SEFLOct 8, 2020

Test4Enforcers: Test Case Generation for Software Enforcers

arXiv:2010.04258v2
AI Analysis

This addresses the problem of ensuring trust in software enforcers for developers and users, though it appears incremental as it builds on existing test generation methods.

The paper tackles the challenge of validating software enforcers, which modify runtime behavior to ensure correctness policies, by presenting Test4Enforcers, the first approach to generate thorough test suites for assessing their impact without side effects, and demonstrates its implementation in DroidBot for Android apps.

Software enforcers can be used to modify the runtime behavior of software applications to guarantee that relevant correctness policies are satisfied. Indeed, the implementation of software enforcers can be tricky, due to the heterogeneity of the situations that they must be able to handle. Assessing their ability to steer the behavior of the target system without introducing any side effect is an important challenge to fully trust the resulting system. To address this challenge, this paper presents Test4Enforcers, the first approach to derive thorough test suites that can validate the impact of enforcers on a target system. The paper also shows how to implement the Test4Enforcers approach in the DroidBot test generator to validate enforcers for Android apps.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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