CRII: CSR: Toward Understanding and Automatically Detecting Specious Configuration in Large Systems

软件配置允许用户针对不同需求定制软件系统。如今，系统向用户公开数百个参数以进行自定义配置的情况并不少见。如此高的可定制性是有代价的，因为配置错误是系统故障的主要来源。虽然已经开发了各种解决方案来解决错误配置，但它们主要集中在违反某些正确性标准的无效配置上。不幸的是，许多错误的配置在技术上是有效的，但会导致严重的生产问题，如性能差。这些被称为似是而非的配置。本项目的目标是系统地调查和主动预防似是而非的配置。具体来说，本项目将研究开源和商业系统中的似是而非的配置，以了解其广泛的范围，特点以及它如何影响系统执行。根据这项研究，该项目将设计算法和技术，通过使用静态分析和选择性符号执行来构建参数化影响表，然后使用离线分析数据对其进行增强，从而对配置更改的风险进行建模。基于此模型，本项目将开发一个在线风险评估工具，该工具可以在生产前提醒专家操作员关于似是而非的配置。似是而非的配置经常被引用以损失生产力。这个项目将进一步加深我们对似是而非的配置背后的潜在因素的理解，并帮助从业者减少大规模系统中由配置错误引起的故障。这项研究的结果将被提炼成研究生研讨会和操作系统课程。最终的数据集、软件、出版物和课程材料将在项目完成后的至少五年内保存在一个开源存储库中。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Software configurations allow users to customize a software system for different needs. Today, it is not uncommon for a system to expose hundreds of parameters to users for customizing configuration. Such high customizability comes at a price, as errors in configuration are a major source of system failures. While various solutions have been developed to tackle misconfiguration, they mainly focus on invalid configurations, which violate some correctness criteria. Unfortunately, many misconfigurations are technically valid, yet cause severe production problems such as poor performance. These are called specious configurations. The goal of this project is to systematically investigate and proactively prevent specious configurations.Specifically, the project will study specious configuration from both open-source and commercial systems to understand its broad scope, traits and how it affects system execution. Informed by this study, this project will then design algorithms and techniques for modeling the risk of a configuration change by using static analysis and selective symbolic execution to construct parameterized impact tables and then enhance them with offline profiling data. Based on this model, this project will develop an online risk assessment tool which can alert expert operators about specious configuration before production.Specious configuration is frequently cited for lost productivity. This project will further our understanding of underlying factors behind specious configuration and help practitioners reduce misconfiguration-induced failures in large-scale systems. Results from this research will be distilled into graduate seminars and classes on Operating Systems. The resulting dataset, software, publications and course materials will be maintained in an open-source repository for at least five years beyond the completion of the project.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.