用于分析动态数据结构的内存图

Vineet Singh, Rajiv Gupta, Iulian Neamtiu
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引用次数: 9

摘要

内存图对于理解使用动态分配数据结构的程序的行为非常有用。我们提出了一种新的记忆图表示方法mg++,以及一种记忆图构建算法,极大地提高了记忆图的实用性。首先,除了捕获动态构造的数据结构的形状外,mg++还捕获它们在程序执行时的演变过程,并记录在其演变过程中起作用的源代码语句,以帮助调试。其次,mg++捕获内存分配器执行的操作的历史记录。这在调试内部管理存储的程序或在理解程序行为需要检查内存分配器操作的情况下非常有用。我们的基于二进制仪器的mg++构造算法不依赖于内存分配器函数的知识或符号表信息。我们的算法适用于自定义内存分配器以及程序内内存管理。研究实际程序的时间和空间效率的实验表明,mg++表示具有空间效率,mg++构造算法的时间开销是可行的。我们证明了mg++在故障定位和分析二进制文件以检测堆缓冲区溢出攻击方面是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MG++: Memory graphs for analyzing dynamic data structures
Memory graphs are very useful in understanding the behavior of programs that use dynamically allocated data structures. We present a new memory graph representation, MG++, and a memory graph construction algorithm, that greatly enhance the utility of memory graphs. First, in addition to capturing the shapes of dynamically-constructed data structures, MG++ also captures how they evolve as the program executes and records the source code statements that play a role in their evolution to assist in debugging. Second, MG++ captures the history of actions performed by the memory allocator. This is useful in debugging programs that internally manage storage or in cases where understanding program behavior requires examining memory allocator actions. Our binary instrumentation-based algorithm for MG++ construction does not rely on the knowledge of memory allocator functions or on symbol table information. Our algorithm works for custom memory allocators as well as for in-program memory management. Experiments studying the time and space efficiency for real-world programs show that MG++ representation is space-efficient and the time overhead for MG++ construction algorithm is practical. We show that MG++ is effective for fault location and for analyzing binaries to detect heap buffer overflow attacks.
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