Why Companies Fail at Test Automation

 GUI Test Automation Paradox

Most teams test features before they release them. The reason for the GUI test automation is that there is a regression problem. Changes to one feature might destroy something elsewhere in software, somewhere unpredictable. Uncertainty means the team must retest everything before liberation, which is expensive and time-consuming. Hope with GUI test automation is possible to find the bug faster, allowing fast release. This is something quality W. Edwards Deming legend called "bulk inspection." The aim for the automotive industry in the 1960s and 70s was to change the work process to eliminate bulk inspection. While American companies widely ignore it, Deming's success is part of what allows the Japanese automotive revolution.

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The software team that pursues automation because of quality problems wants to have bulk inspection - and many - all the time. This produces a strange process, where the first team injects defects, then uses testing to find and delete it as soon as possible. Recently than Deming, Elizabeth Hendrickson, recently R & D vice president in the Pivotal, called a problem "Better testing - worse quality?" Hendrickson shows that when testing is a separate activity, namely "safety net," programmers can feel empowered to pass testing. However, other people do the work. Having a magical tool, myth to find problems can add to the problem.

Unless the disability injection rate decreases, the best tooling test can find the majority of previous problems. There will be rework and re-testing involved. The company that pursues GUI test automation without looking loudly on software engineering practices will find diverse results for their efforts. Combined with other classical errors below, this problem can paralyze the test automation project.

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When Deming talks about bulk inspections, it means every part in the car. With software, there is generally a combination of input, state, and unlimited time. Add interaction between components and expanse of extraordinarily open possibilities. Cem Kaner, the main writer to test computer software and retirees Professor of software engineering in Florida Tech, call it the impossibility of complete testing. In the course of the black box software test, Dr. Kaner suggested a main challenge of testing was to choose some of the most powerful tests to run.

The team that pursues automation must have a concept of coverage, along with the rules to understand how many tests will automatically. Another problem is trying to fix all tests simultaneously, from the start, as a project. These projects are not only expensive but because the software changes under test writer, a new test adds to inertia that can slow shipments rather than speed it up.

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When it comes to coverage, three common approaches are to test each complete feature, to make "EPOS" which is a full Walk-Through user, or to make small, easy-to-debug footage testing the core functionality. In our experience, the first two approaches are susceptible to failure. The first, testing all scenarios, will only be too long and intensive resources. As the user interface changes, the test will require maintenance, creating extra work. The second approach, to make "epic", will explore the user's trip. These generally end-to-end scenarios, starting from entering search, add to cart, and checkout, all in one test. These tests do many things, just like real users, and can do complex things ... and they will be fragile. Debugging and tracking problems will be more difficult because more settings may be needed, resulting in defects that need to be repaired and tested to be restarted. Because more time passes, a new defect appears, which will need debugging, repair, run a retest in the cycle that never ends.

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