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Structured Random Differential Testing of Instruction Decoders

Paper
First seen 7/30/2026
Last seen 7/30/2026
Evidence 6 chunks

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RELATIONSHIPS

14 connections
DERIVE system mentions → 95% 2e
The paper discusses the DERIVE system as related prior work on instruction encoding inference.
libopcodes evaluates → 100% 2e
The paper evaluates libopcodes as one of the instruction decoders under test.
LLVM evaluates → 100% 2e
The paper evaluates LLVM as one of the instruction decoders under test.
Dyninst evaluates → 100% 2e
The paper evaluates Dyninst as one of the instruction decoders under test.
Capstone evaluates → 100% 2e
The paper evaluates Capstone as one of the instruction decoders under test.
Paleari et al. 2010 x86 decoder differential testing ← compares with 100% 2e
The paper explicitly compares its approach with Paleari et al.'s prior work on x86 decoder differential testing.
Fleece introduces → 100% 2e
The paper presents Fleece as the tool implementing their testing methodology.
Differential Testing uses → 100% 2e
The paper uses differential testing as a core component of output verification.
XED evaluates → 100% 2e
The paper evaluates XED as one of the instruction decoders under test.
Barton P. Miller authored by → 100% 1e
Barton P. Miller is listed as an author of the paper.
University of Wisconsin authored by → 100% 1e
Both authors are affiliated with the University of Wisconsin.
model-based input generation mentions → 90% 1e
The paper discusses model-based input generation as prior related work.
structured random testing introduces → 100% 1e
The paper introduces a structured random testing methodology for instruction decoders.
Nathan Jay authored by → 100% 1e
Nathan Jay is listed as an author of the paper.