SHF: Small: Pa3S: Towards Pointer Analysis as a Service

SHF：小型：Pa3S：迈向指针分析即服务

• 批准号: 2006450
• 负责人: Jeff Huang
• 金额: $ 42.5万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2006450&HistoricalAwards=false
• 关键词: SHF; Small; Pa3S; Towards; Pointer

Pointer analysis is a fundamental technique that underpins a wide range of applications in software construction, maintenance and performance optimization, such as compiler optimization, bug detection, security analysis, testing, debugging, verification, program comprehension, and so on. However, despite decades of research there still exists a huge gap between the principled promise of pointer analysis and its practical usage in the real world. Due to the inherent computational complexity of pointer analysis, most production compilers today use only imprecise intra-procedural pointer analyses, and a whole-program interprocedural pointer analysis has rarely been successfully applied to large real-world applications such as the Linux kernel or the Google Chrome browser.This project will create a software as a service (SaaS) platform for pointer analysis, which provides a set of standard APIs for computing pointer analysis and answering pointer analysis queries from users over the Internet, regardless of their applications, execution environments, or physical locations. SaaS provides a promising solution to address the performance and usability challenges of pointer analysis by using a centralized server to compute and memorize the pointer analysis results, and sharing the computation and results effectively among users. To realize such a platform, this project will develop new distributed incremental pointer-analysis algorithms, new APIs for pointer-analysis queries, and evaluations on large-scale applications with compiler optimizations and bug detection. If successful, these techniques will make pointer analysis more scalable and more widely applicable to large complex code bases, eventually leading to faster and more secure end-user software products.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.

指针分析是一种基础技术，它支持软件构建、维护和性能优化中的广泛应用，例如编译器优化、错误检测、安全性分析、测试、调试、验证、程序理解等等。然而，尽管经过了几十年的研究，指针分析的原则承诺和它在现实世界中的实际应用之间仍然存在着巨大的差距。由于指针分析固有的计算复杂性，今天大多数生产编译器只使用不精确的过程内指针分析，整个程序的过程间指针分析很少成功地应用于大型实际应用程序，如Linux内核或谷歌Chrome浏览器。该项目将创建一个用于指针分析的软件即服务（SaaS）平台，该平台提供一组标准api，用于计算指针分析并通过互联网回答用户的指针分析查询，而不管他们的应用程序、执行环境或物理位置如何。SaaS提供了一个很有前途的解决方案，通过使用集中式服务器计算和存储指针分析结果，并在用户之间有效地共享计算和结果，来解决指针分析的性能和可用性挑战。为了实现这样一个平台，本项目将开发新的分布式增量指针分析算法，新的指针分析查询api，以及对大规模应用程序进行编译优化和bug检测的评估。如果成功，这些技术将使指针分析更具可伸缩性，并更广泛地应用于大型复杂代码库，最终导致更快、更安全的终端用户软件产品。该奖项反映了美国国家科学基金会的法定使命，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。