EAGER: Improving Robustness of Numerical Software

数值软件在社会中发挥着越来越重要的作用，因此软件中的数值错误可能会带来灾难性的后果。然而，测试数值软件是非常困难的，并且数值错误很难被检测到，因为它们不一定会导致系统崩溃。因此，迫切需要有效和实用的技术或工具来检测和防止这些错误，并提高数值软件的鲁棒性。本项目探索用于测试和分析数值软件的新颖和实用的技术，以检测数值错误，从而提高其鲁棒性。特别是，该项目进行了一系列初步的研究任务，以证明技术的可行性，包括开发一个初始的公共存储库的数字约束和探索技术，以指导，优化，并使用并行路径探索符号执行。本项目的研究通过提供开放源代码工具和数据集供学生和从业人员使用，并供其他研究人员增强，从而增强了教学和研究的基础设施。

Numerical software is increasingly playing a critical role in society, and thus numerical errors in software can have disastrous consequences. However, it is very difficult to test numerical software, and numerical errors are hard to detect because they may not necessarily result in system crashes. There is a strong need for effective and practical techniques or tools to detect and prevent such errors and improve robustness of numerical software.This project explores novel and practical techniques for testing and analyzing numerical software to detect numerical errors in order to improve its robustness. In particular, this project carries out a set of preliminary research tasks to demonstrate the feasibility of the techniques, including developing an initial public repository of numeric constraints and exploring techniques to guide, optimize, and use parallel path exploration in symbolic execution. The research in this project enhances the infrastructure for teaching and research by providing open source tools and data sets for use by students and practitioners, and for enhancement by other researchers.