# 6GSoft: Software for Edge-to-Cloud Continuum

arXiv: https://arxiv.org/abs/2407.05963 · HTML: https://mlsanity.com/paper/2407.05963/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 21 of its 112 references that are in the map.
- First posted on arXiv 8 Jul 2024.

## Builds on (most cited first, 21 of 21)

- [Large Language Models for Software Engineering: A Systematic Literature Review](https://mlsanity.com/paper/2308.10620/) (2023)
- [MAGIS: LLM-Based Multi-Agent Framework for GitHub Issue Resolution](https://mlsanity.com/paper/2403.17927/) (2024)
- [Semantically Enhanced Software Traceability Using Deep Learning Techniques](https://mlsanity.com/paper/1804.02438/) (2018)
- [Traceability Transformed: Generating more Accurate Links with Pre-Trained BERT Models](https://mlsanity.com/paper/2102.04411/) (2021)
- [Five Facets of 6G: Research Challenges and Opportunities](https://mlsanity.com/paper/2212.07902/) (2022)
- [An Extensive Comparison of Static Application Security Testing Tools](https://mlsanity.com/paper/2403.09219/) (2024)
- [Leveraging Large Language Models for Preliminary Security Risk Analysis: A Mission-Critical Case Study](https://mlsanity.com/paper/2403.15756/) (2024)
- [Beyond Words: On Large Language Models Actionability in Mission-Critical Risk Analysis](https://mlsanity.com/paper/2406.10273/) (2024)
- [The Use of NLP-Based Text Representation Techniques to Support Requirement Engineering Tasks: A Systematic Mapping Review](https://mlsanity.com/paper/2206.00421/) (2022)
- [Software Architecture in Practice: Challenges and Opportunities](https://mlsanity.com/paper/2308.09978/) (2023)
- [Edge to Cloud Tools: A Multivocal Literature Review](https://mlsanity.com/paper/2305.17464/) (2023)
- [On the correlation between Architectural Smells and Static Analysis Warnings](https://mlsanity.com/paper/2406.17354/) (2024)
- [THz-Empowered UAVs in 6G: Opportunities, Challenges, and Trade-Offs](https://mlsanity.com/paper/2201.07886/) (2022)
- [Microservice Architecture Reconstruction and Visualization Techniques: A Review](https://mlsanity.com/paper/2207.02988/) (2022)
- [QCSHQD: Quantum computing as a service for Hybrid classical-quantum software development: A Vision](https://mlsanity.com/paper/2403.08663/) (2024)
- [Disaggregation for Energy Efficient Fog in Future 6G Networks](https://mlsanity.com/paper/2102.01195/) (2021)
- [Workrs: Fault Tolerant Horizontal Computation Offloading](https://mlsanity.com/paper/2305.18219/) (2023)
- [Benchmarks for End-to-End Microservices Testing](https://mlsanity.com/paper/2306.05895/) (2023)
- [End-to-End Test Coverage Metrics in Microservice Systems: An Automated Approach](https://mlsanity.com/paper/2308.09257/) (2023)
- [Evaluating Microservice Organizational Coupling based on Cross-service Contribution](https://mlsanity.com/paper/2309.03552/) (2023)
- [6G Software Engineering: A Systematic Mapping Study](https://mlsanity.com/paper/2405.05017/) (2024)

## Built on by (most cited first, 5 of 5)

- [Integrating LLMs with ITS: Recent Advances, Potentials, Challenges, and Future Directions](https://mlsanity.com/paper/2501.04437/) (2025)
- [On Large Language Models in Mission-Critical IT Governance: Are We Ready Yet?](https://mlsanity.com/paper/2412.11698/) (2024)
- [Autonomic Microservice Management via Agentic AI and MAPE-K Integration](https://mlsanity.com/paper/2506.22185/) (2025)
- [The Invisible Hand of AI Libraries Shaping Open Source Projects and Communities](https://mlsanity.com/paper/2601.01944/) (2026)
- [Making Sense of AI Agents Hype: Adoption, Architectures, and Takeaways from Practitioners](https://mlsanity.com/paper/2604.00189/) (2026)

## Abstract (arXiv)

In the era of 6G, developing and managing software requires cutting-edge software engineering (SE) theories and practices tailored for such complexity across a vast number of connected edge devices. Our project aims to lead the development of sustainable methods and energy-efficient orchestration models specifically for edge environments, enhancing architectural support driven by AI for contemporary edge-to-cloud continuum computing. This initiative seeks to position Finland at the forefront of the 6G landscape, focusing on sophisticated edge orchestration and robust software architectures to optimize the performance and scalability of edge networks. Collaborating with leading Finnish universities and companies, the project emphasizes deep industry-academia collaboration and international expertise to address critical challenges in edge orchestration and software architecture, aiming to drive significant advancements in software productivity and market impact.