TY - GEN
T1 - Improving Fuzzing Coverage with Execution Path Length Selection
AU - Zhang, Wenxi
AU - Sakamoto, Kazunori
AU - Washizaki, Hironori
AU - Fukazawa, Yoshiaki
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Coverage-guided fuzzing is one of the most effective types of fuzz testing. Code coverage is an important parameter of performance evaluation of the coverage-guided fuzzing tools since normally higher coverage result means a higher chance of fault detection. To expand the overall code covered, based on previous basic block analysis, we propose a method for selecting the mutants of inputs that are able to execute some specific length of the execution path.
AB - Coverage-guided fuzzing is one of the most effective types of fuzz testing. Code coverage is an important parameter of performance evaluation of the coverage-guided fuzzing tools since normally higher coverage result means a higher chance of fault detection. To expand the overall code covered, based on previous basic block analysis, we propose a method for selecting the mutants of inputs that are able to execute some specific length of the execution path.
KW - basic block
KW - evaluation
KW - fuzz testing
UR - http://www.scopus.com/inward/record.url?scp=85146326813&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85146326813&partnerID=8YFLogxK
U2 - 10.1109/ISSREW55968.2022.00057
DO - 10.1109/ISSREW55968.2022.00057
M3 - Conference contribution
AN - SCOPUS:85146326813
T3 - Proceedings - 2022 IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2022
SP - 132
EP - 133
BT - Proceedings - 2022 IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 33rd IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2022
Y2 - 31 October 2022 through 3 November 2022
ER -