Author: Anil Polywal

In the fast-paced world of software development, maintaining quality while accelerating delivery is non-negotiable. Two critical pillars of this process are software testing and debugging. Though often used interchangeably, these are distinct activities with unique objectives, methods, and outcomes. Understanding when to test and when to debug can dramatically improve software quality and team efficiency.…

What is Predictive Analytics? Predictive analytics is a branch of advanced analytics that uses historical data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes. In the context of software development and testing, predictive analytics helps teams anticipate potential issues, optimize testing efforts, and improve overall software quality. Predictive Analytics in…

The world of software testing is undergoing a transformative shift. With applications becoming more complex, environments more fragmented, and user expectations higher than ever, traditional testing methods are no longer enough. The rise of artificial intelligence (AI) is reshaping quality assurance (QA) as we know it — ushering in a new era of smart, scalable,…

In the ever-accelerating digital landscape, conventional QA practices are struggling to keep pace with rapid releases, complex user experiences, and sprawling ecosystems of applications and APIs. As organizations push toward hyperautomation and smarter delivery pipelines, the concept of Cognitive QA has emerged as the next frontier in intelligent software testing. Cognitive QA leverages the full spectrum of…

In the digital era of 2025, users expect seamless experiences — whether they’re streaming content, shopping online, or attending a virtual event. Behind these flawless front ends lies a rigorous process of load testing, designed to ensure that applications can scale under real-world pressures. Traditional load testing methods, while useful, often rely on rigid scripts…

As artificial intelligence becomes deeply embedded in everything from healthcare diagnostics to loan approvals and recruitment tools, one issue continues to dominate the conversation: bias. AI systems are only as objective as the data they learn from, and when left unchecked, even the most sophisticated models can perpetuate or even amplify existing inequalities. In 2025, testing…

In a digital world increasingly driven by decentralization and cryptographic integrity, blockchain applications are becoming core components of finance, supply chains, healthcare, and more. These apps promise trust, transparency, and immutability—but these promises are only as strong as the software behind them. As blockchain solutions grow more complex, the testing landscape must evolve to match.…

In 2025, artificial intelligence is not just powering apps — it is the app. From healthcare diagnostics to recommendation engines, ML models are making decisions that influence billions of lives. But while AI builds smarter systems, a critical question remains: Who tests the AI? Traditional software testing has matured over decades. But when it comes to machine learning…

In the fast-evolving world of software development, automation gets most of the spotlight. But amidst the rise of AI scripts, pipelines, and frameworks, there’s one method that still thrives on human insight: exploratory testing. Exploratory testing is the art of simultaneously learning about an application, designing tests, and executing them on the fly. It’s inherently flexible,…

In 2025, mobile apps are no longer just “mobile” — they’re multi-platform ecosystems, expected to run flawlessly across Android, iOS, foldables, tablets, wearables, and even desktop environments. Users demand seamless performance, consistent design, and real-time responsiveness — regardless of the device they use. But achieving that level of cross-platform consistency is far from simple. With so…