Parallel testing is a testing approach that allows multiple tests to run concurrently, reducing the time taken to execute test suites.
The purpose of parallel testing is to improve testing efficiency while reducing overall testing time.
Parallel testing can be used in any stage within the software testing life cycle, most effectively when testing a large number of test cases or configurations, testing software across multiple environments, or testing legacy systems or multiple versions of software.
The challenges of parallel testing include test synchronization, test failure management, test complexity - all of which can lead to significant cost.
Get faster feedback without incurring significant expenses with parallel testing with Launchable’s Test Intelligence Platform, a language agnostic CLI that sits on top of your existing testing lifecycles toolsets for faster parallel testing.
The world of software testing is complex. As software engineering teams standardize their CI/CD pipelines, QA teams are tasked with keeping the testing cycle at the same speed as development. Mounting pressure to deliver flawless products in a shorter time frame is a continuous driver for teams to tackle CI/CD’s most significant bottlenecks.
In a recent survey, 75% of DevOps professionals confirmed that more than 25% of productivity is lost to testing. This has led teams to prioritize finding a faster testing methodology.
One of the ways development and QA teams have been doing this is through parallel testing, a popular testing approach that allows multiple tests to run concurrently, reducing the time taken to execute test suites.
While parallel testing may be a successful approach to faster testing, it also has caveats. Understanding the benefits and limitations of parallel testing can help your team advocate for advanced testing approaches.
Parallel testing is a software testing method that tests software across multiple environments and configurations. Teams divide a test suite into smaller parts, enabling simultaneous execution of tests to expedite the execution of bloated test suites. It allows developers to run tests concurrently, dramatically reducing testing time.
The purpose of parallel testing is to get developer feedback faster. Instead of one long test run, the test suite is split and run concurrently, chopping the length of test run times. Standard approaches to splitting tests for parallel testing include by suite, file, class, or tag.
Ultimately, parallel testing aims to improve testing efficiency while reducing overall testing time. QA teams can cover much more ground than before while maintaining similar speeds.
Parallel testing can slot into any stage within your software testing life cycle. Parallel testing is most effective when:
You need to test a large number of test cases or configurations. Standard testing will often take far too long compared to parallel testing, making parallel testing a slam-dunk option.
You need to test software across multiple environments, such as browsers, operating systems, or devices. Regarding these types of comprehensive testing, the fastest way to get it done is via parallel testing.
You are testing legacy systems or multiple versions of your software. With parallel testing, you can run the same tests across different versions to maintain consistency between versions.
Parallel testing involves running multiple test versions simultaneously on the same application or system. This is typically done to compare the results of each test to identify any discrepancies or potential improvements to make. Parallel testing can be helpful in finding defects, tracking changes, and improving performance.
On the other hand, subsetting tests involve selecting a subset of tests from a more extensive suite of tests to run on a specific application or system. This is done to optimize testing time, minimize resource usage, and focus on critical areas of the application. Subsetting tests can help reduce the time and cost associated with testing while providing comprehensive coverage of the application or system.
The critical difference between parallel testing and subsetting tests is that parallel testing involves running multiple tests simultaneously for comparison. In contrast, subsetting tests include selecting a specific subset of tests for optimization purposes.
Naturally, you’ll want to weigh the pros and cons when overhauling your testing process. With parallel testing, you can achieve the following:
Faster Testing Cycles. It allows your developers to execute multiple tests simultaneously, reducing testing time and enabling faster feedback. And with that quicker speed, your QA teams can focus on improving your overall testing process.
Improved Test Coverage. Parallel testing enables teams to test a greater number of scenarios in a shorter amount of time. This helps your dev teams ensure that every edge case gets caught and nothing goes untested.
Save Costs Overall. With it, teams can simultaneously execute tests on multiple machines, reducing additional hardware and infrastructure need. You can also leverage cloud-based testing services, further extending your savings.
Scales With You: You can enable your teams to scale testing efforts quickly by adding more machines to execute tests concurrently. Then, your teams can test more environments while still maintaining speed.
However, as helpful and straightforward as parallel testing appears, there are always potential downsides and limitations. Three of the most common include:
Test Synchronization. With our testing spread across multiple environments and devices, it can take time to keep expansive test suites consistent. It becomes much more challenging as you scale upwards to ensure that every environment and machine runs on the correct software and package versions.
Test Failure Management. You’ll also need to ensure that your tests are adequately monitored in case of failure. With these extensive, expansive tests across many devices, tracking critical issues or losses in your tests can be difficult.
Test Complexity. Since parallel testing requires you to test across so many different environments, your tests must be able to work consistently every time. Teams that don’t have sufficient product knowledge can quickly write tests that will fail in other environments, or devs might chase perfection and end up with a maze of difficulties to unravel.
We all know how impactful AI has become, from an endless Seinfeld episode to an AI lawyer that attempted to fight a traffic ticket. AI plays an increasingly important role in parallel testing, helping speed up testing velocity and increase quality. Teams are tackling parallel testing with AI for:
Test Prioritization: AI-powered algorithms can analyze test results and prioritize tests based on their likelihood of detecting defects
Defect Prediction: AI-powered algorithms can analyze testing data and predict defects before they occur and identify redundant or ineffective tests and remove them from the test suite
Test Result Analysis: AI-powered tools can analyze test results and provide insights into defects and their root causes
Load Testing: AI-powered tools can simulate user behavior under high load conditions, helping teams to identify performance issues before they impact users.
The most significant impact AI can make on parallel testing is speeding up test times without reducing quality or burning through the budget. Launchable is helping teams adopt AI into their existing testing lifecycles and toolsets for faster parallel testing.
Speed Up Parallel Testing without Burning Through Budget with Launchable’s Test Intelligence Platform
Get faster feedback without incurring significant expenses with parallel testing. The Launchable Test Intelligence Platform utilizes advanced AI technology to drastically enhance your team's testing productivity, performance, and cost-effectiveness.
Traditional parallel testing requires considerable financial investment, prompting teams to turn towards dynamic parallelization. Launchable leverages AI to predict which tests may fail and subsequently generates dynamic subsets. This approach enables teams to identify issues earlier while simultaneously minimizing compute costs.
Launchable offers the ability to generate dynamic subsets for tests that are expected to fail. These subsets can be quickly adjusted based on necessary size and confidence thresholds. Smaller subsets can be created for rapid feedback, while larger subsets can be created for greater confidence. By reducing the execution time for each worker, Launchable delivers a dynamic parallel bin at a specified confidence or time threshold.
Parallel testing is a great way to improve your software testing process significantly. However, it does require a not-so-insignificant amount of preparation and complexity, making it a tough solution for some teams.
However, if you’re looking to improve your testing across the board — with or without parallel testing — you should be using Launchable. We support parallel testing out of the box, and you can even take advantage of our Predictive Test Selection to massively speed up your testing.
Launchable uses the power of machine learning and automation to help teams get the most out of their tests. Our platform can analyze your test suites, pick the best tests for the job, and boost efficiency across the board.