一句话：提出无源码框架 OptDetect，从移动应用二进制检测低优化级别编译问题并量化其影响。
移动应用常出现掉帧、过热和耗电问题，但一个关键瓶颈常被忽视：原生库以低优化级别（O0/O1 而非 O2/O3）编译。由于这类库运行时不产生功能错误，其性能退化在生产应用中难以发现。本文提出 OptDetect，一个无源码框架，通过二进制反汇编、chunk 级分类和加权分数聚合处理混合优化级别，直接从应用二进制检测编译优化问题。OptDetect 在受控数据集上达到 93.0% 准确率，在真实数据集上达到 81.9%。作者将其应用于 830 个 Google Play 热门应用的 21,972 个原生库，发现 30.5% 的库使用低优化级别，影响 91.7% 的应用。对 12 个生产应用的案例研究表明，修复检测出的问题可使商业应用 CPU 指令数减少 10-63%（中位数 20.5%），开源应用减少 15-58%（中位数 32%）；6 个商业应用中有 5 个性能投诉下降、5 个评分上升。进一步调查发现，广泛使用的第三方库本身也以低优化级别分发，某主要仓库中 1,073 个库有 49.7% 存在该问题。这些结果表明，编译器优化问题在移动应用生态中普遍、可无源码检测且具有实际影响。
Mobile apps frequently suffer from frame drops, overheating, and excessive power consumption. While developers optimize algorithms and debug code, a critical bottleneck often goes unnoticed: native libraries compiled with low optimization levels (O0/O1 instead of O2/O3). Because these libraries execute without functional errors, the resulting performance degradation remains hidden in production apps. We present OptDetect, a source-free framework that detects compiler optimization problems directly from app binaries. OptDetect handles mixed optimization levels through binary disassembly, chunk-level classification, and weighted score aggregation, achieving 93.0% accuracy on controlled datasets and 81.9% on real-world datasets. Applying OptDetect to 21,972 native libraries from 830 top-ranked Google Play apps, we find that 30.5% of libraries use low optimization levels, affecting 91.7% of apps. Through case studies on 12 production apps, fixing detected issues reduces CPU instructions by 10-63% (median: 20.5%) for commercial apps and 15-58% (median: 32%) for open-source apps. Performance complaints decrease in 5 of 6 commercial apps, and ratings increase in 5 of 6. Further investigation reveals that widely-used third-party libraries are themselves distributed at low optimization levels, with 49.7% of 1,073 libraries in a major repository exhibiting this problem. These findings show that compiler optimization problems are common, source-free detectable, and practically consequential in mobile app ecosystems.
@inproceedings{abs-2606-23512,
title = {Source-Free Detection and Impact Analysis of Compiler Optimization Problems in Mobile Applications},
author = {Han Hu and Xiaoheng Xie and Bo Sun and Jian Gu and Gang Fan and Li Li},
booktitle = {ASE},
year = {2026},
doi = {10.1145/3832783.3834340}
}