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Automating Software Defect Detection Through Machine Learning and LLMs

By Prashant Upadhyay

Automating Software Defect Detection Through Machine Learning and LLMs

By Prashant Upadhyay

0 - Default Title
Description
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.
Product details
Binding:
Paperback
Number of Pages:
428
Release Date:
2025-10-02
Publication Date:
2025-10-02
Publisher:
IGI Global
Languages:
Original: English
ISBN13:
9798337344614
GPSR Manufacturer Reference:
[email protected]
Weight:
800 g
Height:
178 cm
Width:
254 cm
Thickness:
23 cm
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