Data Poisoning: Lightweight Soft Fault Injection for Python
Mohammad Amin Alipour, Alex Groce

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.
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Taxonomy
TopicsSoftware Testing and Debugging Techniques · Parallel Computing and Optimization Techniques · Advanced Malware Detection Techniques
