Artificial intelligence has played a major role in how software testing has changed over the past couple of years. It has influenced the changes in designing, execution, and maintenance of test cases. In the last two years, Large Language Models (LLMs) have become the core of attention for QA teams looking to speed up test ...

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The V-model is a popular and widely adopted structure approach in software engineering. It follows a systematic and well-articulated process for building high-quality software. It offers a holistic view of the software development lifecycle (SDLC), combining requirements gathering, design, implementation, testing, and maintenance. The V-model gets its name from its shape. It resembles the letter ...

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Artificial intelligence (AI) has become ubiquitous across industries. AI-powered applications are used for almost all tasks in the digital field. In the software field, a new category of solutions has emerged to support their validation and quality control: AI testing tools. At present, there are countless AI testing tools available in the market, making all ...

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Always turn a negative situation into a positive situation. This is an excellent advice from Michael Jordan. However, we explicitly create negative testing scenarios in software testing to enhance the product quality remarkably. This article elaborates on what positive and negative testing are. Also, we will look into their scenarios, differences, examples, and best practices. ...

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Software testing is always treated with caution by engineering teams. The majority agree that testing is important, yet almost everyone has experienced the annoyance of having to maintain test suites at scale. As software systems become more complex and organizations release updates faster, the older methods of QA don’t keep up. Teams spend weeks creating ...

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Artificial intelligence (AI) systems are becoming remarkably capable. Large Language Models (LLMs) nowadays can generate code, summarize documents, answer complex questions, and power customer-facing applications across industries. With almost every organization racing to deploy AI-powered models, safety has become a primary concern. Many teams deploy model guardrails. But are these enough? If not, how should ...

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The last couple of years have completely overturned the way organizations think about AI compliance. It usually used to be about voluntary standards and best practices that transformed into actual binding laws. And this switch happened fast. Over 1080 AI-based laws were introduced by 50 states across the U.S. Around 118 (or 11%) of them ...

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What if a website you visit could quietly tell your AI assistant what to do? What if an AI tool with access to your emails, files, and browser tabs started following instructions from a stranger instead of you? And how much damage could a hacker cause if they gained control of an AI assistant you ...

The post Claude Chrome Extension Vulnerability: A Security Lesson for Every AI User appeared first on testRigor AI-Based Automated Testing Tool.

This is the age of Large Language Models (LLMs) such as GPT-4, GPT-5, Claude, and Gemini. These and other AI assistants have transformed the way organizations build conversational applications, ranging from customer support chatbots and coding assistants to enterprise automation tools and AI agents. The way these systems behave is heavily influenced by prompts, with ...

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Time is a precious commodity in the software development community. With increasing pressure to release high-quality software at a faster pace, understanding how to prioritize test cases is an important skill before creating a testing strategy. In Agile methodology, software testing needs the relevant, context-dependent tools and a well-defined structure for managing your QA process. ...

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