Intelligent Testing- A Game Changing Strategy


In a Forrester survey of 2018, 27% of 3228 global developers surveyed told that their organization releases software monthly or faster. The number has reduced significantly from last year where it was 36%. One reason for the decline… Click To Tweet

Today, in order to meet customer requirements effectively, use of Intelligent Testing Tools along with a change in the testing approach has become mandatory. Several startups are coming up with intelligent testing automation tools in the market, some of which claim to provide up to 70% faster testing of products and applications. However, there is no tool that automates test scenarios or generates test data. AI/ML based testing tools leverage the latest technologies such as NLP, Deep Learning, Speech recognition, etc. to change the testing game. Testing is no longer a lengthy process, nor does it requires lengthy scripts. However, the challenge is getting the right quality of data to train the model.

In 2018, according to one of the statistics revealed by Google at the JFrog SwampUp conference in Napa, over 500 million tests are being run per day inside Google’s systems. That’s to accommodate over 4 million builds/day. Click To Tweet

Yet, software testing is stagnant since decades. Traditional testing lack viability, but are still widely used. Some easily relatable cases are:

  • Automation scripts used for writing test scenarios.
  • Verbiage of scripts and scenarios varying from person to person leading to increased complexity.
  • Manually creation of time consuming test data.
  • Lack of 360° view of the application to be tested, making it difficult to identify defects due to change.
  • Impact of any change made is unknown. Especially, selection of the right set of scenarios to execute during a time crunch.
  • Lack of an interactive dashboard and reports for defects and test results.
  • Root cause analysis of defects by analyzing the complete code, which is a tedious job.
“Testing approach has evolved from diagnostic to predictive. A change from predictive to prescriptive is what we should aim at.” Click To Tweet

Modern day testing approach needs to be an integrated one with complete end-to-end intelligent automation. A 360° application overview is essential during testing. Test scenarios and test cases must be created automatically by the tools, ensuring complete coverage from an application perspective. Any changes in the application must be self-healed (automatically get reflected in application overview) along with the analysis of impacted areas (if any) after the change is made. Also, the user dashboard must be interactive with all detailed reports. AI/ML technologies must be used to achieve the highest level of automation, instead of regular automation scripts. A tool which consists of the aforementioned features will be able to fulfill the Cost, Time and Quality equilibrium.


By – Rahul Pandey.
(Product Marketing Manager – Digitate)

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