REAL-TIME OS REGRESSION DETECTION: AUTOMATING PERFORMANCE TESTING FOR PEAK EFFICIENCY

Abstract

To solve the crucial problem of preserving peak performance across various technological environments, from mobile devices to intricate cloud infrastructures, this article explores the development of automatic regression detection in operating systems. The article thoroughly examines contemporary automated testing techniques based on their application at leading global technology enterprises and major cloud service providers. It highlights these systems' architectural elements, implementation techniques, and practical effects at different operational scales. It examines the revolutionary transition from conventional manual testing methods to complex automated frameworks. The article shows how automated regression detection has transformed quality assurance procedures by dramatically increasing detection accuracy, cutting operational overhead, and boosting system reliability in production settings. It offers practical insights for firms looking to adopt or optimize their regression detection capabilities based on a thorough analysis of case studies and industry implementations. Both technical and commercial viewpoints are covered in the article, which provides helpful advice for implementing automation successfully while avoiding typical problems. Emerging techniques and technology that hold promise for improving regression detection skills in the future are given particular focus.