Data Poisoning: Lightweight Soft Fault Injection for Python
This is an incremental method for researchers and developers prototyping systems in Python to assess fault tolerance.
The paper tackles the problem of evaluating system sensitivity by introducing data poisoning, a lightweight fault injection technique for Python programs that requires minimal modifications, and demonstrates its application using Dijkstra's Self Stabilizing Ring Algorithm.
This paper introduces and explores the idea of data poisoning, a light-weight peer-architecture technique to inject faults into Python programs. This method requires very small modification to the original program, which facilitates evaluation of sensitivity of systems that are prototyped or modeled in Python. We propose different fault scenarios that can be injected to programs using data poisoning. We use Dijkstra's Self Stabilizing Ring Algorithm to illustrate the approach.