Understanding and Detecting Platform-Specific Violations in Android Auto Apps
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
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2025
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| _version_ | 1866911400172978176 |
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| author | Fakorede, Moshood Farooq, Umar |
| author_facet | Fakorede, Moshood Farooq, Umar |
| contents | Despite over 3.5 million Android apps and 200+ million Android Auto-compatible vehicles, only a few hundred apps support Android Auto due to platform-specific compliance requirements. Android Auto mandates service-based architectures in which the vehicle system invokes app callbacks to render the UI and handle interactions, which is fundamentally different from standard Activity-based Android development. Through an empirical study analysis of 98 issues across 14 Android Auto app repositories, we identified three major compliance failure categories: media playback errors, UI rendering issues, and voice command integration failures in line with mandatory requirements for integrating Android Auto support. We introduce AutoComply, a static analysis framework capable of detecting these compliance violations through the specialized analysis of platform-specific requirements. AutoComply constructs a Car-Control Flow Graph (CCFG) extending traditional control flow analysis to model the service-based architecture of Android Auto apps. Evaluating AutoComply on 31 large-scale open-source apps, it detected 27 violations (13X more than Android Lint), while no false positives were observed, achieving 2X faster analysis. Developers have acknowledged 14 of these violations with 8 fixes already implemented, validating AutoComply's practical effectiveness. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_04003 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Understanding and Detecting Platform-Specific Violations in Android Auto Apps Fakorede, Moshood Farooq, Umar Software Engineering Programming Languages Despite over 3.5 million Android apps and 200+ million Android Auto-compatible vehicles, only a few hundred apps support Android Auto due to platform-specific compliance requirements. Android Auto mandates service-based architectures in which the vehicle system invokes app callbacks to render the UI and handle interactions, which is fundamentally different from standard Activity-based Android development. Through an empirical study analysis of 98 issues across 14 Android Auto app repositories, we identified three major compliance failure categories: media playback errors, UI rendering issues, and voice command integration failures in line with mandatory requirements for integrating Android Auto support. We introduce AutoComply, a static analysis framework capable of detecting these compliance violations through the specialized analysis of platform-specific requirements. AutoComply constructs a Car-Control Flow Graph (CCFG) extending traditional control flow analysis to model the service-based architecture of Android Auto apps. Evaluating AutoComply on 31 large-scale open-source apps, it detected 27 violations (13X more than Android Lint), while no false positives were observed, achieving 2X faster analysis. Developers have acknowledged 14 of these violations with 8 fixes already implemented, validating AutoComply's practical effectiveness. |
| title | Understanding and Detecting Platform-Specific Violations in Android Auto Apps |
| topic | Software Engineering Programming Languages |
| url | https://arxiv.org/abs/2503.04003 |