Testing Error Handling Code with Software Fault Injection and Error-Coverage-Guided Fuzzing. Bai, J., Fu, Z., Xie, K., & Jiang, Z. IEEE. bibtex @Article{bai23testing,
author = {Bai, Jia-Ju and Fu, Zi-Xuan and Xie, Kai-Tao and Jiang, Zu-Ming},
date = {2023},
journaltitle = {IEEE Transactions on Dependable and Secure Computing},
title = {Testing Error Handling Code with Software Fault Injection and Error-Coverage-Guided Fuzzing},
comment = {- fuzzing is inefficient
- some bugs related to inputs *and* execution conditions
- e.g. low memory
- explore fault space with fuzzing by leveraging program feedback
- injection guided by metric "error coverage"
- considers error sites *plus* runtime context
- based on LLVM
- process, roughly
- identify "error sites"
- identify unchecked return codes
- according to related work, most error sites are code statements
checking error-indicating return values of function calls
- #dependabilityByDefault #ZLiC #systemCallFaulTolerance
- similar to study by Roberto Natella on Android:
Many bugs in (potentially missing) error-handling code
- generated program with injection points
- execute
- observe
- evaluation on real-life programs
- comprehensive
- vim, ffmpeg, openssl, btrfs, xfs, jfs, cephfs, …
- comparison with other fuzzers},
file = {:bai23testing - Testing Error Handling Code with Software Fault Injection and Error-Coverage-Guided Fuzzing.pdf:PDF},
groups = {fault injection, fault injection tools, dependability by default / dependability wrap},
publisher = {IEEE},
}
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