Kód: 49880468
As software systems grow in complexity and scale, ensuring their reliability and quality becomes challenging. Traditional methods of defect detection are time-consuming, prone to errors, and inadequate for identifying issues. To a ... celý popis
Angličtina
Nákupem získáte 478 bodů
Anotace knihy
As software systems grow in complexity and scale, ensuring their reliability and quality becomes challenging. Traditional methods of defect detection are time-consuming, prone to errors, and inadequate for identifying issues. To address these limitations, the integration of machine learning (ML) techniques and large language models (LLMs) emerges as a transformative approach in automating software defect detection. ML algorithms can learn from historical bug data to predict vulnerabilities, while LLMs can detect anomalies with high accuracy. This convergence holds the potential to improve automation, software engineering, and defect detection, while introducing new challenges in interpretability, data bias, and model reliability that require further exploration. Automating Software Defect Detection Through Machine Learning and LLMs explores how cutting-edge technologies like machine learning (ML) and large language models (LLMs) transform software detection. It examines how these technologies enhance accuracy, scalability, and efficiency in identifying and mitigating software defects. This book covers topics such as algorithms, fraud detection, and software engineering, and is a useful resource for engineers, security professionals, academicians, researchers, and computer scientists.
Parametry knihy
Zařazení knihy Knihy v němčině Naturwissenschaften, Medizin, Informatik, Technik Informatik, EDV Informatik
4779 Kč
Angličtina
Osobní odběr Praha, Brno a 47512 dalších
Copyright ©2008-26 nejlevnejsi-knihy.cz Všechna práva vyhrazenaSoukromíCookies
Vrácení do měsíce
571 999 099 (8-15.30h)Nákupní košík ( prázdný )