# Survey on Models and Techniques for Root-Cause Analysis

arXiv: https://arxiv.org/abs/1701.08546 · HTML: https://mlsanity.com/paper/1701.08546/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Jan 2017.

## Built on by (most cited first, 15 of 15)

- [Hierarchical Graph Neural Networks for Causal Discovery and Root Cause Localization](https://mlsanity.com/paper/2302.01987/) (2023)
- [Reasoning Language Models for Root Cause Analysis in 5G Wireless Networks](https://mlsanity.com/paper/2507.21974/) (2025)
- [A Comprehensive Survey on Root Cause Analysis in (Micro) Services: Methodologies, Challenges, and Trends](https://mlsanity.com/paper/2408.00803/) (2024)
- [Towards AIOps in Edge Computing Environments](https://mlsanity.com/paper/2102.09001/) (2021)
- [AgentTether: Graph-Guided Diagnosis and Runtime Intervention for Reliable LLM Agent Operation](https://mlsanity.com/paper/2607.06273/) (2026)
- [AIOps Solutions for Incident Management: Technical Guidelines and A Comprehensive Literature Review](https://mlsanity.com/paper/2404.01363/) (2024)
- [NetRCA: An Effective Network Fault Cause Localization Algorithm](https://mlsanity.com/paper/2202.11269/) (2022)
- [CHASE: A Causal Hypergraph based Framework for Root Cause Analysis in Multimodal Microservice Systems](https://mlsanity.com/paper/2406.19711/) (2024)
- [Intelligent Cross-Organizational Process Mining: A Survey and New Perspectives](https://mlsanity.com/paper/2407.11280/) (2024)
- [Distribution-free root cause analysis](https://mlsanity.com/paper/2605.21627/) (2026)
- [Conformal Changepoint Localization and Root Cause Analysis with Corrupted Observations](https://mlsanity.com/paper/2607.26481/) (2026)
- [A Survey on Proactive Customer Care: Enabling Science and Steps to Realize it](https://mlsanity.com/paper/2110.05015/) (2021)
- [Disentangled Causal Graph Learning for Online Unsupervised Root Cause Analysis](https://mlsanity.com/paper/2305.10638/) (2023)
- [ORCA: An End-to-End Interactive Copilot for Optimized Root Cause Analysis](https://mlsanity.com/paper/2605.27022/) (2026)
- [StableRCA: Robust Graph-Agnostic Mechanism-Level Root Cause Analysis](https://mlsanity.com/paper/2606.05636/) (2026)

## Abstract (arXiv)

Automation and computer intelligence to support complex human decisions becomes essential to manage large and distributed systems in the Cloud and IoT era. Understanding the root cause of an observed symptom in a complex system has been a major problem for decades. As industry dives into the IoT world and the amount of data generated per year grows at an amazing speed, an important question is how to find appropriate mechanisms to determine root causes that can handle huge amounts of data or may provide valuable feedback in real-time. While many survey papers aim at summarizing the landscape of techniques for modelling system behavior and infering the root cause of a problem based in the resulting models, none of those focuses on analyzing how the different techniques in the literature fit growing requirements in terms of performance and scalability. In this survey, we provide a review of root-cause analysis, focusing on these particular aspects. We also provide guidance to choose the best root-cause analysis strategy depending on the requirements of a particular system and application.