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STIMSMITH

INSTILLER

Tool

No verifiable technical information about INSTILLER was provided in the available evidence.

First seen 5/24/2026
Last seen 6/3/2026
Evidence 6 chunks
Wiki v1

WIKI

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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RELATIONSHIPS

31 connections
Interruption and Exception Simulation implements → 99% 11e
Instiller implements realistic interruption and exception simulation in its fuzzing process.
Input Instruction Distillation implements → 99% 8e
Instiller implements input instruction distillation to shorten and improve the effectiveness of input instructions.
Variant of Ant Colony Optimization implements → 99% 8e
Instiller implements a variant of ant colony optimization (VACO) for input instruction distillation.
DiFuzzRTL ← compares with 100% 8e
Instiller is experimentally compared against DiFuzzRTL, showing improvements in coverage, mismatch detection, and instruction length.
Hardware-based Seed Selection uses → 100% 6e
Instiller uses hardware-based seed selection strategies to improve fuzzing performance.
RTL Fuzzing implements → 100% 6e
Instiller is an RTL fuzzer that implements the RTL fuzzing technique for CPU bug detection.
Hardware-based Seed Selection implements → 98% 6e
Instiller implements hardware-based seed selection to improve fuzzing performance.
CPU Bug Detection evaluates → 100% 6e
Instiller is evaluated on its ability to detect CPU bugs through RTL fuzzing experiments.
Interruption and Exception Simulation uses → 100% 5e
Instiller simulates realistic interruptions and exceptions to better cover CPU states.
Ant Colony Optimization uses → 100% 5e
Instiller is based on ant colony optimization for distilling input instructions.
Hardware-Based Mutation implements → 98% 4e
Instiller implements hardware-based mutation to improve fuzzing performance.
Variant of Ant Colony Optimization uses → 100% 4e
Instiller uses a variant of ACO (VACO) to distill input instructions.
Input Instruction Distillation uses → 100% 4e
Instiller uses input instruction distillation to keep input instruction length short and efficient.
Hardware-Based Mutation uses → 100% 4e
Instiller uses hardware-based mutation strategies to improve fuzzing performance.
VACO uses → 100% 3e
INSTILLER uses VACO, a variant of ACO, to distill input instructions.
Instruction Distillation uses → 100% 3e
INSTILLER distills input instructions using VACO to keep input length short.
Interrupt and Exception Injection uses → 100% 3e
INSTILLER solves the problem of inserting interruptions and exceptions in generating inputs.
RTL uses → 100% 3e
Instiller targets RTL designs for CPU verification.
mismatch detection evaluates → 2e
Instiller is evaluated by measuring the number of mismatches detected compared to DiFuzzRTL.
Input Instruction Distillation introduces → 2e
Instiller introduces input instruction distillation as a novel contribution.
Hardware-Based Mutation Strategy implements → 98% 2e
Instiller implements hardware-based mutation strategies to improve fuzzing performance.
The paper proposes INSTILLER (Instruction Distiller) as the main contribution.
Hardware-based Mutation Strategies uses → 100% 2e
INSTILLER proposes hardware-based mutation strategies to improve fuzzing performance.
Coverage evaluates → 1e
Instiller is evaluated by measuring coverage improvement over DiFuzzRTL.
CPU evaluates → 97% 1e
Instiller conducts experiments against real-world target CPU cores for bug detection evaluation.
Coverage uses → 1e
Instiller uses coverage as a primary metric to evaluate its fuzzing effectiveness.
Fuzz Testing implements → 98% 1e
Instiller is a fuzzer that implements fuzz testing for CPU RTL verification.
CPU Bug Detection uses → 1e
Instiller is designed for CPU bug detection through RTL fuzzing.
Code Coverage evaluates → 97% 1e
Instiller measures code coverage as a key evaluation metric, achieving 29.4% more coverage than DiFuzzRTL.
Hardware-based Seed Selection introduces → 1e
Instiller introduces hardware-based seed selection as a novel contribution.
Hardware-Based Mutation introduces → 1e
Instiller introduces hardware-based mutation as a novel contribution.