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Exception Handling in Processor Verification

Concept

Exception handling in processor verification is planned stimulus and checking for processor exception causes such as illegal opcodes, watchpoints, misaligned memory accesses, and instruction-slot rule violations. In constrained-random verification, exception conditions should be planned early, modeled in transaction properties and constraints, and injected through instruction scenarios with controlled occurrence probabilities and combinations.

First seen 5/28/2026
Last seen 5/29/2026
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Overview

In constrained-random processor verification, exception handling refers to planning and generating instruction streams that exercise the processor hardware's exception behavior. Pure random instruction streams are usually insufficient for this purpose because they rarely create useful stimulus for important functions such as branches, jumps, and exceptions. A constrained-random verification infrastructure therefore needs knowledge of the processor instruction-set architecture and state, and it should be driven by top-down stimulus planning. [C1]

A program trace can be modeled as a collection of one or more instruction scenarios. For example, one scenario may provide boot code with an exception handler, another may program internal configuration registers for hardware watchpoints, and later scenarios may contain load/store, arithmetic, and branch operations. Exception conditions can be introduced randomly inside these scenarios. [C2]

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RELATIONSHIPS

4 connections
Instruction Scenario ← mentions 92% 1e
Instruction scenarios can include exception conditions introduced at random.
Illegal Opcode Injection uses → 95% 1e
Illegal opcode injection is used to trigger and test exception handling in processor verification.
Memory Alignment Constraint uses → 93% 1e
Memory alignment constraint violations are used to trigger exceptions in processor verification.
Top-Down Stimulus Planning uses → 90% 1e
Exception handling verification is planned for early as a requirement from top-down stimulus planning.

LINKED ENTITIES

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Illegal Opcode Injection USES Extracted graph relationship
Memory Alignment Constraint USES Extracted graph relationship
Instruction Scenario MENTIONS Extracted graph relationship
Top-Down Stimulus Planning USES Extracted graph relationship

CITATIONS

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9 citations — click to expand
[1] Pure random instruction streams are insufficient for fully verifying processor functions such as branches, jumps, and exceptions; constrained-random infrastructure needs ISA and state knowledge guided by top-down planning. Applying constrained-random verification to microprocessors
[2] A program trace can be modeled as instruction scenarios, including boot code with an exception handler, watchpoint setup, and scenarios where exception conditions are introduced randomly. Applying constrained-random verification to microprocessors
[3] Exception planning should cover specific causes, occurrence probabilities, and simultaneous exception conditions to test exception priority and handling. Applying constrained-random verification to microprocessors
[4] Processor-verification transactions can be modeled as operation, instruction, and instruction-scenario classes with constraints that describe relationships between properties. Applying constrained-random verification to microprocessors
[5] Example constrained rules include load/store and ERET slot requirements, ERET pairing with NOP, and disallowing same-register writes in both operations of an instruction. Applying constrained-random verification to microprocessors
[6] Separate constraint blocks can be disabled to violate rules intentionally, such as allowing a load/store operation in slot 1 to cause an exception. Applying constrained-random verification to microprocessors
[7] Illegal opcode injection can be modeled with an ILLEGAL operation kind that selects a random unassigned opcode value for exception testing. Applying constrained-random verification to microprocessors
[8] Unaligned load/store accesses trigger exceptions, and memory-alignment constraints can be disabled so misaligned addresses are generated for exception testing. Applying constrained-random verification to microprocessors
[9] A common instruction-scenario base class can encapsulate reusable methods and constraints, supporting targeted random exception cases beyond pure random instruction generation. Applying constrained-random verification to microprocessors