The fintech sector is rapidly transforming, with the financial domain being one of the largest consumers of Quality Engineering (QE) tools and services—accounting for 20-30% according to OpenAI. This segment is also at the forefront of digital transformation, adapting swiftly to emerging changes. As members of the QE community, are we fully aware of the shifts on the horizon?
Universal Testing Cloud is agnostic to the tool, framework or testing platforms you use. A cloud that comes with out of the box integrations and components that are specifically developed with testing in mind, both opensource and commercial.
Prompt engineering is a growing field in AI that’s gaining traction across various domains, including software testing. This article delves into how prompt engineering can revolutionize software testing, enhancing efficiency and accuracy.
Digy360 serves as a Pluggable Continuous Test Orchestration Pipeline, empowering organizations to execute automated tests with every code change in a continuous manner.
Large Language Models (LLMs) are advanced AI tools pivotal in software testing for creating, debugging, and testing code. While models like GPT-4 and Gemini excel in understanding and manipulating software, the challenge lies in customizing LLMs to meet specific software testing needs.
In an era of unprecedented software complexity, the quest for efficient and precise software testing methods has become more critical than ever. Large Language Models (LLMs) like GPT-4, Gemini, and LLaMA2 have made significant contributions across various sectors due to their extensive capabilities. However, the specialized demands of software testing necessitate a more tailored approach—a tool finely aligned with the intricate requirements of an organization’s testing processes.
Proving the return on investment (ROI) for testing tools can be challenging but is crucial for justifying their adoption. Here are some strategies and considerations that can help demonstrate the ROI for testing tools:
In the dynamic landscape of microservices, where decentralized teams operate with distinct tools and frameworks, the absence of end-to-end testing can lead to production incidents and subsequent revenue loss. This blog explores the pivotal role of the CXO Dashboard in addressing these challenges and propelling microservices environments toward enhanced quality and revenue assurance.
When a customer buys DigyDashboard product with CXO feature, flagship feature of DigyDashboard, they would likely leverage its features and capabilities to derive significant value for their teams and projects. Here are the top 12 things or values customers might prioritize with DigyDashboard:
Organizations are increasing their spending on tools in quality engineering. Controls are shifting to technology. 73% of an organization’s spend is on automation for testing.