Modular Heap Abstraction-Based Memory Leak Detection for Heap-Manipulating Programs
Citations Over Time
Abstract
Heap-manipulating programs allow flexible manipulations over dynamically allocated, shared, and mutable heap cells via pointers that point to not only linked data structures but also their pointer fields. Therefore, memory leak detection for these programs requires precise field-sensitive pointer alias information, which make the problem more challenging. In this paper, we present a field and context sensitive algorithm for detecting memory leaks in heap-manipulating programs. First, we propose a modular heap abstraction based on member-access distances and alias bit-vector domain as the escape model of each procedure, Then, based on procedural summaries characterized by this modular heap abstraction, an efficient context-sensitive memory leak detection is proposed in an on-demand way. Experimental evaluation about a set of large C benchmark programs shows that the proposed approach is scalable with satisfied precision as expected.
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