一句话：提出面向工业实践的变异体优先级排序方法，指导开发者迭代编写测试，而非计算变异充分性。
变异测试能提供具体的测试目标（变异体）和严格的测试有效性准则，但变异体数量庞大，其中许多既无用也不可操作，导致成本高昂。已有工作多集中于选择有代表性且充分的变异体子集，并衡量对子集变异充分的测试集是否对整个集合同样充分。然而，已知工业应用并不使用甚至不计算变异充分性，而是迭代地向开发者展示极少量变异体作为具体测试目标，引导其编写测试。本文据此提出对变异体进行优先级排序，以服务于这种指导式变异测试流程。摘要未报告具体评估结果。
Mutation testing offers concrete test goals (mutants) and a rigorous test efficacy criterion, but it is expensive due to vast numbers of mutants, many of which are neither useful nor actionable. Prior work has focused on selecting representative and sufficient mutant subsets, measuring whether a test set that is mutation-adequate for the subset is equally adequate for the entire set. However, no known industrial application of mutation testing uses or even computes mutation adequacy, instead focusing on iteratively presenting very few mutants as concrete test goals for developers to write tests.
@inproceedings{KaufmanFAKAJ22,
title = {Prioritizing mutants to guide mutation testing},
author = {Samuel J. Kaufman and Ryan Featherman and Justin Alvin and Bob Kurtz and Paul Ammann and René Just},
booktitle = {ICSE},
year = {2022},
doi = {10.1145/3510003.3510187}
}