The continuous integration and delivery methodology is an excellent way to keep you delivering high-quality products in the shortest possible time. All of this relies on continuous testing and needs a faster test cycle. While the traditional testing methodology – sequential testing – implies a long chain of test jobs and longer time-to-market, parallel testing is the favored procedure for higher test efficiency and faster turnaround time in software deliveries.
What is Parallel Testing?
Parallel testing is an automated testing method that developers and testers can launch various tests against several real device combinations and browser configurations simultaneously. The purpose of parallel testing is to solve the restraints of time by distributing tests over available resources.
For example, if 20 test cases take a sum of 100 minutes to finish, then 10 parallel execution could run 2 test cases each and take the total testing time below 10 minutes. Ideally, if you have adequate resources, say 20 real mobile devices and real browsers for simultaneous execution of 20 test cases, then you’ll be capable to significantly narrow the runtime to 5 minutes.
On the other hand, sequential testing or serial testing is the reverse of parallel testing. In the above case, 20 test cases are performed one after another, and you will require to wait 100 minutes for the test results.
Benefits of Parallel Testing
As we have scraped the surface of what parallel testing is and how it affects the test cycle, there are a few more reasons why you should think of testing in parallel.
Sequential testing is time-consuming, while parallel testing will enable you to distribute invested time by the number of environments. In order to test your application on ten devices, all you require to do is write only ONE script and run it upon all your target devices, cutting your testing time by ten times.
The building, managing, and keeping your own test environment up-to-date can hurt a hole in your pocket. When it arrives to parallel testing, maintenance isn’t a problem anymore — in fact, you lease the required testing environment, always updated. Plus, cloud-based testing grids enable you to run tests at high concurrency, delivering the cost per test significantly lower.
It’s always a good idea to operate your application through as several platform-device-browser combinations as possible so that no defect sneaks in. Parallel testing will get your test coverage to the next level, providing you a vital ROI boost.
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Optimization of Your CI/CD Processes
Parallel testing is the most reliable friend of continuous integration and delivery. By testing in parallel, you can operate tests as soon as developers present new code updates throughout the complete SDLC. Timely reporting and fast feedback in parallel testing will also facilitate better interaction between various departments.
Improvement of Testing Practices
Parallel testing enhances the QA routine in your company. The aim is crystal clear: by testing at high speed, you can test more. This provides your QA team a chance to improve their testing methods and pinpoint bugs faster.
Gradual Transition from Sequential Testing
Transitioning your QA method from sequential to parallel testing is a large undertaking if you try to do it all at once. Beginning small might be your best bet. You can start with the test cases that are most adaptable to the parallel testing environment, providing your engineers sufficient time to adjust the rest of the tests.
Tips for Successful Parallel Testing
Many companies shifted to parallelism only in some cases and avoid parallelizing all their QA methods. Why? Infrastructure limitations, poor test cases data management, data dependencies, and hard-coding are the various common limitations. The good news is there are methods to nail them down and get all the advantages of it properly.
Test in the Cloud-Based Environment
Executing a parallel testing approach using in-house resources is one of the most typical mistakes. Building and managing your own infrastructure is not adequate. It is not just time- and cost-consuming – you won’t be able to get the most of parallel testing where the ability to test at high concurrency is a significant advantage. Also, managing your testing environment up-to-date needs a lot of resources. To this point, it’s a good plan to turn to cloud-based services that enable you to access the necessary devices at any time.
Avoid Dependencies Between Tests
Dependencies between several test cases are a primary cause why transitioning to parallel testing is so challenging for several teams. Easily put, when test cases are reliant on each other, you should operate them in a particular order, which can damage any parallel testing strategy. So, it is important to building your test cases to be atomic, independent from each other. Only then, you will be capable to run them at any time and in any order, delivering your testing methods free of constraints.
Hard-coding is inserting data directly into the source code instead of producing it at runtime. This notion is an opponent of efficient parallelization since it generates dependencies between test cases, mentioned above. It is heavily suggested to avoid hard-coding values when scripting your test cases to assure that each of your tests is self-sufficient and can be operated whenever necessary. Use the data-driven method to configure your test cases when they are operating in parallel.
Manage Test Data Efficiently
Efficient test data management is the solution to strong parallel test execution. But first, you require a strategy. There are two components you might want to append to it: a creational approach(which test data needs) and a cleanup approach(which cleans it up). Still, the only thing that matters is that your approach is adapted to your special case. The following ones are pretty basic, and perhaps that’s what creates these data management approaches so effective:
- elementary approach, which has no creational and cleanup procedures
- refresh-your-data approach, which resets your source code among test executions but has no creational procedure
- selfish data generation approach, which has a creational approach but no clean-up one.
These are the most basic approaches. You can mix and match them to help your own case or explore alternatives, such as producing other data or refreshing particular data.
Build Tests to be Run in Parallel
You don’t want to settle up with a bunch of tests that can’t be operated in parallel right before the release date. Planning accurately from the get-go will save you from dangerous surprises when time’s up or when a deadline is scheduled. Plan your test cases with parallelization in mind should be your to-go. And believe us, it seems harder than it actually is: test cases designed for running in parallel are simpler, shorter, and faster to develop.
Parallel testing can protect your team from delays in delivery without jeopardizing the quality, which makes it better than sequential testing.
With parallelization, you can cut your QA costs, run cases at high concurrency, optimize your CI/CD methods and constantly upgrade your scripts to get more specific results. At the same time, all these advantages are out of reach without an accurate approach. Testing in a cloud-based environment, eliminating data dependencies, avoiding hard-coding, and scripting with parallelization in mind will help you use all the advantages of parallel testing.
At TestUnity, we strive for the highest quality in every project, and our professional QA specialists are ready to ensure it. Contact us if you’re looking for a dedicated team to enhance your product’s quality.
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