Tag: AIQ

Technical debt is a term familiar to many development teams, referring to the long-term consequences of taking shortcuts in software development. While sometimes necessary to meet tight deadlines, this debt accumulates over time, leading to increased maintenance costs, reduced productivity, and greater risk of defects. Fortunately, the advent of AI-powered solutions like Appvance IQ (AIQ)

Silos between Development (Dev), Quality Assurance (QA), and Operations (Ops) teams often hinder efficiency, innovation, and speed. Each team has distinct goals: developers prioritize building features, QA ensures quality, and Ops focuses on stability. When these teams operate in isolation, communication gaps can lead to delays, bottlenecks, and product issues. This is where TestOps comes

Security breaches can cripple a company’s operations, damage its reputation, and lead to severe financial repercussions. Cyber threats continue to evolve, becoming increasingly sophisticated as attackers exploit even the smallest vulnerabilities in application code. As businesses accelerate their digital transformations, the need to protect applications from security threats is more critical than ever. A robust

Cybersecurity threats have become more frequent, complex, and sophisticated. Businesses of all sizes are under constant attack from hackers who are always looking for vulnerabilities to exploit. Traditional security measures often fall short because they focus on reacting to threats after the damage has already been done. However, as technology evolves, so must our approach

AI-First Testing Platform Introduces AI Script Generation Improvements, Comprehensive Coverage Mapping and Desktop Designer for Cross-Platform Testing Santa Clara, CA – September 25, 2024 – Appvance, a leader in generative AI for software quality, has announced AIQ 5.2.0, the latest major update of its cutting-edge testing platform. AIQ 5.2.0 introduces industry-first functionality alongside extensive improvements

GenAI-driven testing is a game-changer for software QA. It enables faster timelines, better use of scarce and specialized testing engineers, and much greater coverage and bug discovery. Accordingly, planning a GenAI-driven testing project is very different from planning a traditional testing project. This blog post explores six transformative aspects of AI-driven testing with an eye

Autonomous driving requires a digital roadmap. In similar fashion, autonomous testing requires an application blueprint. The AIQ GenAI-driven testing platform automatically creates such blueprints, which simultaneously direct the autonomous testing that AIQ performs. Blueprints also provide architects and engineers with valuable insight into an application’s health, performance, and, most importantly, coverage. This post describes the

We live in an API driven world. One upshot of this is that many applications must be tested at the API level, a reality not without complications. Fortunately, we at Appvance have engineered a great simplification to the challenges of API testing. It’s called the Appvance Services Workbench and comes as part of our Appvance