税务编制软件的变形测试与调试

Saeid Tizpaz-Niari, Morgan Wagner, Shiva Darian, Krystia Reed, Ashutosh Trivedi
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引用次数: 1

摘要

本文提出了一个数据驱动的调试框架,以提高美国报税软件系统的可信度。考虑到此类软件中的错误对其用户的法律影响,确保税务准备软件的合规性和可信度至关重要。开发税务准备系统调试辅助工具的主要障碍是无法获得明确的规范和难以获得oracle。我们认为,由于美国税法遵循先例的法律原则,因此必须将个人纳税人的税务准备软件结果的规格与被认为相似的个人进行比较。因此,这些规范作为需要类似输入提供类似输出的软件上的属性自然可用。受变形测试范式的启发,我们将这些关系称为变形关系,因为它们与结构修改的输入有关。与法律和税务专家合作,我们从美国国税局(IRS)的各种出版物中,包括1040表格(美国个人所得税申报表),596出版物(劳动所得税抵免),附表8812(符合条件的子女和其他家属)和8863表格(教育抵免),阐明了一系列具有挑战性的属性的变形关系。虽然我们的案例研究重点是开源税务准备软件,但提议的框架可以很容易地扩展到其他商业软件。我们开发了一种随机测试用例生成策略,以系统地验证由变质关系指导的税务准备软件的正确性。我们通过使用易于解释的决策树模型可视化地解释软件在可疑实例上的行为,进一步帮助这个测试用例的生成。我们的工具发现了几个严重程度不同的问责错误,从边缘情况下的非稳健行为(当纳税申报表接近于零时的不可靠行为)到软件更新版本中缺失的资格条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Metamorphic Testing and Debugging of Tax Preparation Software
This paper presents a data-driven debugging framework to improve the trustworthiness of US tax preparation software systems. Given the legal implications of bugs in such software on its users, ensuring compliance and trustworthiness of tax preparation software is of paramount importance. The key barriers in developing debugging aids for tax preparation systems are the unavailability of explicit specifications and the difficulty of obtaining oracles. We posit that, since the US tax law adheres to the legal doctrine of precedent, the specifications about the outcome of tax preparation software for an individual taxpayer must be viewed in comparison with individuals that are deemed similar. Consequently, these specifications are naturally available as properties on the software requiring similar inputs provide similar outputs. Inspired by the metamorphic testing paradigm, we dub these relations metamorphic relations as they relate to structurally modified inputs.In collaboration with legal and tax experts, we explicated metamorphic relations for a set of challenging properties from various US Internal Revenue Services (IRS) publications including Form 1040 (U.S. Individual Income Tax Return), Publication 596 (Earned Income Tax Credit), Schedule 8812 (Qualifying Children and Other Dependents), and Form 8863 (Education Credits). While we focus on an open-source tax preparation software for our case study, the proposed framework can be readily extended to other commercial software. We develop a randomized test-case generation strategy to systematically validate the correctness of tax preparation software guided by metamorphic relations. We further aid this test-case generation by visually explaining the behavior of software on suspicious instances using easy-to-interpret decision-tree models. Our tool uncovered several accountability bugs with varying severity ranging from non-robust behavior in corner-cases (unreliable behavior when tax returns are close to zero) to missing eligibility conditions in the updated versions of software.
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