Segregating heap objects by reference behavior and lifetime
Proceedings of the eighth international conference on Architectural support for programming languages and operating systems
A framework for reducing the cost of instrumented code
Proceedings of the ACM SIGPLAN 2001 conference on Programming language design and implementation
A practical flow-sensitive and context-sensitive C and C++ memory leak detector
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
Low-overhead memory leak detection using adaptive statistical profiling
ASPLOS XI Proceedings of the 11th international conference on Architectural support for programming languages and operating systems
Context- and path-sensitive memory leak detection
Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering
Valgrind: a framework for heavyweight dynamic binary instrumentation
Proceedings of the 2007 ACM SIGPLAN conference on Programming language design and implementation
Practical memory leak detection using guarded value-flow analysis
Proceedings of the 2007 ACM SIGPLAN conference on Programming language design and implementation
Detecting and eliminating memory leaks using cyclic memory allocation
Proceedings of the 6th international symposium on Memory management
LeakSurvivor: towards safely tolerating memory leaks for garbage-collected languages
ATC'08 USENIX 2008 Annual Technical Conference on Annual Technical Conference
Proceedings of the 23rd ACM SIGPLAN conference on Object-oriented programming systems languages and applications
Efficiently and precisely locating memory leaks and bloat
Proceedings of the 2009 ACM SIGPLAN conference on Programming language design and implementation
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Embedded applications with a long running life time particularly require a high degree of reliability. Many types of weaknesses residing in software can reduce the reliability, but memory leaks are prominent sources of software weaknesses for long running applications. As memory leaks are typically cumbersome and illusive, finding their sources demands programmers to make a huge effort even with fairly automated memory leak detection tools. Recently, dynamic detectors with light overheads have been emerged. They use sampling-based techniques to reduce overheads. According to the frequencies of code executions and data accesses, the memory monitor adaptively controls the sampling periods. The accuracies of existing sampling techniques are, however, unsatisfactory in some cases. In this paper, we present a more accurate memory leak detection technique, which takes advantage of context information. Our memory leak detector, which is also based on data sampling, adopts a notion of context (or call path) to sort out dynamically allocated memories and more accurately tracks the sources of memory leaks in the source code. Our experiments with SPEC CINT2000 benchmarks show our technique finds more memory leaks by up to 72% with comparable overheads to the existing data sampling technique.