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pro vyhledávání: '"Marcel Böhme"'
We make all the data, analysis, and results of the conference (ICSE 2023) paper "Reachable Coverage: Estimating Saturation in Fuzzing" openly accessible. We have incorporated each data pre-processing and analysis step into a single R notebook, analys
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5586d1c1be9e5dd3d269bd7b1a17df86
Publikováno v:
Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis.
Publikováno v:
Proceedings of the 44th International Conference on Software Engineering.
Automated test generators, such as search-based software testing (SBST) techniques are primarily guided by coverage information. As a result, they are very effective at achieving high code coverage. However, is high code coverage alone sufficient to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1ab49ad638a82af3b5524157108005df
http://urn.fi/urn:nbn:fi-fe2022042530264
http://urn.fi/urn:nbn:fi-fe2022042530264
Autor:
Xiaogang Zhu, Marcel Böhme
Publikováno v:
CCS
What you change is what you fuzz! In an empirical study of all fuzzer-generated bug reports in OSSFuzz, we found that four in every five bugs have been introduced by recent code changes. That is, 77% of 23k bugs are regressions. For a newly added pro
Publikováno v:
ACM Conference on Computer and Communications Security
Coverage-based Greybox Fuzzing (CGF) is a random testing approach that requires no program analysis. A new test is generated by slightly mutating a seed input. If the test exercises a new and interesting path, it is added to the set of seeds; otherwi
Statistical fault localization is an easily deployed technique for quickly determining candidates for faulty code locations. If a human programmer has to search the fault beyond the top candidate locations, though, more traditional techniques of foll
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4a4d2f196f2a376b58d8f119fd8b50c0
http://orbilu.uni.lu/handle/10993/52016
http://orbilu.uni.lu/handle/10993/52016
Today, most automated test generators, such as search-based software testing (SBST) techniques focus on achieving high code coverage. However, high code coverage is not sufficient to maximise the number of bugs found, especially when given a limited
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::278bc8b5eef7fd7ec6f46cbc3038cb4a
Autor:
Marcel Böhme, Brandon Falk
Publikováno v:
ESEC/SIGSOFT FSE
We present counterintuitive results for the scalability of fuzzing. Given the same non-deterministic fuzzer, finding the same bugs linearly faster requires linearly more machines. For instance, with twice the machines, we can find all known bugs in h
Publikováno v:
ESEC/SIGSOFT FSE
In this paper, we take the fundamental perspective of fuzzing as a learning process. Suppose before fuzzing, we know nothing about the behaviors of a program P: What does it do? Executing the first test input, we learn how P behaves for this input. E