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Page Fault Handling, Trap Flow, and Recovery Paths: Debug Playbook

Debug Playbook for Page Fault Handling, Trap Flow, and Recovery Paths.

Debug playbook

Debug Playbook for Page Fault Handling, Trap Flow, and Recovery Paths is anchored on Fault service latency (median/P99), restart success rate, and throughput impact during demand paging and copy-on-write stress.. Convert observations into mechanism-backed decisions with explicit ownership.

  1. Freeze workload seed, binary, compiler, firmware, and platform setup.

  2. Find earliest persistent mechanism failure in the timeline.

  3. Build one reduced reproducer for dominant hypothesis.

  4. Patch minimal fix with explicit rollback gate.

  5. Rerun correctness + performance + power matrix.

Decision tree

diagram
ROOT CAUSE TREE - Page Fault Handling, Trap Flow, and Recovery Paths

Fault service latency (median/P99), restart success rate, and throughput impact during demand paging and copy-on-write stress. regressed
          |
   reproducible on fixed seed?
      /                 \
    no                   yes
    |                     |
env/tool drift       first failing domain?
                     /        |         \
                  decode    execute    memory/MMU
                    |         |            |
               control map  bypass/FU   TLB/walk/perm
                    |
         privilege/CSR side effects checked?

Stop at first confirmed mechanism, then assign explicit owner + fix proof.

Review memo template

diagram
RISC-V REVIEW MEMO - Memory & Virtualization / Page Fault Handling, Trap Flow, and Recovery Paths

1. Symptom
   - Failing metric: Fault service latency (median/P99), restart success rate, and throughput impact during demand paging and copy-on-write stress.
   - Failing workload slice: <name>
   - Triggering mode: <privilege/virtualization/interrupt/cache/boot>
   - Build and runtime tags: <toolchain/firmware/RTL revision>

2. Mechanism hypothesis
   - Primary mechanism: When translation or permission checks fail, the core raises precise exceptions with fault metadata (cause and faulting address) so software can resolve the condition deterministically. Kernel or hypervisor handlers inspect PTE state, allocate or map backing pages, update access/dirty bookkeeping, and resume execution at the correct architectural point. Robust designs align hardware trap guarantees with software expectations for speculative accesses, nested virtualization, and shared page tables so faults are neither lost nor misattributed. The critical engineering challenge is balancing low-latency fast paths for common demand faults with correctness under races, including concurrent unmap, shootdown, and copy-on-write updates.
   - Competing hypotheses: <decode control / hazard / MMU / privilege / integration>
   - Missing evidence: <trace/counter/proof/report>

3. Proposed action
   - Smallest reversible change: <RTL/compiler/runtime/config>
   - Expected movement: <throughput/latency/tail/perf-per-watt>
   - Regression risk: correctness, security, power, timing, software compatibility

4. Signoff
   - Required artifact: Fault lifecycle sequence from exception entry to TLB shootdown and instruction replay, including nested page-fault cases.
   - Required owners: OS kernel memory owner, hypervisor owner, CPU exception and privilege architect, runtime performance owner, system validation owner
   - Final decision: ship, bounded rollout, rollback, or escalate
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