

Review of Software Testing Models and Performance Optimization Techniques
Abstract
Software testing is still a vital activity to ensure the quality, reliability, and security of software. This review paper discusses current software testing models and performance optimization strategies. The review is based on various frameworks and tools and emphasizes automation and AI advancements. Key models include Waterfall, V-Model, Agile, and Spiral, each of which has specific characteristics and uses. Optimization techniques, such as fault localization and combinatorial testing, are also assessed. Scalability and AI model biases are identified as challenges and future research ideas in intelligent testing frameworks are presented.
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