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In the rapidly evolving software landscape, ensuring quality at scale is crucial, with global IT spending exceeding $5.1 trillion in 2024. Quality assurance and testing represent significant budget allocations for many companies, emphasizing the importance of quality engineering. Gopinath Kathiresan, a senior quality engineering manager, exemplifies how intelligent automation is transforming software validation processes.
The shift from manual testing to intelligent automation has drastically improved development speed and reliability. Innovations like parallel execution allow thousands of test cases to run simultaneously, significantly reducing validation time. Kathiresan's work in designing scalable automation frameworks is pivotal in integrating automation into the software development lifecycle, enhancing efficiency and quality.
• AI-driven testing is projected to reduce maintenance efforts by 80% by 2026.
• Self-healing automation scripts can adapt to UI changes dynamically.
Intelligent automation enhances software development speed and minimizes human error.
Parallel execution allows simultaneous testing across various environments, improving efficiency.
AI-driven testing utilizes machine learning to predict defects and optimize testing efforts.
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