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The scope of Artificial intelligence AI in software testing is broad and encompasses various aspects of AI system development and deployment. Here are some key areas within the scope of testing in AI: Data Testing: AI systems heavily rely on data for training, testing, and validation. Data testing involves ensuring the quality, completeness, and accuracy of the training data. It includes data preprocessing, data validation, and data augmentation techniques. Model Testing: This involves testing the AI model or algorithm itself. It includes verifying the model’s performance, accuracy, and robustness across different scenarios and input data. Model testing may involve evaluating metrics such as precision, recall, accuracy, F1-score, and analyzing the model’s behavior under different conditions. Performance Testing: AI systems often deal with large volumes of data and complex computations. Performance testing focuses on assessing the system’s speed, responsiveness, scalability, and resource utilization. It helps identify potential bottlenecks, optimize algorithms, and…

Introduction As you look to adopt an automated testing process to meet the rising demand for faster delivery cycles and bug-free releases, it’s vital to assess whether the return on investment (ROI) is worth the change. Before executing, or even thinking of building out an automation strategy, you’ll want to calculate the net gain you’ll see from transitioning. Divide this by the net investment needed to transition (i.e., the tools and resources you use), and you’ll get your ROI for automated testing. The equation to measure ROI of Automated Testing is – Automation ROI = ( Gains- Investment ) / Investment The six ways to Measure ROI of Automated Testing: Start by breaking down the ROI equation into two parts and review how to calculate your Gains as well as your Investments. To establish ROI, first compute the following six costs and reduction in costs. We’ll go through the measurements…

The Covid-19 pandemic has reformed the business landscape for the planet. it isn’t only a health crisis of immense proportions—it’s also an imminent restructuring of the world economic order. Consequently, there are now learnings to think about when pivoting toward the “new normal” which will help organizations thrive within the future. Will this stimulate crowdsourcing post Covid-19? or will the offshoring tradition administrated post pandemic? Offshoring With a market greater than $50B in India alone, the worldwide offshore market has been very successful within the past few years with none reconsideration. How ever there could also be some recent development that emerge thanks to Covid-19 pandemic. Most of the offshoring firms aren’t prepared for this pandemic and also the lockdowns. Especially the offshoring teams don’t seem to be responsive to this work from home scenarios but any how they still manage the performance and client requirement by tackling the operational challenges. the businesses which are more relied on offshoring firms for his or her software testing services are now left within the stagger. Crowdsourcing Crowdsourcing has become a crucial tool for businesses to leverage in an exceedingly sort of areas, including data collection, creating…

Every user in this world expects the software to do wonders and interact with the other application to give uninterrupted service. To meet such requirement companies of all sizes are moving towards API-driven software architecture. Any company can create an application that sends an impulse to a public API and receives a certain response. This enables coherent communication and information exchange between multiple software systems from multiple software companies. What is API Testing? API (Application Programming Interface) enables communication and data exchange between two separate software systems. It also involves testing application programming interfaces directly and as part of integration testing to determine if they meet expectations for functionality, reliability, performance, and security. Ola and Uber’s applications are real-world examples of how APIs are used by developers to integrate functionality developed by other companies. When you book a cab using ola or uber the application doesn’t know how to find the route so it…