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AI to Help Software Testing Productivity

With the competitiveness that exists in today’s market, businesses are on the lookout for any edge they will recover from their competitors. Bolstering software testing productivity with automated testing is beginning to appear to be the logical best place to start for several.

These days, it isn’t uncommon to ascertain companies cause new software all with the assistance of free tools, open-source software and a huge pool of international developers. We’d argue that the barrier to plug entry doesn’t exist anymore and this has an impact on the market itself, where saturation with the most recent software and applications is at an all-time high. In such a competitive landscape, how are you able to ensure your product stands out?

Most seasoned software engineers can vow to the very fact that “traditional QA” was a nightmare to handle for many. This sparked the necessity for newer software testing tools with the newest tech to undertake and ease the pain for said engineers.

To top it all off, the straightforward matter of fact is this: the more complex your software is, the more test cases you’ll get to develop. One deceptively simple feature can warrant tens of test cases, which successively can demand many lines of the latest code for every unique test suit. And maintenance is required on the number of tests too, all the while ensuring that product software is maintained alongside the tests. It also can dawn upon some test engineers that their role during this entire concoction is to archive tests and check out and untangle a hideously intertwined mess of code.

A usual misconception with QA tests is that they are robust. That isn’t the case within the slightest. A minor change to the code can cause the tests to show false results or, in some instances, crash the system entirely. Even something as minor - and insignificant - as changing the font style may end in the tests flagging your software as broken, so bigger changes got to proceed with tons of caution, to mention the smallest amount.

The Issue with Today’s Testing Tools
During development, periodic testing allows developers to explore the software functions, look for bugs, and keep their eyes on the top product. The goal is to line the quality of the software. There's particular freedom during this type of unit testing that feeds into the drive for test automation.

Because of QA testing’s purpose and scope, it's extremely hard to automate in a way that reinforces overall productivity. There are test case management tools that exist, which does help with curating test scripts. But these features alone aren’t enough. A worthwhile QA testing tool needs to:

  • Curate test scripts.
  • Execute scripts and log results.
  • Save individual test runs for replay later.
  • Update test scripts automatically when conditions change.

    Automation and test case management tools capable of the first two tasks are out there today. However, tools that will truly boost software productivity got to do all four. These tools help QA testing by maintaining scripts and recording simple test cases. The thing they can’t help with is automating the testing process and learning from the test results.

  • About The Author:, more technical information on Software Testing Tools and Testing Resources



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