What are the Benefits and Limitations of Pair Testing? Software Quality Assurance & Testing Stack Exchange

June 2022

It can be hard to pass unknown dependencies of variables within the software. It can be used in any type of project regardless of the domain, i.e it is applicable for various fields like agriculture, healthcare, technology etc. It can be used when we can’t implement exhaustive testing due to certain circumstances and the application is in a critical state.

• 6-months after launching a product, I had come to the conclusion that I had built something that nobody wanted.
• Customers can access the online store at anytime and offline store is open only during ‘Business hours’.
• You'll be amazed how easy it is to learn Java and write powerful cross-platform applications when writing your first Java program...
• As a result, the number of test-cases used is lowered while the overall functional coverage does not decrease significantly.
• A piece of software can be delivered with many kinds of plugins and extensions activated.

Still, you do want to test that the website works on both IPv4 and IPv6. Therefore you might set the thoroughness of the parameter IP version to 1 even though the other parameters are set to 2. This means that all pairs of all other parameter values will be covered, but not together with the IP version values.

You need to apply the same logic which was explained in the section to generate test combinations for pairwise testing. Below is the list of the test combinations to be used for cross browser testing based on our pairwise testing example. The section where we discussed about the ‘Pros & Cons of Pairwise testing’ clearly mentioned about the importance of focusing on the test combinations that can give the maximum ROI as far as pairwise testing is concerned.

Let’s take an example of a popular game classic Super Mario, we have so many parameters to work with. We can start with Character Mario – Luigi, we have a positive scenario of jumping over the turtles and a negative scenario of falling by hitting the turtle. I found online some information, but I am still looking for something I could understand. As we can see in this example, the first 12 tests include more than 95% of the pairs. For each added degree of thoroughness, the number of tests is roughly multiplied by some factor.

As a long time tester without much formal education I had the opportunity to recently discover the concept of pairwise testing during a testing certification course. Pairwise testing is a kind of combinatorial testing because it includes all combinations of some number of values in at least one of the tests. If we talk of combining something, we must at least have two things to combine. So, as a kind of combinatorial testing, the lowest thoroughness is 2. If we are running the pairwise tests automatically, we need to import them into a testing tool and set up the expected results. Also, pairwise tests can be a good inspiration for making manual tests.

Is pairwise testing completely automatic?

The mechanism used by pairwise testing to come up with discrete test combinations will be discussed in subsequent sections. Based on that model, the pairwise testing tool will generate a set of filled-out forms. If each resulting car is tested, the confidence that any configuration will in fact work is strengthened. It is also likely that doing such testing will uncover a faulty interaction between some two options that a customer might select. The effectiveness of pairwise testing is neither hypothetical nor only academic.

If pairwise testing isn't turning up defects, consider switching it out for another process, or increasing the size of value sets. Even in an ideal use case, I don't recommend the pairwise testing technique as the sole QA methodology. This could mean manual or automated tests, or a mix of testing execution styles. All-pairs testing greatly reduces testing time, which in turn controls testing costs. The QA team only checks a subset of input/output values -- not all -- to generate effective test coverage. This technique proves useful when there are simply too many possible configuration options and combinations to run through.

I call these the “seeded options” because we often have gaps in our awareness of all the different options that participants consider during the activity of focus. As you’ll see in Step 5, there’s a really important reason why we need to be aware of these gaps — they tend to exist even in the most thoroughly prepared Pairwise Comparison projects. Transitivity allows us to infer the result of the unvoted pairs — ie. But sometimes we have a lot of options to compare, like 50+ different problem statements or 100+ different crowdsourced feature ideas.

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If you’re working with larger option sets or participant populations and still need to do calculations manually, I would recommend using an ELO Rating Algorithm. ELO isn’t as thorough as some other forms of Pairwise Comparison analysis, however it’s relatively easy to understand compared to the much more complex means-based approaches. The best research projects use Pairwise Comparison as the middle step of a broader discovery project. This is transitivity in action — it allows us to understand the wider web of relationships that exists between all options from just a handful of comparisons. Transitivity is one of the two key functions that powers the much more useful form of Probabilistic Pairwise Comparison. Pairwise Comparison is uniquely suited for informing complex decisions where there are many options to be considered.

MODELORDER CATEGORYLOCATIONIMEI VALADITYBOOKING TYPETIMINGSSamsungBuyHyderabadValidIn StoreWorkingOne PlusSellMumbaiInvalidOnlineNon-WorkingOppo–––––As you can see from the above array, Phones can be purchased/sold via online/offline medium. Irrespective of the medium being used, only customers from Hyderabad, and Mumbai can use the application. Customers can access the online store at anytime and offline store is open only during ‘Business hours’. We now work on the different test combinations that are possible with the available data set. Before we had a look at a ‘cross browser testing’ use case; to start with, let us have a look at a rather simpler pairwise testing example. For a given decision agent, if the information, objective, and alternatives used by the agent remain constant, then it is generally assumed that pairwise comparisons over those alternatives by the decision agent are transitive.

In ordinary pairwise test generation, the pairs included (pseudo-)randomly, meaning that any faulty pair is most likely to be included early in the test suite. Thus, a partial test suite of, for example, 95% can be expected to detect 95% of the bugs that a complete pairwise test suite would find. We have already covered the degree of 2, the classic 2-wise or pair-wise tests. A pairwise test suite with a thoroughness of 2 includes each 2 of values in at least one of the test cases. Having a domain expert make tests for a software or hardware system is valuable and highly recommended.

In these cases, we’d still need each participant to spend a lot of time voting in order to get enough data to reliably use transitivity to fill in the gaps. Further down this article, you’ll find real life examples of pairwise comparison projects that I’ve personally worked on explained in more detail. Pairwise Comparison is a common research technique utilized by technology startups. We can use Pairwise testingWhen there are many parameters like different input variables, several configurations. According to a paper published on Combinatorial testing, experimental data shows that nearly 60-95% of issues arise due to interaction between two parameters.

Basics of the pairwise, or all-pairs, testing technique

Though boundary value testing is important to achieve maximum test coverage, it should not happen that testing is performed with incorrect input values. Take the case of testing your web application/website on different devices. Having an input combination of Linux & Internet Explorer may not fetch any results and should be ignored.

We have got ourselves 8 unique combinations for a sample that has 96 combinations. This is how the Pairwise testing technique reduces the number of test cases without compromising the test coverage. In pairwise testing, defect yield ratio may be reduced if a combination is missed. In pairwise testing it is possible to miss the highly probable combination while selecting the test data. Among a bunch of other related techniques of arguable usefulness, pairwise testing was a gem. For example, whether a website is transported with IPv4 or IPv6 will not cause any rendering problems.

A tester analyzes the software to deduce the range of value pairs to test that will reveal the highest percentage of defects without wasting time. Another intuitive tool for performing combinatorial testing is testcover.com https://globalcloudteam.com/ where factors, values, and constraints are simply written in the editor, and test configurations are generated. This tool has an extremely fast and efficient algorithm and can generate about 15 test cases in 1 second.

There are scenarios where you have to perform cross-browser testing of your product and you focus your effort on ‘test combinations that are invalid’ or ‘ignore combinations that matter the most’. Create a browser compatibility matrix to keep your priorities in check. Also, use a web analytics tool to track browsers which bring your the most traffic. Phone of model Samsung can have ‘Buy/Sell’ option and that operation is only possible for cities like Mumbai & Hyderabad. If the IMEI is valid, the necessary operation (Buy/Sell) can go through, else the operation is rejected.

Pairwise testing should be used in scenarios where the application/web-app being developed has huge number of entries and large test configurations. For instance, if you are working on a website/web-application that can be downloaded & used by consumers from across the globe, you need to make sure that it works seamlessly on different browsers/devices/operating systems. Your job is to devise a foolproof cross browser testing strategy so that the application is tested on different combinations definition of pairwise testing that yield best possible test results. The pairwise testing method is highly effective for the cases with the limited number of parameters with multiple possible values. One important application of pairwise comparisons is the widely used Analytic Hierarchy Process, a structured technique for helping people deal with complex decisions. It uses pairwise comparisons of tangible and intangible factors to construct ratio scales that are useful in making important decisions.

What skills are needed to do pairwise testing?

Pairwise testing is based on the ‘coupling effect’, a research which was conducted by Jefferson Offutt in the year 1992. As per this finding, major complicated faults are implicitly tested if the product is explicitly tested for simple faults. For a pairwise testing example, we will consider an e-commerce store (or a store which is an integration of O2O i.e. Online to Offline) which caters to ‘buying & selling’ of mobile phones. Consumers can ‘Buy’ new/old phones from the online medium or from the physical outlet/store. Though you may come up with the possible values for these variable factors, come up with test cases/test suites that can cover all the combinations can be a herculean task. Hence, it becomes critical to come up with a ‘subset of combinations’ which when inputted to the test cases result in achieving the best results i.e. maximum test coverage.

For example, check out this detailed explanation of how multiple algorithms work together to power Probabilistic Pairwise Comparison on OpinionX. The type of integration testing aimed at a pair of components, working together, respectively, the challenges. The same issue will happen when the combination creates repetitive sets.

When is Pairwise Comparison used?

Francisco used this data to calculate the financial impact of each segment’s top problem so that he could pick which one to focus on solving first. Rather than guessing or following a hunch, Francisco had real data to inform his roadmap prioritization and he could easily explain his decisions to the rest of his team. My favorite example of stack ranking in action is actually a story of my own.

All-pairs testing

Pairwise can help us create better test cases with optimum effort without exhausting the system. We can take a real-time example of game testing where combinatorial testing is applied. For a complex application, the outputs for the majority of the test cases may not be a single parameter but multiple factors like state transitions, input parameters, environmental factors, etc. We may have to test cross-browser, cross-platform, cross devices etc.

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Therefore, when presented A and B alone, you are indifferent between apple A and apple B; and you are indifferent between apple B and apple C when presented B and C alone. Using the filled-in matrix , count how many times each item is listed in the matrix, and record the totals in the ranking matrix . Unless you’re an Excel whizz, this approach only works for small, simple projects or children’s math class assignments. Gathering a contact method from your participants helps with this third part of the Discovery Sandwich. If the tester does not understand the interaction between different modules, they might end up with test cases that are not effective. Let’s add music to the input to check whether there is any issue arising with this additional input.You can see how the input set is getting constructed now.

Best of all, it’s completely free to create a stack ranking survey. In my previous example, I told you that a Pairwise Comparison study with 45 options and 150 participants provided the data which turned my failing startup into a success. If I had used the approach above for that study, I would have ended up with 148,500 manual data points to consider. And my Pairwise Comparison study was a fraction of the size of some projects that have been run on OpinionX, which have thousands of participants and hundreds of options being compared.

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