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Abstract
As a fundamental component of artificial intelligence, Machine Learning (ML) has become deeply embedded within the software industry, transforming conventional methodologies and giving birth to an innovative era of applications and services. This paper investigates the significant influence of ML on the field of software engineering, demonstrating its practical uses, and highlighting its impact on various areas. ML contributes to predicting bugs and automating program repair in software creation and debugging; cybersecurity, where ML-fueled anomaly detection frameworks offer immediate protection against cyber threats. In quality assurance, ML improves testing efficiency, while in cloud computing, it enhances resource management. Despite challenges surrounding data needs and ML model intricacy exist, the increasing incorporation of ML into software engineering signals a future characterized by enhanced efficacy, exactness, and pioneering problem-solving. As ML methodologies continue to improve, they will undoubtedly revolutionize the software industry, nurturing unique applications and redefining existing paradigms in extraordinary ways.
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