# Effectively Sampling Higher Order Mutants Using Causal Effect

arXiv: https://arxiv.org/abs/2104.11005 · HTML: https://mlsanity.com/paper/2104.11005/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Apr 2021.

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

- [Applications of statistical causal inference in software engineering](https://mlsanity.com/paper/2211.11482/) (2022)
- [Causal Reasoning in Software Quality Assurance: A Systematic Review](https://mlsanity.com/paper/2408.17183/) (2024)

## Abstract (arXiv)

Higher Order Mutation (HOM) has been proposed to avoid equivalent mutants and improve the scalability of mutation testing, but generating useful HOMs remain an expensive search problem on its own. We propose a new approach to generate Strongly Subsuming Higher Order Mutants (SSHOM) using a recently introduced Causal Program Dependence Analysis (CPDA). CPDA itself is based on program mutation, and provides quantitative estimation of how often a change of the value of a program element will cause a value change of another program element. Our SSHOM generation approach chooses pairs of program elements using heuristics based on CPDA analysis, performs First Order Mutation to the chosen pairs, and generates an HOM by combining two FOMs.