Efficiently and precisely locating memory leaks and bloat

Novark, Gene; Berger, Emery D.; Zorn, Benjamin G.

doi:10.1145/1543135.1542521

Cited by 20 publications

(25 citation statements)

References 30 publications

(9 reference statements)

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“…Let us consider SPEC2000 first. All the faults (20) in ammp are conditional leaks, caused when functions do not free memory when returning on errors. All these faults can also be found by FASTCHECK as they require only value-flow analysis for top-level pointers.…”

Section: Accuracymentioning

confidence: 99%

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Detecting Memory Leaks Statically with Full-Sparse Value-Flow Analysis

Sui

Xue

2014

IIEEE Trans. Software Eng.

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We introduce a static detector, SABER, for detecting memory leaks in C programs. Leveraging recent advances on sparse pointer analysis, SABER is the first to use a full-sparse value-flow analysis for detecting memory leaks statically. SABER tracks the flow of values from allocation to free sites using a sparse value-flow graph (SVFG) that captures def-use chains and value flows via assignments for all memory locations represented by both top-level and address-taken pointers. By exploiting field-, flow-and contextsensitivity during different phases of the analysis, SABER detects memory leaks in a program by solving a graph reachability problem on its SVFG. SABER, which is fully implemented in Open64, is effective at detecting 254 leaks in the 15 SPEC2000 C programs and seven applications, while keeping the false positive rate at 18.3 percent. SABER compares favorably with several static leak detectors in terms of accuracy (leaks and false alarms reported) and scalability (LOC analyzed per second). In particular, compared with FASTCHECK (which analyzes allocated objects flowing only into top-level pointers) using the 15 SPEC2000 C programs, SABER detects 44.1 percent more leaks at a slightly higher false positive rate but is only a few times slower.

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Section: Accuracymentioning

confidence: 99%

“…There are a number of reported attempts on memory leak detection using static analysis [3], [9], [10], [11], [13], [22], [30], [33] or dynamic analysis [1], [5], [20], [35], [36]. The SABER approach can speed up existing static techniques by using a full-sparse representation to track the flow of values through assignments.…”

Section: Related Workmentioning

confidence: 99%

Detecting Memory Leaks Statically with Full-Sparse Value-Flow Analysis

Sui

Xue

2014

IIEEE Trans. Software Eng.

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“…The second technique, leak pruning [Bond and McKinley 2009], predicts leaked objects based on data structure usage patterns, and then reclaims these objects at runtime; an error is thrown if any reclaimed object is later accessed. Other recent work on detecting memory leaks has resulted in the development of Hound [Novark et al 2009], a runtime system that helps identify the sources of memory leaks and bloat in C and C++ applications, that results in no false positives.…”

Section: Related Workmentioning

confidence: 99%

Execution suppression

Jeffrey

Nagarajan

Gupta

2008

ACM Trans. Program. Lang. Syst.

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By studying the behavior of several programs that crash due to memory errors, we observed that locating the errors can be challenging because significant propagation of corrupt memory values can occur prior to the point of the crash. In this article, we present an automated approach for locating memory errors in the presence of memory corruption propagation. Our approach leverages the information revealed by a program crash: when a crash occurs, this reveals a subset of the memory corruption that exists in the execution. By suppressing (nullifying) the effect of this known corruption during execution, the crash is avoided and any remaining (hidden) corruption may then be exposed by subsequent crashes. The newly exposed corruption can then be suppressed in turn. By iterating this process until no further crashes occur, the first point of memory corruption-and the likely root cause of the program failure-can be identified. However, this iterative approach may terminate prematurely, since programs may not crash even when memory corruption is present during execution. To address this, we show how crashes can be exposed in an execution by manipulating the relative ordering of particular variables within memory. By revealing crashes through this variable re-ordering, the effectiveness and applicability of the execution suppression approach can be improved. We describe a set of experiments illustrating the effectiveness of our approach in consistently and precisely identifying the first points of memory corruption in executions that fail due to memory errors. We also discuss a baseline software implementation of execution suppression that incurs an average overhead of 7.2x, and describe how to reduce this overhead to 1.8x through hardware support.

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“…There have been many proposals for detecting or preventing one or some kinds of invalid pointer dereferences [3], [4], [5], [6], [7], [8]. These approaches can be mainly divided into two kinds: dynamic methods that check pointer dereferences during the running of programs and static analysis without running programs.…”

Section: Introductionmentioning

confidence: 99%

Invalid Pointer Dereferences Detection for CPS Software Based on Extended Pointer Structures

Dong

Chen

2012

2012 IEEE Sixth International Conference on Software Security and Reliability Companion

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Invalid pointer dereferences, such as null pointer dereferences, dangling pointer dereferences and double frees, are a prevalent source of software bugs in CPS software, due to flexible dereferencing pointers along various pointer fields. Existing tools have high overhead or are incomplete, thereby limiting their efficiency in checking the kind of CPS software with shared and mutable memory. In this paper, we present a novel extended pointer structure for detecting all invalid pointer dereferences in this kind of CPS software. We propose an invalid pointer dereferences detection algorithm based on the uniform transformation of abstract heap states. Experimental evaluation about a set of large C benchmark programs shows that the proposed approach is sufficiently efficient in detecting invalid pointer dereferences of CPS software with shared and mutable memory.

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Efficiently and precisely locating memory leaks and bloat

Cited by 20 publications

References 30 publications

Detecting Memory Leaks Statically with Full-Sparse Value-Flow Analysis

Detecting Memory Leaks Statically with Full-Sparse Value-Flow Analysis

Execution suppression

Invalid Pointer Dereferences Detection for CPS Software Based on Extended Pointer Structures

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