The invention addresses the challenges associated with microservices architecture by introducing a novel approach that combines self-contained microservices with centralized assessment methods. While the advantage of microservices lies in their streamlined management and deployment, the decentralized nature of these services often leads to scattered knowledge across the system, making it difficult to comprehend the holistic picture. The technology introduces quantification metrics as indicators for investigating system architecture evolution and reasoning about changes across various versions. The innovation specifically focuses on two holistic viewpoints: inter-service interaction and data modeling perspectives. These perspectives are derived through static analysis of the system's source code. By providing a structured method for assessing changes and understanding the evolution of the system, the technology aims to simplify system maintenance in dynamic environments where substantial changes can impact both individual microservices and the entire system. Overall, this invention aims to enhance the comprehensibility and manageability of evolving microservices architectures. Background: The technology seeks to address the challenges associated with managing and comprehending evolving microservices architectures. The problem lies in the decentralized nature of microservices, which scatters knowledge across the system and makes it challenging to understand the holistic picture, especially as these systems undergo continuous changes. Current solutions often lack centralized assessment methods, leading to increased complexity in system maintenance. This technology stands out by introducing quantification metrics as indicators, offering a systematic approach to investigating system architecture evolution and understanding changes across different versions. Unlike existing approaches, it focuses on holistic viewpoints derived through static analysis of the source code, providing a more structured and comprehensive means of addressing the dynamic nature of microservices. By enhancing the understanding of inter-service interaction and data modeling perspectives, this technology aims to streamline system management and maintenance in the face of ongoing evolution. Applications:
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