The DOI matches its Crossref record; 71 of the 72 references it cites were found in a registry or an index.
Graph-based root cause analysis for service-oriented and microservice architectures
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“Graph-based approaches are widely applied to anomaly detection and root-cause identification in microservices, as they capture the complex interdependencies among services and enable structured analysis of propagation patterns [1].”
From Anomaly detection and root-cause identification in microservices: a survey (2026) · cites this paper as [1]
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“While they provide powerful tools for anomaly detection and root-cause analysis, they face challenges of explainability and data availability in fast-evolving microservice environments [1].”
From Anomaly detection and root-cause identification in microservices: a survey (2026) · cites this paper as [1]
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“While graph-based methods capture structural and causal relationships effectively, they may be overly complex for isolated failures (e.g., single node anomalies) where simpler techniques may be more efficient [1].”
From Anomaly detection and root-cause identification in microservices: a survey (2026) · cites this paper as [1]
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Cites
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- Boyan, 2000, Learning evaluation functions to improve optimization by local search, J. Mach. Learn. Res., 1, 77
- Marvasti, 2013, An anomaly event correlation engine: identifying root causes, bottlenecks, and black swans in it environments, VMware Techn. J., 2, 35
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Cited by
Sorted by citations
Soldani, J., & Brogi, A. (2023) · ACM Computing Surveys · doi:10.1145/3501297 · Cited by 256
MicroHECL: High-Efficient Root Cause Localization in Large-Scale Microservice Systems
Liu, D., He, C., Peng, X., Lin, F., Zhang, C., Gong, S., Li, Z., Ou, J., & Wu, Z. (2021) · 2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP) · doi:10.1109/icse-seip52600.2021.00043 · Cited by 192
Robust Failure Diagnosis of Microservice System Through Multimodal Data
Zhang, S., Jin, P., Lin, Z., Sun, Y., Zhang, B., Xia, S., Li, Z., Zhong, Z., Ma, M., Jin, W., et al. (2023) · IEEE Transactions on Services Computing · doi:10.1109/tsc.2023.3290018 · Cited by 118
Xin, R., Chen, P., & Zhao, Z. (2023) · Journal of Systems and Software · doi:10.1016/j.jss.2023.111724 · Cited by 116
Groot: An Event-graph-based Approach for Root Cause Analysis in Industrial Settings
Wang, H., Wu, Z., Jiang, H., Huang, Y., Wang, J., Köprü, S., & Xie, T. (2021) · IEEE/ACM International Conference on Automated Software Engineering (ASE) · doi:10.1109/ase51524.2021.9678708 · Cited by 105
Metadata
- Authors
- Brandón, Á., Solé, M., Huélamo, A., Solans, D., Pérez, M. S., & Muntés-Mulero, V.
- Affiliations
- Universidad Politécnica de Madrid (ES)
- Corresponding author
- Brandón, Álvaro
- Venue
- Journal of Systems and Software
- Publisher
- Elsevier BV
- Published
- 2020-01
- Volume
- 159
- Pages
- 110432
- ISSN
- 0164-1212 (ISSN-L)
- OpenAlex
- W2980932398
- Cited by
- 121
- References
- 72
- Citations by year
- 2026: 15 · 2025: 17 · 2024: 30 · 2023: 20 · 2022: 16 · 2021: 18 · 2020: 5
- FWCI
- 5.34
- Type
- journal article
- Language
- en
- Open access
- green
- oa.upm.es
- Locations
- Journal of Systems and Software (publishedVersion)
- UPM Digital Archive (Technical University of Madrid) (submittedVersion)
- Funders
- European Commission
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Software System Performance and Reliability
- Physical Sciences › Computer Science › Software › Advanced Software Engineering Methodologies
- Physical Sciences › Computer Science › Software › Software Testing and Debugging Techniques
- Keywords
- root cause analysis, service-oriented architecture, microservices, graph representation, anomaly detection, troubleshooting, software observability, graph comparison, distributed systems
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