5 Test Design Techniques QA Engineers Should Know
Creating effective test suites is significantly simpler for QA professionals who are familiar with test design approaches. We receive instructions on what to test and how to establish test conditions by using a certain technique. In other words, every test design technique contributes to the efficient conversion of the supplied data into test cases. You will discover five often-used test design strategies in this post, which will help you assure complete test coverage and cut down on the amount of time spent on testing operations. A good online QA certification course will provide adequate information about test design techniques.
What is Test Design?
Let’s begin with the fundamentals. We develop test scenarios and lay out the organisation of the project’s testing operations during the test design stage of the quality assurance process. A QA team chooses the most efficient way to increase test coverage.
When And Why Do We Need Test Design?
The primary goal of the test design process is to organise QA procedures to make it simpler to monitor the requirements coverage. Test design is required:
- to reduce the number of tests necessary.
- to validate the product.
- to build tests that aid in detecting major problems.
- to approach testing thoughtfully and avoid resource waste.
What are test design techniques?
These are techniques that facilitate the creation of better test cases. Using test design principles allows you to write fewer tests while still guaranteeing comprehensive requirement coverage. Although there are dozens of test design methodologies available, let’s concentrate on the most common ones:
- Equivalent Class Partitioning.
- Boundary Value Analysis.
- State Transition.
- Pairwise Testing.
- Error Guessing.
Since they attempt to decrease the number of necessary test scenarios, equivalent class partitioning and boundary value analysis are likely the two black-box test design techniques used the most commonly.
1.Equivalent Class Partitioning.
The corresponding class partitioning entails categorising test data into groups of elements that are all somewhat similar. Only if the components are similar and can form a single group does this strategy make sense.
By using this method, we will only test a small number of variables from each category. Note that this does not imply that the remaining values not tested will be bug-free. We can only guess that employing a few of the group’s components will be very illustrative.
When dealing with a lot of incoming data or various variations of the same input, comparable class partitioning is a useful option. If not, it could be prudent to conduct more in-depth studies on the product.
2.Boundary Value Analysis.
The previous method is comparable to the boundary value analysis. Some might even claim that it is based on a similar form of class partitioning.
So what distinguishes the boundary value analysis?
We continue to classify the data into equivalent groups, but we don’t solely test results from one class. In its place, boundary values—those that are on the ‘borders’ of the classes—are checked. Integration testing is a wonderful application of the same principle. During unit testing, we examine smaller components, and at the following level, the unit junctions are where faults are most likely to appear.
A software system’s states at various points in time and stages of usage are represented visually by the state transition. Comparatively speaking, verbal description is harder to comprehend than visual information. As a result, the state transition makes it easier for you to determine the total test coverage. For building test suites for systems with several state variations, this method works well. You should test an event sequence with a limited set of input possibilities.
Of the five test design strategies, paired testing is regarded as being the most challenging and perplexing. And this is for a good cause. The paired testing is based on combinatorics, a branch of mathematics. It allows for the creation of unique pairs and the testing of a substantial amount of incoming data in various combinations, but the calculations could become challenging. You need to accurately match data, combining pairs in a specific way depending on the calculations, in order to cover the greatest number of features with test scripts that will take the shortest amount of time to test.
The most experimental approach of all is error guessing, which is typically used in conjunction with another test design strategy. A QA engineer uses error guessing to make predictions about error locations based on past performance, system expertise, and product specifications. A QA specialist should therefore find places where errors tend to build up and pay closer attention to those areas.
A properly selected test design technique aids in the wise utilisation of QA resources. To get the most thorough coverage, QA engineers frequently need to mix different test design methodologies. A particular project will always determine the best combination. Some experts make their decision regarding a given strategy purely intuitively, rarely making use of the theory. Well, over time, you begin to act in certain ways out of reflex.
Check out the online QA training to learn more.