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More enterprises around the world are adopting automation as an effective strategy to enhance business productivity, employee efficiency, and customer satisfaction. This increase in automation is appearing in environments ranging from autonomous vehicles to robots and even in software development. The spectacular breakthrough for automation was made possible mainly by the implementation of two technologies; Artificial Intelligence (AI) and Machine Learning (ML). These technologies are already generating value for businesses across various domains and services, and enterprises across sectors leverage them in an array of processes to personalize digital transformation.
Over the last couple of years, several industries have seen a tremendous digital transformation in their business workflow and operation. To adopt digital solutions, businesses were forced to innovate at lightning speed and integrate software solutions into the existing process. As more companies started to leverage the multiple benefits of software solutions, developers found it extremely challenging to deliver an efficient solution at a faster time to market. While several enterprises adopted the DevOps strategy to reduce delivery cycle time, the technical complexity required to deliver a positive user experience and maintain a competitive edge was not properly addressed—which led to the introduction of compelling innovations.
Also Read: Why Should Software Development Companies Prefer Agile Testing And Not Traditional Software Testing?
Artificial intelligence (AI) in software testing, that mimicked intelligent human behavior for machine learning and predictive analytics, was one such advanced innovation.
The rapid rise of Artificial intelligence (AI) is being leveraged by many software development service providers to make sense of the tremendous availability of data and to take informed decisions based on relevant big data. The traditional or manual strategy of allocating a QA analyst or tester to conduct a comprehensive analysis of every stage in an application development and maintenance (ADM) cycle is now no longer prelevant. Now, businesses can reduce time to market, expense, human intervention, and make sense of all the data, by leveraging AI-based tools to cut through the noise and enable leaders to focus on making informed decisions.
Such tools empower testers to run informed testing strategies, which means that they can manage the complete process from test result generation to re-testing all using the same platform. It has helped businesses in adopting an agile way of working and building, assuring, testing, and delivering change quickly and securely. QA testers are now able to bring together smart and expert systems as well as artificial intelligence with the help of high-end reporting tools. These tools can also help them visualize complex information from test results into simple representations that manual testers can easily process and base decisions on.
There are several benefits of integrating Artificial Intelligence (AI) in Software Testing. Some of the advantages are mentioned below:
We all are by now well aware about the importance of accuracy in testing. Especially in software development, testing and verification are imperative. If not accurately tested software solutions will have several flaws that can adversely affect the entire functionality of the solution. Not only will this lead to customer dissatisfaction and loss in revenue but it can also tremendously affect the brand’s reputation. With the help of AI implemented software automated testing, testers can perform the same or repetitive steps over and over multiple times to ensure that the results are accurate. To perform such repetitive tests manually will take the testers more time and expense but with the help of AI, it can be done quickly with a much lesser expense.
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Every enterprise deploys software solutions for not just a few people but is meant for thousands of people around the globe. Most software developers find it significantly challenging to conduct a controlled software application test with this many amounts of users. Also, the users vary by different methods such as the browsers they use, the operating systems, mobile devices, and much more. Testing on all these different platforms for over a thousand people can be almost impossible when done manually. But, with the help of AI-based automation testing, QA teams can simulate thousands or tens of thousands of virtual systems that represent real-world conditions and users.
With Artificial Intelligence (AI), testers can enhance the overall depth and scope of software tests resulting in the complete improvement of software quality. Unlike manual testing, AI-based software testing can also analyze the comprehensive software solution including the memory, file contents, internal program states, and data tables. Therefore, testers can determine the all-around performance of the application and not just of individual modules.
Also Read: What Is Regression Testing and How To Build An Effective Regression Testing Suite?
Enterprises will have to repeat the entire software testing process even after very minute changes in the code. Testing after each modification can be repetitive and time-consuming as well as expensive. Whereas, AI- implemented automated test scripts can be executed over and over, with zero additional cost at a much quicker pace when compared to manual testing. With the help of artificial intelligence, the software testing time span can be reduced from days to just hours which results in faster time to market and cost savings.
Automated software testing is crucial to application success in today’s competing business environment. At ThinkPalm, we employ top automation tools and testers who implement innovative automation frameworks using the most advanced testing infrastructure. ThinkPalm provides a comprehensive range of test automation services that helps in reducing testing time with significant cost savings, thus enhancing application quality. Through our sophisticated techniques and the help of continuous verification, validation and quality assurance service, we bring in great advantage to all our clients. By implementing such a software testing technique, ThinkPalm helps in increasing the workflow and also satisfying the requirements of the client by providing them with the best services.