The Role of Software Metrics in Quality Assurance and Risk Management
Abstract
Software metrics play a pivotal role in evaluating and improving the quality of software systems. This paper examines various types of software metrics, including complexity metrics, coupling and cohesion metrics, and performance metrics, and their application in quality assurance and risk management. It reviews how these metrics help in identifying potential issues early in the software development process and predict possible risks associated with software failures. By focusing on real-world case studies, the paper highlights the effectiveness of metrics in improving decision-making, tracking progress, and managing risks in large-scale software projects. The paper also discusses the limitations of current metric-driven approaches and proposes ways to integrate them with machine learning techniques for more accurate predictions and enhanced risk management.
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