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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2512.21555 |
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| _version_ | 1866915694092746752 |
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| author | Hu, Qi Liu, Jiangchao Yu, Xin Zhang, Lin Jiang, Edward |
| author_facet | Hu, Qi Liu, Jiangchao Yu, Xin Zhang, Lin Jiang, Edward |
| contents | As the complexity of mobile applications grows exponentially and the fragmentation of user device environments intensifies, ensuring online application stability faces unprecedented challenges. Traditional methods, such as static logging and post-crash analysis, lack real-time contextual information, rendering them ineffective against "ghost bugs" that only manifest in specific scenarios. This highlights an urgent need for dynamic runtime observability: intercepting and tracing arbitrary methods in production without requiring an app release. We propose XTrace, a novel dynamic tracing framework. XTrace introduces a new paradigm of non-invasive proxying, which avoids direct modification of the virtual machine's underlying data structures. It achieves high-performance method interception by leveraging and optimizing the highly stable, built-in instrumentation mechanism of the Android ART virtual machine. Evaluated in a ByteDance application with hundreds of millions of daily active users, XTrace demonstrated production-grade stability and performance. Large-scale online A/B experiments confirmed its stability, showing no statistically significant impact (p > 0.05) on Crash User Rate or ANR rate, while maintaining minimal overhead (<7 ms startup latency, <0.01 ms per-method call) and broad compatibility (Android 5.0-15+). Critically, XTrace diagnosed over 11 severe online crashes and multiple performance bottlenecks, improving root-cause localization efficiency by over 90%. This confirms XTrace provides a production-grade solution that reconciles the long-standing conflict between stability and comprehensive coverage in Android dynamic tracing. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_21555 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | XTrace: A Non-Invasive Dynamic Tracing Framework for Android Applications in Production Hu, Qi Liu, Jiangchao Yu, Xin Zhang, Lin Jiang, Edward Software Engineering As the complexity of mobile applications grows exponentially and the fragmentation of user device environments intensifies, ensuring online application stability faces unprecedented challenges. Traditional methods, such as static logging and post-crash analysis, lack real-time contextual information, rendering them ineffective against "ghost bugs" that only manifest in specific scenarios. This highlights an urgent need for dynamic runtime observability: intercepting and tracing arbitrary methods in production without requiring an app release. We propose XTrace, a novel dynamic tracing framework. XTrace introduces a new paradigm of non-invasive proxying, which avoids direct modification of the virtual machine's underlying data structures. It achieves high-performance method interception by leveraging and optimizing the highly stable, built-in instrumentation mechanism of the Android ART virtual machine. Evaluated in a ByteDance application with hundreds of millions of daily active users, XTrace demonstrated production-grade stability and performance. Large-scale online A/B experiments confirmed its stability, showing no statistically significant impact (p > 0.05) on Crash User Rate or ANR rate, while maintaining minimal overhead (<7 ms startup latency, <0.01 ms per-method call) and broad compatibility (Android 5.0-15+). Critically, XTrace diagnosed over 11 severe online crashes and multiple performance bottlenecks, improving root-cause localization efficiency by over 90%. This confirms XTrace provides a production-grade solution that reconciles the long-standing conflict between stability and comprehensive coverage in Android dynamic tracing. |
| title | XTrace: A Non-Invasive Dynamic Tracing Framework for Android Applications in Production |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2512.21555 |