CROC constructs finite-sample valid confidence sets for the root-cause index in multi-stream change detection using conformal p-values under independence and exchangeability assumptions.
Survey on Models and Techniques for Root-Cause Analysis
4 Pith papers cite this work. Polarity classification is still indexing.
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abstract
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.
years
2026 4verdicts
UNVERDICTED 4representative citing papers
A new counterfactual definition of root cause and the identifiable probability of root cause (PRC) for attributing an outcome to its origin.
StableRCA performs mechanism-level root cause analysis via local Markov boundary estimation and conditional distribution shift detection, with exponential convergence guarantees under faithful recovery and non-degenerate shifts.
ORCA is an agent-orchestrated interactive copilot that automates and guides end-to-end causal analysis from workflow selection to report generation across real-world use cases.
citing papers explorer
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StableRCA: Robust Graph-Agnostic Mechanism-Level Root Cause Analysis
StableRCA performs mechanism-level root cause analysis via local Markov boundary estimation and conditional distribution shift detection, with exponential convergence guarantees under faithful recovery and non-degenerate shifts.