QA.tech is an AI-powered tool for QA testing, empowering engineers to be more productive by autonomous testing of applications. No more waiting for feedback from your QA team or stakeholders. Get instant feedback on your work, with less bugs, improved quality and faster time-to-market.
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QA Tech's answer
QA.tech leverages AI to blend the expertise of QA engineers with the efficiency of automated testing, streamlining time-to-market, reducing expenses, and enhancing user satisfaction. By simulating human testing at automated speeds, we offer a comprehensive repository of best practices and usage patterns. Our services encompass identifying release-blocking issues and recommending code fixes and improvements of identified issues.
QA Tech's answer
QA.tech emerged from the recognition that traditional QA testing, while essential, is often perceived as time-consuming and monotonous. Developers prefer focusing on product development rather than writing and maintaining tests. To address this challenge, QA.tech was founded with the mission of automating QA testing using AI technology, freeing up developers' time and reducing errors. Backed by a $1 million pre-seed funding round, QA.tech aims to revolutionize software testing by combining the efficiency of end-to-end tests with the precision of manual testing. The founding team, comprising entrepreneurs and engineers with vast experience in technology and entrepreneurship, is dedicated to making QA testing more efficient and accessible for businesses across the globe.
QA Tech's answer
The primary audience for QA.tech includes software developers, CTOs, QA engineers at companies which provide a website application and are looking to streamline their quality assurance processes. These professionals are seeking efficient and effective solutions to automate testing, reduce errors, and accelerate time-to-market for their software products. Additionally, QA.tech may also appeal to product managers and other stakeholders responsible for overseeing software development projects and ensuring product quality.
Based on our record, Robot framework seems to be more popular. It has been mentiond 32 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Fixing a bug is incomplete without preventing its recurrence. Root cause analysis (RCA), coupled with regression testing and documentation, ensures long-term reliability. Antony Marceles, Founder of Pumex Computing, emphasizes, โFixing a bug is only part of the solution, preventing it from happening again is the real goal.โ Marcelesโ team uses regression tests via Robot Framework and code reviews with Gerrit to... - Source: dev.to / 5 months ago
Documentation is your best friend. It provides comprehensive guides, examples, and API references to help you navigate the library effectively. Here you can access it, as well as the Robot Framework documentation. - Source: dev.to / 10 months ago
The Robot Framework is an acceptance testing tool that is easy to write and manage due to its key-driven approach. Let us learn more about the Robot Framework to enable acceptance testing. - Source: dev.to / over 1 year ago
Well, I work with software quality and despite not having a strong foundation in automation, one fine day I decided to make a change. I have been working with Robot Framework for a few months - and that's when I got a taste of the power of python. Some time later, I dabbled a little with Cypress and Playwright, always using javascript. - Source: dev.to / almost 2 years ago
I've used Lua/Busted in a data-heavy environment (telemetry from hospital ventilators). I've also used robot: https://robotframework.org/. Source: over 2 years ago
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