Making the Most of Your Testing Resources
Most QA teams and others need to be more staffed and able to meet business objectives. So, how will they perform their tasks?
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Because testing is so low-profile at the top of the food chain, many people regard it as another expense center. If companies tighten their belts, testing organizations will have to do more with less (or less). However, most QA teams and others need to be more staffed and able to meet business objectives. So, how are they going to do the task now?
The solution is straightforward. We must consider how to do things more effectively to accomplish more (and better) with what we have. Then, we must go further than our walls to see if new technology and tool developments may enable these changes.
Until recently, testing in the communications business resembled a continent lost in time. Little was done to give more complex testing tools or to assist testing teams in keeping up with development. They had no choice except to rely on manual testing methodologies, construct their own testing tools, and employ outmoded programming languages. The costs of these techniques have been high, ranging from squandered resources and disgruntled employees to ineffective operations.
Manual testing, for example, could be faster, error-prone, and more reliable. With more sophisticated technologies on the horizon, attaining the same quality targets would require either more employees or longer testing cycles, which is a possibility in the current economy. Building tools in-house is only sometimes an option.
Organizations believed this would help them progress toward automation years ago. Instead, it turned out to be unsustainable and a drain on talent. Many of the sharpest testers are now tethered to tool maintenance responsibilities and have little time to test. When it comes to scripting, talent is rare, and scripting languages may be brittle, making maintenance time-consuming and a burden on testers who must spend more time establishing APIs. Not to add that many testers struggle to comprehend each other's scripts and so on.
Testing companies now have additional options because of the availability of new technologies and testing tools.
Here Are Some Ideas on How People Might Start Doing More With Less
First, provide manual testers tools to help them be more productive. You may expect productivity improvements of 50-100% with no issues. Manual testers may now use sophisticated testing technologies to speed up day-to-day testing operations. The idea is to look for tools that are semi-automated and simple to use. They may run a test once and then click a button to rerun it when the new build arrives. Manual testers will save time if the tool can execute the test and create a significant portion of the documentation, including pass/fail metrics.
Consequently, individuals who attempted to share documentation and tests frequently discovered that the amount of work necessary to comprehend them outweighed any time savings. Modern technologies may make semi-automated testing a reality while offering a solid work product and clear, precise documentation that makes test cases and results important down the process.
Second, provide autometers with a platform that allows work items to flow in an assembly line form. This will make creating an automated test case a more efficient process for everyone involved and better communication regarding tests and problems. You may expect a three- to four-fold increase in productivity from your current workforce throughout the quality process. Autometers used to have to start from scratch with textual test plans and data. Furthermore, they had to establish and manage a wide range of libraries to protect their efforts as the product expanded. Because of the variety of tools and frameworks available in the market, autometers may now construct complicated tests more rapidly and efficiently than ever before.
It is a significant breakthrough to establish a pass/fail analysis and rule with a single mouse click rather than a complicated calculation. Such tools can also assist them in creating and maintaining looping, branching, and simplifying. As a result, they can construct automated test scenarios more quickly and eventually be free of time-consuming library management. Better still, they may alter a semi-automated test case created by a manual tester to create a fully automated test case. It also makes global updates simple whenever software or hardware changes, so maintenance takes less time than it would build scripts. Furthermore, even individuals with little programming skills may use this toolkit to develop complicated test scenarios.
Third, find a solution that makes testing and performing regression considerably less time-consuming, allowing you to save up resources. Up to 10-25% of the staff that had been trapped conducting maintenance will be able to resume testing. There are now tools and frameworks that can help regression teams run nightly tests and ensure findings are forwarded to the correct person or system. More significantly, such tools are devoid of programming faults, allowing engineers to run tests that are written in a standard language and are simple to understand.
They may use these frameworks/tools to determine what the feature is intended to accomplish and rapidly determine whether the failure is due to regression system issues or a genuine problem. They may minimize their time running regression testing and triaging test failures if the output is customizable to current reporting or problem systems. They can also make communication with everyone who produces test cases much easier. This should result in increased test coverage, shorter and more consistent time to market, and a superior quality product. It should also permit skilled testers to return to testing.
Although employers demand testing teams to perform more with the same (or less), with the new technology and testing tools available, this is not an insurmountable issue. More significantly, by embracing these advances, testing companies can guarantee that individuals are executing their jobs correctly, resulting in new procedures based on efficiency. This has resulted in enhanced code coverage, shorter testing cycles, and better efficient and effective service delivery.
Published at DZone with permission of David Tzemach. See the original article here.
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