一句话：一个开箱即用的统计故障定位工作台，支持多种谓词、覆盖谱和相似系数。
统计故障定位旨在检测与程序失败相关的执行特征，例如某一行是否被执行。然而，研究者往往缺少统一且易用的基础设施来组合、比较和复现不同的统计故障定位技术。本文提出 SFLKit，一个开箱即用的统计故障定位工作台。该框架提供对统计故障定位基本概念的简洁访问，支持五种谓词类型、四种受覆盖启发的谱（如行覆盖谱）以及44种相似系数（如 TARANTULA 或 OCHIAI），用于统计程序分析。SFLKit 以工作台形式降低实验门槛，为系统化评估与比较统计故障定位方法提供支持。
Statistical fault localization aims at detecting execution features that correlate with failures, such as whether individual lines are part of the execution. We introduce SFLKit, an out-of-the-box workbench for statistical fault localization. The framework provides straightforward access to the fundamental concepts of statistical fault localization. It supports five predicate types, four coverage-inspired spectra, like lines, and 44 similarity coefficients, e.g., TARANTULA or OCHIAI, for statistical program analysis.