which functionalities QA team needs to do a near-exhaustive testing.
QA team can streamline the risk mitigation plan by looking at their scores
- Scores 1-5:- Unit testing and reviews.
- Scores 5-10:-Unit testing + black-box testing(regression and high business impact areas)
- Scores 10-15:-Typical test types with limited depth.
- Scores 15-25:-Typical test types with depth in certain test types.
- Scores 25-30:- High-risk areas. Complete coverage and in-depth testing for all test types.
As per the above-mentioned method areas with the score above 25 should be considered as an extremely high-risk area and a near-exhaustive testing needs to be done. So for the above example “Add to Cart” should implement in-depth testing for all test types and exhaustive testing should be done.
More details are available at Test Automation Resources.
Published at DZone with permission of Jefferey Dunn. See the original article here.
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