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The early returns on gen AI for software development

CIO

Generative AI is already having an impact on multiple areas of IT, most notably in software development. Early use cases include code generation and documentation, test case generation and test automation, as well as code optimization and refactoring, among others.

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Calculating The Cost of Software Quality in Your Organization

OverOps

The following is a guest post from Herb Krasner, an Advisory Board Member for the Consortium for IT Software Quality (CISQ) and industry consultant for 5 decades. Demands of the competitive global economy have placed a strong emphasis on quality across the IT industry, and it shows no signs of going away.

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QA Wolf exits stealth with an end-to-end service for software testing

TechCrunch

QA Wolf , a cloud-based platform designed to detect bugs in software, today exited stealth and announced a $20 million funding round led by Inspired Capital with participation from Notation Capital, Operator Partners and Thiel Capital and several angel investors (among them Peter Thiel). Neither, obviously, are very desirable scenarios.

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Leveraging Standardization and Automation to Facilitate DevOps Testing in Multi-Code Environments

CIO

By Milan Shetti, CEO Rocket Software In today’s volatile markets, agile and adaptable business operations have become a necessity to keep up with constantly evolving customer and industry demands. Manual testing also creates barriers to optimizing DevOps.

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Low-Code Development: Create Applications Without Programming Knowledge

Apiumhub

The rise of low-code platforms is revolutionizing how applications are built, deployed, and maintained. This article delves into the world of low-code development, exploring its benefits, key features, leading platforms, use cases, and the future of this transformative approach. What are Low-Code Platforms?

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Quality Management is Risk Management

Xebia

Avoid : This is the most severe of the risk treatment options, and requires organizations to stop performing any tasks or processes that pose a risk. In software development this can be translated into ‘prevent bugs from ending up in the codebase’. This is basically assuming the system is correct until proven otherwise.

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Five Metrics to Track the Performance of Your Quality Assurance Teams and the efficiency of your Quality Assurance strategy

Trigent

Why Quality Assurance and Engineering? Organizations often seek to hasten their long release cycle while maintaining product quality. Additionally, ensuring a superior and connected customer experience is one of the primary objectives for organizations. This is where Quality Engineering comes in.