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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Flagged first, then by citations
1 of the 72 references couldn’t be matched to a known paper.
Research works printed but not linked: 3
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Web service fault diagnosis based on graph convolutional networks
yang, Z., Jia, Z., Cheng, W., Cui, X., Li, J., Qi, J., & Xing, X. (2024) · International Conference on Electronic Information Engineering and Data Processing (EIEDP) · doi:10.1117/12.3032903
Ding, J., Yan, Y., Wang, J., & Chen, T. (2024) · Lecture notes in computer science · doi:10.1007/978-981-97-5672-8_2
Multi-source KPIs’ root cause localization in online service systems
Xia, H., Xu, J., Xiao, B., Jia, H., Gao, C., & Chen, Y. (2024) · International Conference on Networking and Network Applications (NaNA) · doi:10.1109/nana63151.2024.00072
An Anomaly Localization Method for Large-Scale Micro-services
Zhao, W., Xu, B., Ma, C., Zhu, S., Tai, Y., & Li, G. (2024) · International Symposium on Computer Technology and Information Science (ISCTIS) · doi:10.1109/isctis63324.2024.10698988
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Anytime Communication: A Human-AI Collaboration Framework for Causal-Based Root Cause Analysis
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LLM for Automated Root Cause Analysis in Microservices Architectures
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A Framework For Real-Time Root Cause Analysis In Connected Vehicle Iot Data Streams Using Aiops
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Root Cause Analysis for Middleware Issues by Kubernetes Resource Events
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Quality–Latency Benchmarking of Log-Template Retrieval for GenAI-Assisted Operational RCA
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Explainable Root Cause Analysis for Microservices’ Incomplete Logs
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GridScope: Cross-Domain Root-Cause Interpretation for Mission-Critical Facility Power Incidents
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Supporting Root Cause Analysis Decision in Cloud Microservices Using Hybrid Ai Techniques
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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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