Automated Failure Categorization
ConceptAutomated Failure Categorization (AFC) is a rule-based analysis stage for RVV RTL verification that clusters failing tests by architectural symptoms, instruction context, and RVV-parameter predicates to make large failure sets easier to debug.
First seen 9/5/2026
Last seen 9/5/2026
Evidence 7 chunks
Wiki v1
WIKI
Overview
Automated Failure Categorization (AFC) is a stage introduced in the open-source RVVTS-based RTL verification framework for the RISC-V Vector Extension (RVV) 1.0. It is intended to make large sets of RTL verification failures more scalable to analyze by clustering failing cases into meaningful failure-mode categories rather than leaving engineers to inspect each failing test manually.
AFC addresses a specific problem in RVV verification: RVV instructions are parameterized by runtime configuration state such as vtype, vl, vstart, element width, register grouping, and masking. This creates a large configuration space, so even after failures are isolated to individual instructions, many distinct architectural symptoms can remain.
NEIGHBORHOOD
5 nodes · 4 edgesgraph · Automated Failure Categorization · depth=1
RELATIONSHIPS
4 connections From Generation to Failure Categorization: An Open-Source automated RTL Verification Framework for RVV ← introduces 100% 2e
The paper introduces the novel Automated Failure Categorization (AFC) stage.
AFC analyzes the extracted Machine State from the reference simulator and the DUT to cluster failures.
AFC clusters failures into meaningful failure mode categories using predefined rules.
AFC builds upon single-instruction isolation to further categorize failures.
LINKED ENTITIES
4 linksFrom Generation to Failure Categorization: An Open-Source automated RTL Verification Framework for RVV INTRODUCES Extracted graph relationship
Machine State USES Extracted graph relationship
failure mode category INTRODUCES Extracted graph relationship
single-instruction isolation USES Extracted graph relationship
CITATIONS
11 sources11 citations — click to expand
[1] AFC is introduced as a novel stage in an open-source RVVTS-based RTL verification framework for RVV 1.0. From Generation to Failure Categorization: An Open-Source automated RTL Verification Framework for RVV
[2] AFC is motivated by the large RVV configuration space and the need to analyze diverse failure modes even after single-instruction isolation. From Generation to Failure Categorization: An Open-Source automated RTL Verification Framework for RVV
[3] The framework defines a failure mode as an equivalence class of mismatching tests sharing instruction context, a minimal predicate over RVV parameters, and the same architectural symptom. From Generation to Failure Categorization: An Open-Source automated RTL Verification Framework for RVV
[4] AFC analyzes Machine States from the reference simulator and DUT, evaluates predefined rules sequentially, assigns the first matching failure-mode category, and uses UNKNOWN as a fallback. From Generation to Failure Categorization: An Open-Source automated RTL Verification Framework for RVV
[5] The paper defines 29 failure-mode categories for AFC, including the fallback UNKNOWN category. From Generation to Failure Categorization: An Open-Source automated RTL Verification Framework for RVV
[6] AFC examples include instruction validity errors, vector length and type handling errors, register value deviations, CSR deviations, deadlocks or hangs, and cross-instruction propagation. From Generation to Failure Categorization: An Open-Source automated RTL Verification Framework for RVV
[7] For hang handling, the AraRunner creates a Machine State with an invalid last executed PC so RVVTS can process hang cases like other Machine State deviations. From Generation to Failure Categorization: An Open-Source automated RTL Verification Framework for RVV
[8] In the Ara evaluation, AFC detected hang-category cases by checking for an invalid last executed PC in the DUT Machine State. From Generation to Failure Categorization: An Open-Source automated RTL Verification Framework for RVV
[9] In the Ara evaluation, the framework detected more than 82,000 deviations, minimized about 97%, and clustered failures into 16 categories. From Generation to Failure Categorization: An Open-Source automated RTL Verification Framework for RVV
[10] The Ara study reports AFC associating minimized failures with 611 instructions across 16 failure-mode categories. From Generation to Failure Categorization: An Open-Source automated RTL Verification Framework for RVV
[11] The six largest Ara failure-mode categories account for more than 93% of all failed cases and include VREG_ONLY, VTYPE_VILL_SET_ERROR, ARA_HANG, MSTATUS_EXT_REF, EXC_INVALID_REJECT, and EXC_INVALID_ACCEPT. From Generation to Failure Categorization: An Open-Source automated RTL Verification Framework for RVV