Fix Clang Static Analyzer null dereference warning in mesh_device_view.cpp#38710
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Fix Clang Static Analyzer null dereference warning in mesh_device_view.cpp#38710
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…w.cpp Changed lambda capture from capture-all-by-reference [&] to explicit capture-by-value [num_rows, num_cols] to avoid potential undefined behavior with structured binding variables. Co-authored-by: blozano-tt <[email protected]>
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[WIP] Fix null dereference in mesh_device_view
Fix Clang Static Analyzer null dereference warning in mesh_device_view.cpp
Feb 27, 2026
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Mar 1, 2026
The workflow has been reporting failures since Feb 26 when the GitHub Actions runner image updated from gh CLI 2.86.0 to 2.87.3. gh CLI v2.87.0 introduced API version pinning (X-GitHub-Api-Version: 2022-11-28) which broke the Copilot API (CAPI) log streaming endpoint (cli/cli#12729, cli/cli#12730). The fix in cli/cli#12731 corrected the API version for CAPI requests, but the --follow flag still exits non-zero with 'not found' when streaming session logs. Crucially, the agent task itself succeeds — every 'failing' run since Feb 26 actually created a PR: Feb 26 06:20 → #38614 Feb 26 08:18 → #38615 Feb 27 06:16 → #38710 Feb 27 08:17 → #38723 Feb 28 08:09 → #38828 But because of 'set -euo pipefail', the non-zero --follow exit code killed the script before the PR labeling code could run. Fix: tolerate --follow failures with '|| echo warning', allowing the script to continue to extract the PR number and apply labels.
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Ticket
N/A
Problem description
Clang Static Analyzer reports
core.NullDereferenceat line 262 inmesh_device_view.cpp. Lambdaget_neighborscaptures structured binding variables (num_rows,num_cols) via[&], which the analyzer flags as potentially unsafe.What's changed
Changed lambda capture from capture-all-by-reference to explicit capture-by-value:
Single-line change eliminates analyzer warning with zero functional impact.
Checklist
Model tests
If your changes cover model-related code, you should run tests corresponding to affected models and platforms (Single card, T3K, Galaxy). "Choose your pipeline" workflows facilitate running multiple kinds of tests in a single run. Each offers
models-mandatoryandmodels-extendedpresets.The former includes a minimal set of tests, to be run always. The latter extends that with additional ones - use your best judgement in deciding which is the most appropriate for your PR.
models-mandatorypreset (runs: Device perf regressions and Frequent model and ttnn tests)models-extendedpreset (runs: the mandatory tests, plus Demo and Model perf tests)models-mandatorypreset (runs: Unit tests)models-extendedpreset (runs: the mandatory tests, plus Demo and Model perf tests)models-mandatorypreset (runs: Quick tests)models-extendedpreset (runs: the mandatory tests, plus Demo and Model perf tests)Original prompt
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