# ProFIPy: Programmable Software Fault Injection as-a-Service

arXiv: https://arxiv.org/abs/2005.04990 · HTML: https://mlsanity.com/paper/2005.04990/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 May 2020.

## Built on by (most cited first, 2 of 2)

- [Enhancing the Analysis of Software Failures in Cloud Computing Systems with Deep Learning](https://mlsanity.com/paper/2106.15182/) (2021)
- [PyResBugs: A Dataset of Residual Python Bugs for Natural Language-Driven Fault Injection](https://mlsanity.com/paper/2505.05777/) (2025)

## Abstract (arXiv)

In this paper, we present a new fault injection tool (ProFIPy) for Python software. The tool is designed to be programmable, in order to enable users to specify their software fault model, using a domain-specific language (DSL) for fault injection. Moreover, to achieve better usability, ProFIPy is provided as software-as-a-service and supports the user through the configuration of the faultload and workload, failure data analysis, and full automation of the experiments using container-based virtualization and parallelization.