Software Design Pattern Model and Data Structure Algorithm Abilities on Microservices Architecture Design in High-tech Enterprises
November 05, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Jun Cui
arXiv ID
2411.04143
Category
cs.SE: Software Engineering
Cross-listed
cs.CL
Citations
1
Venue
arXiv.org
Last Checked
5 months ago
Abstract
This study investigates the impact of software design model capabilities and data structure algorithm abilities on microservices architecture design within enterprises. Utilizing a qualitative methodology, the research involved in-depth interviews with software architects and developers who possess extensive experience in microservices implementation. The findings reveal that organizations emphasizing robust design models and efficient algorithms achieve superior scalability, performance, and flexibility in their microservices architecture. Notably, participants highlighted that a strong foundation in these areas facilitates better service decomposition, optimizes data processing, and enhances system responsiveness. Despite these insights, gaps remain regarding the integration of emerging technologies and the evolving nature of software design practices. This paper contributes to the existing literature by underscoring the critical role of these competencies in fostering effective microservices architectures and suggests avenues for future research to address identified gaps
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted