Data Poisoning: Lightweight Soft Fault Injection for Python

TL;DR

This paper presents a lightweight data poisoning technique for Python programs that allows fault injection with minimal modifications, aiding the evaluation of system sensitivity and robustness.

Contribution

It introduces a novel, low-overhead data poisoning method for fault injection in Python, demonstrated using Dijkstra's algorithm.

Findings

Enables easy fault injection with minimal code changes

Effective in evaluating system sensitivity and robustness

Applicable to various Python-based systems

Abstract

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.