Demand-Driven Memory Leak Detection Based on Flow-and Context-Sensitive Pointer Analysis
Demand-Driven Memory Leak Detection Based on Flow- and Context-Sensitive Pointer Analysis

We present a demand-driven approach to memory leak detection algorithm based on flow- and context-sensitive pointer analysis. The detection algorithm firstly assumes the presence of a memory leak at some program point and then runs a backward analysis to see if this assumption can be disproved. Our algorithm computes the memory abstraction of programs based on points-to graph resulting from flow- and context-sensitive pointer analysis. We have implemented the algorithm in the SUIF2 compiler infrastructure and used the implementation to analyze a set of C benchmark programs. The experimental results show that the approach has better precision with satisfied scalability as expected. This work is supported by the National Natural Science Foundation of China under Grant Nos. 60725206, 60673118, and 90612009, the National High-Tech Research and Development 863 Program of China under Grant No. 2006AA01Z429, the National Basic Research 973 Program of China under Grant No. 2005CB321802, the Program for New Century Excellent Talents in University under Grant No. NCET-04-0996, and the Hunan Natural Science Foundation under Grant No. 07JJ1011.