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fix-sldv-incompatibility【设计与创意】Use when a Simulink model is incompatible with Simulink Design Verifier (sldvcompat returns false, or an SLDV analysis errors out on an unsupported construct) and needs to be made analyzable. Diagnoses the incompatibility, applies the matching fix to a copy, and confirms the copy is compatible; optionally raises confidence the fix preserved behavior …
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Fix Simulink Design Verifier incompatibilities by diagnosing the model and applying the matching fix. Block-level fixes go through model_edit; solver/config-level fixes are the one exception that requires setting the parameter directly (see Step 3).
sldvcompat and gets falsesldvcompat returns true) — there is
nothing to fix.The core job is diagnose → fix → confirm compatible (Steps 1–4). That is the default endpoint. Running an SLDV analysis mode (test generation, design error detection) and verifying behavior on the original model is optional and only happens when the surrounding intent calls for it (Step 5). A user who just wants compatibility gets the fix and nothing more.
sldvcompat return
false: a genuine authoring bug (undefined block parameter, unresolved
reference), fixed by repairing the model; and a genuinely missing external
dependency — a data-dictionary file, referenced-model file, data file,
library, or workspace variable the model needs that is not present / cannot be
located — fixed by providing the resource, not by editing the model (see
Step 1.5). Neither is fixed with a compatibility rule. (A resource that is
present but merely opaque to SLDV — a protected .slxp reference, external
custom code, an S-function — is different again: that you do fix, by
stubbing.) When a model fails sldvcompat, Step 1 also runs a normal-mode
compile probe and reports result.compiles / result.buildError so you can
tell these apart before matching a rule.scripts/ directory. Call them with
evaluate_matlab_code using project_path set to that folder so MATLAB can
find them.Call via evaluate_matlab_code:
% project_path = the skill's scripts/ folder (via evaluate_matlab_code)
result = sldv_diagnose_incompatibility('<model_path>');
This will:
<model>_sldv_compatible.slx in the same foldersldvcompat on the copyIt returns a result struct with these top-level fields:
.compatible — true/false, the sldvcompat status on the copy.copyPath — full path to the working copy (<model>_sldv_compatible.slx).
Later steps pass this to model_edit and to sldv_verify_consistency.copyName — name of the copy with no extension (use with sldvcompat /
save_system / close_system).findings — struct array, one entry per issue sldvcompat itself reports,
each with .msgid, .message, .type, .blockPath, and .blockType.compiles — logical, populated only when .compatible == false: the result
of a normal-mode Simulink compile probe on the copy. It is a diagnostic aid,
not a gate — the findings above stay authoritative and are matched against
the catalog regardless. Its purpose is the case where the findings are only
generic: true means the model builds (a real SLDV limitation), false means
it does not compile at all (a plain authoring bug the catalog does not cover —
see Prerequisites; fix the model first)..buildError — when .compiles == false, the compile error's .identifier
and .message; empty strings otherwise.sldvcompat is authoritative: each finding already names the offending object.
For a block-level issue, .blockPath is the full block path (nesting
included, e.g. mdl/Sub/White Noise) and .blockType its BlockType. For a
config-level issue (variable-step solver, nonempty InitFcn, concurrent
execution, …), .blockPath is the model name, .blockType is empty, and
.msgid identifies the setting.
The diagnostic does not scan blocks or pre-read config params: use
model_overview / model_read / model_query_params to inspect whatever a
finding points to, and the rule catalog in references/incompatibility-rules.md
to decide the fix.
A config-level finding can MASK block-level findings. A variable-step
solver, for example, stops sldvcompat before it reaches the blocks. So more
issues may surface only after you fix the config-level ones and re-run the
diagnostic — never assume the first pass lists everything (Step 4 loops).
If result.compatible == true, the model is already compatible. Done.
Some incompatibilities are not something to fix in the model at all — the
model is fine, but an external resource it depends on is genuinely absent from
the environment: a data dictionary (.sldd) file that is not on disk, a
referenced model file that cannot be located, a From File / From Spreadsheet
data file that does not exist, a library / MATLAB class / workspace variable a
parameter resolves to that is nowhere on the path. SLDV cannot analyze what it
cannot find, so sldvcompat fails — but applying a compatibility rule
(replacing or stubbing the block) would be wrong: it hides a real gap and
discards the model's intended behavior.
Recognize this class before matching a rule: it shows up as result.compiles == false together with a result.buildError (or a result.findings entry) whose
message says a named resource is missing / not found / does not exist / cannot
be located or resolved. The identifiers vary by resource and release (e.g. a
missing data-dictionary file, a not-found referenced-model file, an absent data
file), so match on the meaning — a named external artifact that isn't
there — not on a fixed list of msgids. See "Missing External Dependencies" in
references/incompatibility-rules.md.
This is NOT the present-but-opaque case — do not confuse the two. A resource
that exists but SLDV cannot see inside is a normal stubbing job, not a
missing dependency: a protected (.slxp) referenced model, a
Model block referencing one that is present, external custom code / an
S-function whose source is opaque, a MATLAB Function block calling an
external routine. These are on disk and resolve fine — SLDV just can't analyze
their internals. Fix them (stub the block), do not ask the user for them. If
result.compiles == true (the model builds), it is by definition not a
missing dependency — go straight to Step 2. Only defer to the user when the
named artifact truly cannot be found.
When you hit one, do not fix or rewrite the model. Instead:
result.buildError.message / the finding message (e.g. "the model
references data dictionary params.sldd, which SLDV cannot find on the
path").Only once the dependency is resolvable does the normal diagnose → match → fix
flow apply. Two other compiles == false cases are not this and must not be
routed here: a plain authoring bug (undefined parameter, broken expression)
is resolved by repairing the model; a present-but-opaque resource
(protected .slxp reference, external custom code, S-function) is resolved by
stubbing the block per Step 2/3. Ask the user only when the named artifact
genuinely cannot be found — never for a resource that is present but unanalyzable.
The rule catalog is not inlined here — it lives in
references/incompatibility-rules.md. Load and follow that file. For
each entry in result.findings, match .msgid (and, for block-level findings,
the .blockType at .blockPath) against the catalog, then apply the listed
fix. Use model_read on .blockPath to inspect the offending block's
parameters. Use the catalog's Disambiguation Guide when a msgid maps to multiple
rules, and its Stubbing Strategy / Integrator port-matching / block-reduction
sections for the cross-cutting guidance the fixes reference.
Most findings already name the offending object in .blockPath. But some are
generic — the message is vague (e.g. a bare SLDV:Compatibility:Generic)
and .blockPath points at a container (the model root or a SubSystem)
rather than a leaf block. A generic, container-scoped finding does not tell you
what to fix. When (and only when) you hit one, narrow it:
% project_path = the skill's scripts/ folder
loc = sldv_localize_incompatibility('<model_or_atomic_subsystem_path>');
This drills the hierarchy, scoping sldvcompat onto each atomic subsystem,
atomic Stateflow subchart, and referenced model, and keeps descending into
whichever children are individually incompatible. It descends through
virtual subsystems (which sldvcompat cannot scope) to the next atomic
boundary. It returns:
loc.culprits — one entry per deepest responsible scope (the narrowest
subsystem/subchart/model that is incompatible while none of its scopable
children are), each with that scope's .path, .kind, and .findings.loc.drilled — true if the search narrowed below the scope you passed in.loc.searched — every scope it scoped sldvcompat onto (for transparency).Then match the rule (Step 2) against each culprit's .findings, which are now
scoped to the responsible subsystem instead of the whole model. If
loc.culprits still points at a scope whose own findings are generic (the
issue is that scope's wiring/config, not a nested block), inspect that scope
directly with model_read / model_query_params.
Do not run localization for findings that already name a leaf block — use those directly. Localization is only for the generic, container-scoped case.
Based on the matched rule:
model_edit on result.copyName. This is the
default — all block edits (replacement, stubbing, port matching, rewiring) go
through model_edit.model_edit
cannot touch — it only operates on blocks. This is the one exception where
you set the parameter directly via evaluate_matlab_code (set_param on the
model root, e.g. the solver type). Most such fixes are the config-level rules
(Rules 1–7), but a handful of otherwise block-level rules also include a
config-level set_param step (e.g. clearing CustomSourceCode, aligning
referenced-model hardware settings, forcing a fixed-step solver, or disabling
BlockReduction) — those config steps use set_param too. The exception is
defined by the kind of fix (a config/model-root parameter), not by the
rule number. Do not generalize it to block-level edits: never reach for
set_param to add, delete, replace, or rewire a block — that is always
model_edit's job.Most block-level rules do semantic replacement (swap the unsupported block
for an analyzable equivalent). When no faithful equivalent exists — or the
block's internals are irrelevant to the analysis — use the general stubbing
strategy instead (see "Stubbing Strategy" in
references/incompatibility-rules.md). Stubbing abstracts a block's output to a
free value so SLDV stops analyzing inside it; prefer a bounded stub so
analysis stays realistic.
Before any block replacement, guard against optimized-out blocks. Block
reduction can delete blocks (bus selectors/creators, IC blocks, …) before the
replacement runs, so it silently finds nothing to replace — check
get_param(result.copyName,'BlockReduction') and disable it first if needed.
See "Block Reduction / Optimized-Out Blocks" in
references/incompatibility-rules.md for the procedure and its open caveats.
Run the diagnostic again:
[compat, ~] = sldvcompat(result.copyName);
If still incompatible, repeat Steps 2–3 (multiple issues may exist).
Once compatible, save and report — this is where the skill stops by default:
save_system(result.copyName);
close_system(result.copyName);
Report the compatible copy path to the user. If the user only asked to make the model compatible, you are done. Do not run test generation or design error detection unless the surrounding task calls for it (see Step 5).
Step 4 is the default endpoint. Compatibility does not confirm the fix
preserved behavior. When — and only when — the surrounding intent calls for
behavior preservation (test generation, design error detection, or the user
explicitly asks), an optional back-to-back consistency replay
(sldv_verify_consistency) can raise confidence the fix preserved behavior by
replaying SLDV-generated tests through the original model.
This is a specialized sub-case with its own API, status codes, and eligibility
rules. Load and follow references/consistency-check.md for the full
procedure. Do not load it for a plain compatibility request — stop after Step 4.