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

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.

Award Number: 2532965
Principal Investigator: Saeid Tizpaz-Niari
Funds Obligated: $208,214
State: IL