| Project Overview | This project direction follows recent AIOps and LLM-agent research for cloud and DevOps automation. The work can process logs, metrics, build failures, runbooks, or cloud usage data to support monitoring, incident triage, and operational decision-making. The reference paper, 'A Survey on Large Language Models for Software Engineering', provides the academic base for the topic. Instead of copying the paper abstract directly, this page keeps the same research intent in a safe paraphrased form: the system uses large-language-model capabilities for explanation, reasoning, summarization, and natural-language interaction. The final student implementation can include dataset preparation, model/API integration, dashboard or app interface, result explanation, and a short documentation-ready workflow. |
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| Research Paper Title | A Survey on Large Language Models for Software Engineering |
| Research Paper / PDF Link | Open Paper / PDF |
| Year | 2023 |
| Project Area | Cloud Computing & DevOps |
| Project Type | Cloud Project |
| Required Tools / Software | Docker, GitHub Actions, Python, Flask/FastAPI, Prometheus/Grafana, Cloud APIs, LLM API |
| Main Features / Working Principle | Collect or upload relevant data, preprocess it, apply an AI/ML/LLM/RAG/software workflow, and present the result through a dashboard or application interface for Cloud Computing & DevOps. |
| Expected Output | A working B.Tech project prototype for Cloud Computing & DevOps with input, processing, result display, and explanation/report sections. |
| Possible Add-ons | Admin panel, PDF report export, model comparison, source citations, login system, WhatsApp help button, and deployment on cloud/hosting. |
| Get Help | Get Help on WhatsApp
Message: Hi FE, I need help with "CI/CD Pipeline Failure Prediction Using Machine Learning" in "Computer Science & Engineering" |
This B.Tech Computer Science & Engineering project resource connects a recent research direction with a practical implementation plan, tools, expected output, and possible extensions.
