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Root Cause Analysis of Failures in Microservices Through Causal Discovery
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In the citing paper
“Metric-based RCA baselines include causal inference-based methods such as RUN, CausalRCA, CIRCA, RCD, MicroCause, EasyRCA, MSCRED, as well as noncausal methods such as BARO, and 𝜖-Diagnosis [6,8,10,14].”
From RCAEval: A Benchmark for Root Cause Analysis of Microservice Systems with Telemetry Data (2025) · cites this paper as [8]
In the citing paper
“For example, existing studies [8,10,13] typically evaluate their methods on only 1-2 systems with 2-3 fault types.”
From RCAEval: A Benchmark for Root Cause Analysis of Microservice Systems with Telemetry Data (2025) · cites this paper as [8]
In the citing paper
“Multi-source RCA baselines include PDiagnose, multi-source BARO, multi-source RCD, multi-source CIRCA [8,10,16].”
From RCAEval: A Benchmark for Root Cause Analysis of Microservice Systems with Telemetry Data (2025) · cites this paper as [8]
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RCAEval: A Benchmark for Root Cause Analysis of Microservice Systems with Telemetry Data
Pham, L., Zhang, H., Ha, H., Salim, F., & Zhang, X. (2025) · Companion Proceedings of the ACM on Web Conference 2025 · doi:10.1145/3701716.3715290 · Cited by 72
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Liu, C., Yang, W., Mittal, H., Singh, M., Sahoo, D., & Hoi, S. C. H. (2023) · arXiv · doi:10.48550/arxiv.2306.11417 · Cited by 4
TORAI: Multi-source Root Cause Analysis for Blind Spots in Microservice Service Call Graph
Pham, L., Ha, H., Zhang, X., & Zhang, H. (2026) · Proceedings of the ACM on software engineering. · doi:10.1145/3808137 · Cited by 10
CausalRCA: Causal Graph-Augmented Retrieval for Root Cause Analysis in Microservice Systems
Kou, J., Qing, Z., Wei, R., Xue, F., Huang, W., & Zhuang, H. (2026) · International Conference on Electronic Information Engineering, Big Data and Computer Technology (EIBDCT) · doi:10.1109/eibdct69742.2026.11566729 · Cited by 2
When LLMs Listen to Experts: Accurate Failure Diagnosis in Operating Systems
Zhao, Y., Zhang, S., Sun, Y., Gu, W., Sun, Y., Wang, L., Shi, L., Huang, C., Yang, G., Zhang, L., et al. (2026) · IEEE/ACM International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP) · doi:10.1145/3786583.3786852 · Cited by 2
Causal Inference for Quantifying Noisy Neighbor Effects in Multi-Tenant Cloud Environments
Schiavo, P. S., Milanezi, J. P. S., Ribeiro, M. R. N., Martínez, V. M. G., Corrêa, J. H., Nogueira, J. M. S., Redígolo, F., Carvalho, T. C., & Silva, F. D. O. (2026) · International Conference on Communications · doi:10.1109/icc59461.2026.11587133 · Cited by 1
CAVIAR: Disentangling Root Causes with an ICA-based VAE for Large-Scale Microservice Systems
Jiang, X., Bi, T., Ma, M., & Wang, P. (2026) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3770854.3780229 · Cited by 1
Wang, J., Chen, R., Wang, Y., Liao, X., Fan, Z., Wu, X., Wu, W., Liu, X., & Zhao, J. (2026) · 2026 IEEE International Conference on Web Services (ICWS) · doi:10.1109/icws72778.2026.00056 · Cited by 1
Zeng, Z., Wang, X., Xu, L., Ye, X., Hu, J. W., Kumbhar, F. H., & Dev, K. (2026) · IEEE Internet of Things Journal · doi:10.1109/jiot.2026.3663198
Ma, L., Peng, Y., Peng, Y., & Peng, K. (2026) · IEEE Sensors Journal · doi:10.1109/jsen.2026.3676619
Conditional Attribution for Root Cause Analysis in Time-Series Anomaly Detection
Mishra, S., Patil, K., Schockaert, C., Stricker, D., & Rambach, J. R. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-37685-5_10
Gaussian Process Based Causal Discovery for Root Cause Analysis in Multivariate Time Series
Kong, H., Shin, J., & Ahn, C. (2026) · International Conference on Computer Research and Development · doi:10.1145/3796263.3796299
An Empirical Study of Energy Efficiency Monitoring for Container-Based Data Exchange Systems
Koufakis, A., Poetoehena, C., van Engers, T., & Oprescu, A. (2026) · IEEE/ACM International Workshop on Green and Sustainable Software (GREENS) · doi:10.1145/3786148.3788628
Graphical Causal Reasoning for Root Cause Analysis in Cloud Networks
Chraim, F., Janzing, D., & Evans, J. (2026) · International Conference on Communications · doi:10.1109/icc59461.2026.11587493
Bridging the Delay: Lag-Aware Spatio-Temporal Causal Inference for Microservice Root Cause Analysis
Zhang, S., Kuang, J., Zhang, Y., Xia, S., Feng, J., Wang, J., Gu, W., Sun, Y., Li, W., Zhang, L., et al. (2026) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3803437.3805219
郑明卓, Wu, G., Zhang, J., Wei, J., Chen, W., Zhu, J., & Liang, Z. (2026) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3803437.3805257
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Sun, H., Tian, P., Zhou, Z., & Liu, A. L. (2026) · International Journal of Data Science and Analytics · doi:10.1007/s41060-026-01211-9
Yu, X., Liu, X., Sun, T., Li, Y., Tang, F., Zhao, M., & Kato, N. (2026) · IEEE Transactions on Emerging Topics in Computing · doi:10.1109/tetc.2026.3713344
Deployment-Aware Causal Root Cause Analysis in Distributed Computing Continuum Systems
Wu, Z., Dong, R., & Malazi, H. T. (2026) · IEEE International Conference on Distributed Computing Systems Workshops (ICDCSW) · doi:10.1109/icdcsw72724.2026.00052
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StaR: Stateful Dynamic-Graph Root Cause Analysis through Memory-Enhanced Causality Discovery
Huang, H., Ng, M. T., Lyu, J., Huang, Y., Yu, G., Wang, Y., & Lyu, M. R.-T. (2026) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3770855.3817863
Wang, X., Wen, Y., He, Y., Xu, H., Zhao, Y., Haddad, M. F. C., & Ma, T. (2026) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3770855.3817978
PORCA: Root Cause Analysis with Partially Observed Data
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Liu, J., & Pi, D. (2026) · Measurement · doi:10.1016/j.measurement.2026.122929
Probabilistic Dynamic Causal Graphs for Root Cause Analysis with Distributional Forecasting
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TD-RCA: Topology-Aware and Dual-Perspective Decoupling for Root Cause Analysis in Microservices
He, S., Tang, B., Wei, M., Xiang, L., & Xie, K. (2026) · International Workshop on Quality of Service · doi:10.1109/iwqos70441.2026.11661074
RCAgentBench: An Agent-Oriented Benchmark for Multimodal Root Cause Analysis in Microservices
Jiang, H., Wang, Z., Nie, X., Gao, D., Li, J., & Pei, C. (2026) · International Workshop on Quality of Service · doi:10.1109/iwqos70441.2026.11661026
CausalTwinOps: Governance-Gated Counterfactual Repair Verification for Enterprise Data Pipelines
Konduru, R. K. (2026) · IEEE Access · doi:10.1109/access.2026.3730237
Why Did the Agent Fail? Root Cause Analysis for Compositional AI Agents
Sharma, R., Mehta, M., Sharma, G., Gupta, D., Rangarajan, T. S., & Rodrigues, J. J. P. C. (2026) · IEEE International Conference on Electro Information Technology · doi:10.1109/eit68936.2026.11670338
Li, B., Tang, L., & Chen, Q. (2026) · IEEE International Conference on Web Services (ICWS) · doi:10.1109/icws72778.2026.00037
SCALER: LLM-Based Cross-Modal Alignment for Microservice Root Cause Analysis
Yang, S., Wang, G., Ming, Z., He, D., Cui, L., Yu, X., & Zhou, X. (2026) · IEEE International Conference on Web Services (ICWS) · doi:10.1109/icws72778.2026.00101
A Lightweight Causal Evidence Pipeline for Root-Cause Localization in Cloud-Native Systems
Dua, M., Gautam, A. S., Chowdhury, R., & Kundu, T. (2026) · IEEE International Conference on Information Reuse and Integration (IRI) · doi:10.1109/iri69576.2026.00015
FoundRoot: Towards Foundation Model for Root Cause Analysis via Structured Deep Thinking
Xie, Z., Li, Z., He, X., Zhang, S., Xu, L., Yang, Y., Zhang, T., Chen, J., Shi, R., & Pei, D. (2026) · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) · doi:10.1145/3744916.3787814 · Cited by 2
Supporting Root Cause Analysis Decision in Cloud Microservices Using Hybrid Ai Techniques
Elambooranan, G., Sood, P., Zaman, M. H. U., Singh, K., & Liu, Y. (2026) · International Conference on Cloud Computing and Big Data Analytics (ICCCBDA) · doi:10.1109/icccbda69573.2026.11676559
Vytla, S. K. (2026) · Engineering Technology & Applied Science Research · doi:10.48084/etasr.20360
Khan, O., & Khamis, A. M. (2026) · IEEE Access · doi:10.1109/access.2026.3742649
Metadata
- Authors
- Ikram, A., Chakraborty, S., Mitra, S., Saini, S., Bagchi, S., & Kocaoglu, M.
- Venue
- Advances in Neural Information Processing Systems 35
- Published
- 2022
- Pages
- 31158-31170
- ISSN
- 1049-5258 (ISSN-L)
- OpenAlex
- W7133209642
- Cited by
- 35
- References
- 0
- Citations by year
- 2026: 35
- FWCI
- 0.00
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- neural information processing systems (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Software System Performance and Reliability
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Computer Networks and Communications › Distributed systems and fault tolerance
- Keywords
- root cause analysis, microservices, causal discovery, fault location, causal inference
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