Using Valgrind to Detect Undefined Value Errors with Bit-Precision

By Julian Seward, Nicholas Nethercote. USENIX ATC, General Track, 2005

416 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/5f6a808bedd3dbfd1290063b3cd8221132ce5c95

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Citations in the corpus

Backward-compatible constant-time exception-protected memory (2009, background): “Significant work has transpired since [1] on these error classes because of the very hard to trace and fix attributes of these errors [2, 5, 6-9, 11-19, 22].”
AddressSanitizer: A Fast Address Sanity Checker (2012, methodology): “However, AddressSanitizer uses a more efficient shadow mapping, a more compact shadow encoding, detects errors in stack and global variables in addition to the heap and is an order of magnitude faster than AddrCheck.”
Valgrind: a framework for heavyweight dynamic binary instrumentation (2007, methodology): “Memcheck [25] uses shadow values to track which bit values are undefined (i.”
Jalangi: a selective record-replay and dynamic analysis framework for JavaScript (2013, result): “Previous research [31, 20, 8, 6, 21] and our experience with concolic testing [13, 30] and race detection techniques have shown that support for shadow values and shadow execution could significantly simplify implementation of dynamic analyses techniques.”
SweeD: Likelihood-Based Detection of Selective Sweeps in Thousands of Genomes (2013, methodology): “software (Seward and Nethercote 2005).”
DieHard: probabilistic memory safety for unsafe languages (2006, background): “Tools like Purify [18] and Valgrind [28, 35] allow programmers to pinpoint the exact location of these memory errors (at the cost of a 2-25X performance penalty), but only reveal those bugs found during testing.”