Name:
ConfErr
Description:
Quantify the resilience of software systems to human-induced configuration errors
Professor — Lab:
George CandeaDependable Systems Lab

Home page:
ConfErr
Layman description:
ConfErr uses human error models rooted in psychology and linguistics to generate realistic configuration mistakes; it then injects these mistakes and measures their effects, producing a resilience profile of the system under test. The resilience profile, capturing succinctly how sensitive the target software is to different classes of configuration errors, can be used for improving the software or to compare systems to each other.
Papers:
Posters:
Project status:
inactive — entered showcase: 2021-11-03 — entry updated: 2022-07-05

Source code:
Personal GitHub - last commit: 2015-03-14
Code quality:
This project has not yet been evaluated by the C4DT Factory team. We will be happy to evaluate it upon request.
Project type:
Application
Programming language:
Java