Sumedh Meshram

A Personal Blog


Artificial Intelligence in Software Development and Testing

According to Gartner, artificial intelligence will be omnipresent in all spheres of technology and will successfully make its presence prominent among the top investment priority of CIOs by 2020. Going by the figures of the market research firm, the worldwide scope for artificial intelligence in 2019 is approximately $6.36 billion in North America.

Technical masters like Amazon, Facebook, Google, and many others spend a huge sum of money on acquiring AI in software.

AI emerged as an enterprise technology and has changed the outlook of everything, including software development and software testing. It is, therefore, important that we take a minute to look into the role of artificial intelligence in software development and testing.

Higher Level of Precision

It is natural for humans to make errors. Even highly skilled testers sometimes end up making mistakes while performing annual testing. With automated testing, similar steps can be executed with precision every time the task of testing is undertaken and never miss an opportunity to notify specific outcomes. Testers are exempted from ongoing manual examination and they can have a more significant proportion of time to develop new automated software tests and manage chic properties.

Artificial intelligence can help to overcome the drawbacks of annual testing. It is practically unsustainable for leading software or quality assurance (QA) segments to perform a well-managed web app test with more than thousands of users. With the help of automated testing, the user can trigger tens, hundreds, or thousands of optical group of users who can communicate with a network, software, or web-based app.

Massive Support for Developers as Well as Testers

Developers can utilize the shared tests conducted by the computing device to monitor errors instantly before sending it for quality assurance. These tests can function automatically as and when the source code alterations are examined based on which the squad or the app builder can be notified accordingly if a test result turns out to be unsuccessful. Different properties like these help in securing a time for developers and boosts up their self-confidence.

Leveraging the Whole Test Scope

In software testing, with the help of artificial intelligence, the user can leverage the complete coverage and depth of tests, thereby leading to massive enhancement in software quality. Artificial intelligence-driven software testing enables looking into the storage capacity and document content, internal strategy states, and data tables to ascertain whether the software is acting as it should or not. On the whole, test automation can perform more than a thousand various test cases in each test run, offering a scope that would never have been possible through manual testing.

Less Time-Consuming and Helps in Quick Marketing

With the help of software tests being replicated, every time a source code is altered, repetitive manual tests can prove to be time-consuming and tremendously expensive.

On the other hand, once developed, machine learning and testing together can be performed continuously without the need to incur any extra expenses.

The total time taken for software testing can be reduced from two or three days to a few hours, which indirectly helps to save money.

To Wrap Up

Integrating artificial intelligence (AI) with software testing and software development can help to build a society where software can be swiftly examined, diagnosed, and modified.

Artificial intelligence testing will permit high-quality engineering and will decrease the total time taken for examination and development. As a result, it will help to secure time, money, and resources; while allowing testers to pay attention to performing prime activities such as launching quality software.


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