Collaborative Research: DASS: Assessing Accountability of Tax Preparation Software Systems

随着美国税法的频繁变化，决策支持软件在帮助纳税人、专业人士和国税局（IRS）应对其复杂性方面发挥着至关重要的作用。报税软件的使用量大幅增加，2020年有超过7200万人使用。然而，评估税务软件责任的独立研究有限。该项目面临两个主要挑战：i）根据税法和专家的观点，确保软件的合规性，准确性和公平性，以及ii）提高测试，调试和修补税务软件的可扩展性和精度。该项目特别关注低收入纳税人的免税、抵免和扣除，目的是确保所有纳税人，包括弱势群体的纳税人，只缴纳税法规定的所有税款。虽然预计具有法律的和社会影响的软件应公平并遵守法律，缺乏关于税务软件等法律关键领域预期行为的正式规范，对确保问责制构成了重大挑战。由于美国税法遵循法律的先例原则（遵循先例），本项目提出，这些规范自然存在于特定背景下被视为相似的个人之间的变态关系。项目团队计划1）从美国税法中大量具有挑战性的要求中阐明变形关系，2）通过利用与相关性有关的感知心理学原理自动提取此类变形关系，3）开发用于评估税务软件的工件，该软件使用正式验证技术利用这些关系，以及4）通过实验将税务软件的准确性和对程序正义的感知与人类税务专家的准确性和感知进行比较。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而被认为值得支持。

As the U.S. tax law frequently changes, decision-support software plays a crucial role in helping taxpayers, professionals, and the Internal Revenue Service (IRS) navigate its complexities. The use of tax preparation software has witnessed a significant increase, with over 72 million people utilizing it in 2020. However, there has been limited independent research conducted to assess the accountability of tax software. This project takes on two main challenges: i) ensuring the software's compliance, accuracy, and fairness based on tax law and experts' perspectives, and ii) enhancing scalability and precision in testing, debugging, and patching tax software. The project specifically focuses on exemptions, credits, and deductions for low-income taxpayers, with the aim of ensuring that all taxpayers, including those from vulnerable communities, pay all and only the taxes that tax law prescribes.While it is expected that software with legal and social implications should be fair and compliant with the law, the absence of formal specifications regarding expected behaviors in legal-critical domains like tax software poses significant challenges in ensuring accountability. Since U.S. tax law adheres to the legal doctrine of precedent (stare decisis), this project proposes that these specifications naturally exist as metamorphic relationships between individuals who are considered similar within a given context. The project team plans to 1) explicate metamorphic relations from a large set of challenging requirements in U.S. tax law, 2) automate the extraction of such metamorphic relations by leveraging principles from the psychology of perception pertaining to relateness, 3) develop artifacts for assessing tax software that leverages those relations using formal verification techniques, and 4) experimentally compare the tax software's accuracy and perception of procedural justice to that of human tax experts.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.