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Topseed: Learning Seed Selection Strategies for Symbolic Execution from Scratch

descriptionPublicationkeyboard_double_arrow_right Article , Conference object 26 Apr 2025Publisher:IEEEJournal:2025 IEEE/ACM 47th International Conference on Software Engineering (ICSE)
Authors: Lee, Jaehyeok; Cha, Sooyoung;

doi: 10.1109/icse55347.2025.00095 , 10.5281/zenodo.14890193 , 10.5281/zenodo.14602978 , 10.5281/zenodo.14603223 , 10.5281/zenodo.14602979

Topseed: Learning Seed Selection Strategies for Symbolic Execution from Scratch

Abstract

Topseed is a novel technique designed to enhance symbolic execution by selecting the most promising seeds without prior knowledge using a learning-based approach. This tool is basically implemented on the top of KLEE, an actively maintained symbolic executor for testing C programs.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green