Tianyin Xu
University of Illinois Urbana-Champaign, IL·Computer Science·Early-career
Large cloud and internet services change their configuration settings hundreds to thousands of times a day. These settings decide how software behaves, from performance tuning to switching on new features.
- Fields
Computer Science
Engineering
- Topics
configuration management
misconfiguration
configuration testing
- Grants
- 1 known grant, through May 2027
What they work on
- Establish the foundations of configuration testing for cloud and datacenter software, a missing piece of how production configuration changes are checked today.
- Develop practical configuration testing techniques that detect failure-inducing configuration changes before deployment to production cloud systems.
- Address key problems in static configuration validation, the standard pre-deployment check, to make it more effective at catching misconfigurations.
- Explore new configuration designs and interfaces that let systems repair and recover from faulty configurations and make misconfigurations less likely.
More about the research
With so many changes, a faulty setting is inevitably a major cause of system failures and service outages. This CAREER project aims to improve existing configuration management techniques. It also explores new system designs that prevent configuration problems from the start.
Why it matters
Faulty configuration changes are a leading cause of cloud outages that disrupt services many people and businesses depend on. Practical testing and validation tools, and systems that can recover from bad settings, could help cloud and datacenter operators catch errors before deployment and reduce outages.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Andre Bauer
Illinois Institute of Technology, IL·Computer Science
Develop the Cosimo co-simulation framework, coupling existing simulators with live orchestration platforms such as Kubernetes to model autoscaling, load balancing and failure recovery.
Remzi Arpaci-Dusseau
University of Wisconsin-Madison, WI·Computer Science
Characterize dependencies across blockchain computing, storage and network resources to build a foundation for classifying faults that cause transaction data loss.
Yang Wang
Ohio State University, OH·Computer Science
Build a multi-dimensional scale-testing platform that can exercise and reproduce many dimensions of system scale efficiently, enabling large-scale unit tests for faults that only manifest in deployments of hundreds or thousands of nodes.
The school
University of Illinois Urbana-Champaign: 41 labs on PI Pages, $907M a year on research, 870 research doctorates a year.
Reach out
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