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<Emerging Trends in QA and Software Testing>

calendar Mar 16, 2022
calendar 8 min read

Technology changes quickly; gone are the days when software testing teams had months to run through quality assurance (QA). Companies are driven to release software faster by demand for new features, and as competition heats up in all sectors, QA automation is critical now. You need end-to-end QA automation from a dedicated software testing company; otherwise, your competitors will be releasing faster, with better quality software that will lead to churn as customers look for software that works dependably. Knowing the emerging QA automation trends is critical in your ability to stay on top of releasing high-quality software at today’s breakneck speeds, and it will assist in finding the best automation testing services from a company that’s on top of the latest QA technology. image Top testing

AI/ML Automation

One of the most promising and exciting QA automation trends is using artificial intelligence and machine learning in automated quality assurance. The advances in AI and ML are moving quickly now, and once real quantum computing becomes available in the next few years, the speed at which the AI/ML automation performs testing will be almost instantaneous across thousands of different tests, with new testing scenarios being determined by the AI without input needed from a QA engineer. The future of AI/ML automation starts with feeding your algorithms with data from historical testing, and as much data as possible is ideal. Your algorithm will be able to start learning what types of code lead to failures and identify those areas for you. AI automation services can also review crash dumps or heap dumps to find the likely culprits and predict where crash dumps may happen in the future. You’ll also be able to take in production traffic data and build synthetic testing based on real customers to be used in your testing environments. This provides you with automated quality assurance that can produce real production load with real user interactions with the system, to see if changes or features will get broken by anything your customers currently use your system for, which one of the big failures in manual testing, you can’t always predict hat customers will do. AI and ML test automation services will save you time, reduce missed tests and human error, widen your test scope, provide real production usage and loads, and a huge range of other benefits as your algorithm gets smarter in the QA testing process. image AI

Visual Automation Testing

Visual automation testing services are one of the new QA automation trends to keep your eye on if you provide a user interface to your customers. Visual automation testing compares expected visual results with what is being output by the application during your testing. What’s even more important about these types of test automation services is that you can run through as many browsers and operating systems, including different versions, as are available through the service. It’s easy for you as a company to say you only support the latest version of 1-2 major browsers, but many large companies don’t allow upgrades as quickly as you’d like, and in some cases may even be locked into browsers that you don’t specifically want to support through manual testing. By using visual automation testing, your frontend developers can commit changes and then quickly test that their changes haven’t impacted the visual appearance of a system across all browsers and can make updates before any code reaches production. It’s a much better user experience not finding bugs, and it’s much faster to test and implement changes while the developer still has time assigned. [add_content]

Salesforce Automation Testing

Salesforce is hugely complex, integrated with a vast range of third-party systems, and with the need to release new Salesforce apps and use continuous delivery methods, it’s challenging for QA teams to stay on top of manual testing or building their own tests. Implementing an effective end-to-end QA process for Salesforce can require the resources of dedicated QA automation services to ensure that you’re covering the entire system and remove the human aspect and manual testing that many are still performing. Instead of reviewing code, Salesforce automation testing works on the user experience and the flow of traffic to see where issues may be. Selenium has historically been one of the most popular quality assurance services, but it had big limitations and relied on QA engineers to capture the process. By implementing neer Selenium apps that have been integrated with AI algorithms, you can ignore use cases and leave it up to the AI is implement new testing and find new ways to use the system. The AI can also be used to build production like traffic to find new use cases to test continuously. image Salesforce

Shopify Automation Testing

Automation testing services are not often implemented for Shopify, but with the ease to implement and the higher earnings people are making with Shopify, it’s making more sense to ensure your Shopify store is working as expected and catching issues well before it starts costing you revenue. Consider if you’re manually testing using one browser, but a change that you just implemented removed the ability for a major browser you don’t test to make purchases or browse your Shopify store, and nobody tells you, and it stays broken for months. As a result, your earnings will decrease, and you won’t know why. Utilizing cross-platform automation to test your Shopify store is becoming easier for non-technical people and much faster. Shopify testing options now include no-code visual test creation, AI-driven test cases, data creation to simulate real customers, and cross-browser testing to ensure your system always works for all customers.

OTT Devices Automation Testing

QA automation services are now becoming possible for OTT devices automation testing; with a huge range of different devices all accessing a variety of streaming services, it’s difficult to implement testing efficiently, and manual testing is not scaleable as more OTT devices hit the market. It’s critical to ensure a smooth signup and user experience with streaming options; there are a huge range available in the market, so any issues and people move on to the next best option that actually works.

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