The exponential growth in digitization programs worldwide has led to a rise in demand for high-quality and reliable applications/products. But, given the current Global economy projections, it won’t be an easy year for businesses looking to ride the wave of digital transformation. The IT QA budget is under heavy scrutiny and the QA managers are under tremendous pressure.

As per Gartner’s study, it is a well-established fact that the businesses that took the bull by the horns in the past and invested in software test automation managed to make faster recoveries.

Then why are some decision-makers hesitant in taking the plunge? Is it their budget constraint? 

Little do they realize that this delay cost them dearly in the long run.

Let us examine some of the factors that drive the cost of quality assurance activity thus bloating the IT budgets. Taking pre-emptive measures can salvage the situation before it is too late.

Flaws in test automation

Test automation has proved beneficial for software testing, however, with increasing demand and the need for speed with superior quality has exposed certain chinks in the armor. 

False failures are the bane of test automation since they lead to slowing down the whole testing process. 

Test suite maintenance increasingly becomes a major headache with every test cycle.  Updating test cases based on previous test results, or changes in specifications is a challenging and error-prone activity. 

Test data maintenance isn’t easy either. Any change in specifications may lead to modification in test inputs. Keeping pace with rapid changes and testing multiple test conditions with multiple data combinations is an enormous task.

All these issues add to the overall project cost since the efforts involved are high and there might be delays due to tracking correcting false failures and maintenance activity.

Discovering bugs late in the testing cycle

Sometimes, the bug is discovered very late in the test cycle. Reasons could be any- outdated or limited test data, or unexpected errors due to an untested path because of limited test cases. Discovering bugs late in the testing cycle has a cascading effect on the project quality and schedule, which puts the whole estimated QA cost in peril.

Shift-left testing coupled with the power of AI addresses this issue to a major extent. 

Inadequate test planning 

Impeccable planning is the key to the success of any project. However, the lack of collaboration and communication between business and technical teams may riddle the project with delays. And the cost goes high since time is money.  for more information: Ai based test automation

Ai based test automation or intelligent test automation is a technique or process to automate the repetitive testing tasks using various test automation tools and testing scripts. AI-enabled test set optimizers that build, maintain, run and optimize test assets. Ai based test automation has the capability to heal the test cases by itself thus saving effort and time.

Ai based test automation is the key to continuous testing and has marked benefits in accuracy, scalability, dependability, enhanced test coverage, time, and effort saving. Intelligent automation contributes to the enormous potential for higher productivity, and efficiency in application testing at a lower cost.

Link:https://www.webomates.com/blog/using-ai-based-test-automation-to-optimize-qa-costs/