SHF: Small: INCA: Incremental Analysis of Software Specification for Evolving Systems

SHF：小型：INCA：不断发展的系统软件规范的增量分析

• 批准号: 2204536
• 负责人: Allison Sullivan
• 金额: $ 48.99万
• 依托单位: University of Texas at Arlington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2204536&HistoricalAwards=false
• 关键词: SHF; Small; INCA; Incremental; Analysis

From the cars we drive to online banking, society has become increasingly dependent on software systems. As a result, software reliability remains an important problem to solve. One way developers can improve software reliability is by using software models, which allow developers to define the behavior of their software in the form of mathematical logic. Once a software system is modeled, various tools exist that automatically analyze the model for any issues with the software’s design. Unfortunately, software systems are not static: software is constantly getting updated as new features are added or requirements change. As the system evolves, the software model also needs to be updated and re-analyzed. However, if the change to the model is small, this analysis can be largely redundant. This project looks to improve the efficiency of re-running different types of analysis over an updated model, which increases the feasibility for maintaining models of real world systems. The project involves preparing students for their careers by mentoring graduate students and connecting students to role models in the formal methods community, and the tools developed by the project will improve formal methods education. The project focuses on improving incremental analysis of Alloy models based on three ways users can interact with a model: writing a model, testing a model, and synthesizing a model. First, this project explores improvements to incremental analysis when writing Alloy models, which focuses on how to maximize reuse of past scenarios and how to minimize the new scenario exploration problem. This project investigates a suite of techniques that derive new reuse and exploration strategies based on what component of the model changed and seek to present the impact of the change to the user through disjoint categories of scenarios. Second, this project explores improvements to incremental analysis when testing Alloy models, which includes introducing regression testing to Alloy as well as leveraging first order logic to automatically generate high value tests that reason over the changed portion of the model. Third, this project explores improvements to incrementally synthesizing Alloy models by pausing the sketch to generate tests to refine the synthesis problem and by creating an incremental, parallel sketching environment. In addition to research papers, the project will produce open-source toolsets and benchmarks of incremental models.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.

从我们开车到在线银行的汽车，社会已经越来越依赖软件系统。结果，软件可靠性仍然是要解决的重要问题。开发人员可以提高软件可靠性的一种方式是使用软件模型，该模型允许开发人员以数学逻辑的形式定义其软件的行为。一旦建模软件系统，就会存在各种工具，可以自动分析软件设计问题的模型。不幸的是，软件系统不是静态的：随着添加新功能或要求更改，软件正在不断更新。随着系统的发展，软件模型还需要更新和重新分析。但是，如果对模型的更改很小，则该分析可能在很大程度上是多余的。该项目旨在提高更新模型的重新运行不同类型分析的效率，这增加了维护现实世界系统模型的可行性。该项目涉及通过心理研究生和将学生与正式方法社区中的榜样联系起来为学生做好准备，该项目开发的工具将改善正式的方法教育。该项目的重点是基于用户可以与模型交互的三种方式改进合金模型的增量分析：编写模型，测试模型和合成模型。首先，该项目在编写合金模型时探讨了增量分析的改进，该模型的重点是如何最大程度地利用过去的场景以及如何最大程度地减少新方案探索问题。该项目研究了一系列技术，这些技术会根据模型的哪些组成部分来得出新的再利用和探索策略，并试图通过场景的分离类别向用户展示变更对用户的影响。其次，该项目在测试合金模型时探讨了增量分析的改进，其中包括向合金引入回归测试，并利用一阶逻辑来自动生成高价值测试，这些测试在模型的更改部分中推理了这些原因。第三，该项目通过暂停草图生成测试以完善合成问题并创建增量的，并行的草图环境来探索逐步合成合金模型的改进。除研究论文外，该项目还将生产开源工具集和增量基准。该奖项反映了NSF的法定使命，并通过使用基金会的知识分子优点和更广泛的影响审查标准来评估，以诚实地表示支持。

项目成果

Abstract Alloy Instances

抽象合金实例

• 发表时间: 2023
• 期刊: Formal Methods - 25th International Symposium
• 作者: Ringert, J.O.;Sullivan, A.
• 通讯作者: Sullivan, A.