Selected work

PROFESSIONAL CONTRIBUTION / BUILD INFRASTRUCTURE

Native compute.
Repeatable delivery.

Migrating the build and packaging path of a C++/Python computing library from CMake to Bazel, with native dependencies and artifact-level validation in view.

Context
Professional computing-library work
Contribution
Build · Packaging · Regression analysis
Stack
C++ · Python · Bazel · pybind11

The output matters more than the build command.

A C++/Python computing library needed a Bazel-based container build path alongside an established CMake workflow. A successful compile was only one part of the job: native libraries, Python extensions, public headers, packaging, and installed behavior also had to line up.

I contributed to the migration and validation work, focusing on build targets, dependency and linking issues, package contents, and test comparison.

Make dependencies and artifacts explicit.

Native targets and Python bindings

Developed Bazel targets for the C++ core, CPU implementations, shared libraries, and pybind11 modules. Target boundaries needed to reflect both compilation dependencies and what Python imports at runtime.

Headers and packaging

Integrated Python modules, native libraries, and exported headers into the packaging path. Checked the resulting package contents and import behavior rather than assuming the build-tree layout was a usable installation.

Platform and link behavior

Investigated architecture-specific compatibility across amd64 and arm64 build paths, including older compiler and standard-library behavior. Refined transitive-link dependencies after identifying CPU backend code embedded repeatedly in downstream shared libraries.

A test must load the artifact it claims to test.

An early Bazel test setup inherited a library search path pointing to the CMake build tree. That meant the test result could not establish the behavior of the newly built Bazel library, even when the test command itself was a Bazel command.

The validation setup was corrected to remove that override and use the Bazel runtime paths. Library-loading evidence was then captured alongside rerun results to establish that the Bazel-built artifact, rather than the CMake baseline, was actually under test.

Engineering takeaway: verify runtime provenance, not just the build label. Test outcomes, loaded-library paths, and artifact identity answer different questions.

Use the baseline to classify the difference.

01 / BUILD

Resolve targets

Compile core code, bindings, and architecture-specific dependencies.

02 / PACKAGE

Inspect outputs

Check shared libraries, Python modules, headers, and runtime paths.

03 / COMPARE

Classify failures

Separate migration regressions from existing baseline failures.

The work produced real Bazel-built native packages and comparison records against the CMake path. Common test cases were compared by identity and outcome, with additional coverage and environment differences tracked separately.

The final comparison used the Bazel-built library. Failures shared with the CMake baseline remained failures rather than being relabeled as passes; matching outcomes establish consistency only within the exercised scope.

Professional contribution, described without internal project names, package paths, or unpublished metrics. This case covers build and artifact validation, not production deployment or a claim that every test passed.

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