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David Massoud

PROFILE

David Massoud

David Massoud developed modular API features for the google-ai-edge/LiteRT and LiteRT-LM repositories, focusing on flexible program node interfaces and scalable model data access. He designed and implemented a C API for explicit node interface mapping, allowing input and output ports to be mapped by name or position, which supports reusable compute graphs and reduces node coupling. In LiteRT-LM, David enhanced model data querying by enabling efficient retrieval of section offsets and refactored engine initialization to support backend-specific executors. His work leveraged C++, modular programming, and software architecture principles, delivering foundational improvements for maintainability and extensibility over a two-month period.

Overall Statistics

Feature vs Bugs

100%Features

Repository Contributions

3Total
Bugs
0
Commits
3
Features
3
Lines of code
87
Activity Months2

Work History

November 2025

2 Commits • 2 Features

Nov 1, 2025

Month: 2025-11. Focused on enabling fast, scalable model data access and flexible engine initialization in LiteRT-LM. Delivered two features: Efficient Model Data Query in LiteRtLmLoader to retrieve section location offsets, and Flexible Engine Creation with backend-specific executor initialization. No major bugs reported; these changes improve data retrieval performance, modularity, and readiness for new backends. Tech stack includes loader internals, executor orchestration, and backend abstraction patterns, with strong Git traceability via commit references.

September 2025

1 Commits • 1 Features

Sep 1, 2025

September 2025 LiteRT work focused on enabling flexible program node interfaces via a new explicit node interface mapping API. Implemented core C API surface to map input/output ports by name or position, including type definitions and helpers to manage interfaces and connections, enabling modular program interface definitions and reusable compute graphs. This lays groundwork for broader LiteRT graph composition and authoring efficiency, reducing coupling between compute nodes. Key commit reference: 6188cdb14d529ff40246a43c1d5de029275fda03.

Activity

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Quality Metrics

Correctness86.6%
Maintainability86.6%
Architecture86.6%
Performance73.4%
AI Usage26.6%

Skills & Technologies

Programming Languages

C++

Technical Skills

API DesignC++C++ DevelopmentC++ developmentmodular programmingsoftware architectureunit testing

Repositories Contributed To

2 repos

Overview of all repositories you've contributed to across your timeline

google-ai-edge/LiteRT-LM

Nov 2025 Nov 2025
1 Month active

Languages Used

C++

Technical Skills

C++C++ developmentmodular programmingsoftware architectureunit testing

google-ai-edge/LiteRT

Sep 2025 Sep 2025
1 Month active

Languages Used

C++

Technical Skills

API DesignC++ Development