Mutation analysis is a useful technique for both practitioners and researchers in examining the strength of a test suite. If the change introduced by a mutant cannot be detected, it may represent a "blind spot" that the test suite failed to consider. However, there are currently no publicly available tools that developers and researchers can use to examine mutants produced by the plethora of existing mutation analysis tools that currently exist for a variety of programming languages (e.g., PIT for Java and Stryker for JavaScript). This is increasingly important given the fact that nowadays, systems are composed of code written in multiple languages. Instead, code editors and diff analysers are used, which are not well optimised for this particular activity. Where tools do exist, they are focused on specific mutation tools/programming languages only. In this paper, we introduce the Marv tool (Mutations Analysis, Review and Visualisation) to specifically address this problem. Marv provides in-code visualisations of mutants and information about them from multiple mutation analysis tools simultaneously. The tool allows users to complete formal textual reviews of each mutant and can export results from all of its supported frameworks in a standardised JSON format. Marv currently includes support for 13 different mutation analysis frameworks that collectively span 12 different programming languages. A screencast demonstrating Marv is available at https://youtu.be/qMjVgXmWrnk.

@inproceedings{paperbot12477,
  title = {Marv: An Interactive Tool for Visualising and Reviewing the Results of Mutation Analysis},
  author = {Daniel Wells and Zalán Lévai and Phil McMinn},
  booktitle = {ASE},
  year = {2026},
  doi = {10.1145/3832783.3834643}
}