Design Patterns in Software Architecture: A Critical Analysis of Their Influence on Performance and Maintainability

Abstract

This academic report provides a critical analysis of the influence of design patterns on the performance and maintainability of contemporary software architecture, with a particular focus on distributed environments such as microservices and blockchain. Through a systematic review of the scientific literature, based on articles published between 2020 and 2025 in databases such as Scopus and IEEE Xplore, this research identifies and classifies various patterns according to their structural, transactional, and security purposes. It finds that while the use of patterns like the "FAN" in microservices significantly increases performance and scalability, it also has technical drawbacks in terms of operational complexity and latency. The impact of artificial intelligence and machine learning on automatic pattern detection is also analyzed, highlighting the optimization that can be achieved in application architectural design despite current challenges related to bias and a lack of standardization. Therefore, the research defines guidelines for pattern selection in digital transformation projects and concludes by stating that their correct implementation requires a thorough analysis of quality objectives and the technological context, thus ensuring the system's sustainability.