INSTILLER
ToolNo verifiable technical information about INSTILLER was provided in the available evidence.
First seen 5/24/2026
Last seen 6/3/2026
Evidence 6 chunks
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INSTILLER
INSTILLER is identified as an entity of kind Tool in the request, but no evidence, public context, or related entities were provided. As a result, no technical description, capabilities, architecture, usage, integrations, or provenance can be documented from the supplied materials.
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31 connectionsInstiller implements realistic interruption and exception simulation in its fuzzing process.
Instiller implements input instruction distillation to shorten and improve the effectiveness of input instructions.
Instiller implements a variant of ant colony optimization (VACO) for input instruction distillation.
Instiller is experimentally compared against DiFuzzRTL, showing improvements in coverage, mismatch detection, and instruction length.
Instiller uses hardware-based seed selection strategies to improve fuzzing performance.
Instiller is an RTL fuzzer that implements the RTL fuzzing technique for CPU bug detection.
Instiller implements hardware-based seed selection to improve fuzzing performance.
Instiller is evaluated on its ability to detect CPU bugs through RTL fuzzing experiments.
Instiller simulates realistic interruptions and exceptions to better cover CPU states.
Instiller is based on ant colony optimization for distilling input instructions.
Instiller implements hardware-based mutation to improve fuzzing performance.
Instiller uses a variant of ACO (VACO) to distill input instructions.
Instiller uses input instruction distillation to keep input instruction length short and efficient.
Instiller uses hardware-based mutation strategies to improve fuzzing performance.
INSTILLER uses VACO, a variant of ACO, to distill input instructions.
INSTILLER distills input instructions using VACO to keep input length short.
INSTILLER solves the problem of inserting interruptions and exceptions in generating inputs.
Instiller targets RTL designs for CPU verification.
Instiller is evaluated by measuring the number of mismatches detected compared to DiFuzzRTL.
Instiller introduces input instruction distillation as a novel contribution.
Instiller implements hardware-based mutation strategies to improve fuzzing performance.
The paper proposes INSTILLER (Instruction Distiller) as the main contribution.
INSTILLER proposes hardware-based mutation strategies to improve fuzzing performance.
Instiller is evaluated by measuring coverage improvement over DiFuzzRTL.
Instiller conducts experiments against real-world target CPU cores for bug detection evaluation.
Instiller uses coverage as a primary metric to evaluate its fuzzing effectiveness.
Instiller is a fuzzer that implements fuzz testing for CPU RTL verification.
Instiller is designed for CPU bug detection through RTL fuzzing.
Instiller measures code coverage as a key evaluation metric, achieving 29.4% more coverage than DiFuzzRTL.
Instiller introduces hardware-based seed selection as a novel contribution.
Instiller introduces hardware-based mutation as a novel contribution.