DUNE-DAQ/appmodel
Nov 2024 – Aug 2025
8 Months active
Languages Used
C++PythonYAMLCMake
Technical Skills
Backend DevelopmentBug FixBuild System ConfigurationC++C++ DevelopmentCode Cleanup
Marco Roda
PROFILE
Marco Roda
Over eight months, Michael Roda developed and maintained the DUNE-DAQ/appmodel repository, focusing on backend systems for data acquisition and configuration management. He engineered robust schema evolution, Python bindings, and JSON serialization to streamline application modeling and enable parameter-driven deployments. Using C++, Python, and CMake, Michael introduced automation-friendly workflows, centralized object creation, and enhanced error handling, which improved reliability and maintainability. His work included integrating real-time trigger frameworks, expanding CTB configurability, and implementing security-focused access controls. By addressing bugs, refactoring code, and evolving data models, Michael delivered a scalable, flexible foundation that supports both current operations and future system growth.
Overall Statistics
Feature vs Bugs
71%Features
Repository Contributions
99Total
Bugs
14
Commits
99
Features
35
Lines of code
2,548
Activity Months8
Your Network
20 peopleSame Organization
@liverpool.ac.uk2
Work History
August 2025
1 Commits • 1 Features
Aug 1, 2025Monthly summary for 2025-08 focusing on key accomplishments in DUNE-DAQ/appmodel. Highlighting the System Parameter Expansion feature added to enhance configurability and deployment flexibility.
1 Commits • 1 Features
Aug 1, 2025Monthly summary for 2025-08 focusing on key accomplishments in DUNE-DAQ/appmodel. Highlighting the System Parameter Expansion feature added to enhance configurability and deployment flexibility.
August 2025
July 2025
3 Commits • 3 Features
Jul 1, 2025In July 2025, DUNE-DAQ/appmodel delivered security hardening, configurability, and data-model enhancements, with clear traceability to commits. Key features included security-focused access control updates, CTB trigger reconfiguration for improved test coverage, and a schema evolution to support new data structures. No major bugs were reported for this period. Overall impact: increased security, operational flexibility, and scalable data handling with maintainable architecture.
July 2025
3 Commits • 3 Features
Jul 1, 2025In July 2025, DUNE-DAQ/appmodel delivered security hardening, configurability, and data-model enhancements, with clear traceability to commits. Key features included security-focused access control updates, CTB trigger reconfiguration for improved test coverage, and a schema evolution to support new data structures. No major bugs were reported for this period. Overall impact: increased security, operational flexibility, and scalable data handling with maintainable architecture.
May 2025
15 Commits • 4 Features
May 1, 2025May 2025 highlights focused CTB improvements in DUNE-DAQ/appmodel, delivering automation-friendly, configurable, and more maintainable CTB components. Key outcomes include Python bindings for CTBApplication, enhanced CTB JSON handling with hex-encoded command masks and optional socket host support, expanded CTBoard configuration accessors (HLTs, Random Triggers, LLTs, get_misc, geo-id), and centralized object creation with ConfigObjectFactory plus refactored network initialization. Also addressed correctness and stability through improved handling of optional features and a vector flag fix, strengthening reliability for production deployments.
15 Commits • 4 Features
May 1, 2025May 2025 highlights focused CTB improvements in DUNE-DAQ/appmodel, delivering automation-friendly, configurable, and more maintainable CTB components. Key outcomes include Python bindings for CTBApplication, enhanced CTB JSON handling with hex-encoded command masks and optional socket host support, expanded CTBoard configuration accessors (HLTs, Random Triggers, LLTs, get_misc, geo-id), and centralized object creation with ConfigObjectFactory plus refactored network initialization. Also addressed correctness and stability through improved handling of optional features and a vector flag fix, strengthening reliability for production deployments.
May 2025
April 2025
28 Commits • 9 Features
Apr 1, 2025April 2025 focused on expanding data modeling, stabilizing the trigger framework, and laying the groundwork for real-time processing and cross-system integration in DUNE-DAQ/appmodel. Key work delivered progressed schema evolution, trigger integration, HLT development, subsystem wiring, and JSON output generation, with improvements in observability, reliability, and cross-app interoperability.
April 2025
28 Commits • 9 Features
Apr 1, 2025April 2025 focused on expanding data modeling, stabilizing the trigger framework, and laying the groundwork for real-time processing and cross-system integration in DUNE-DAQ/appmodel. Key work delivered progressed schema evolution, trigger integration, HLT development, subsystem wiring, and JSON output generation, with improvements in observability, reliability, and cross-app interoperability.
March 2025
16 Commits • 3 Features
Mar 1, 2025March 2025: Focused on enhancing the DUNE-DAQ appmodel to improve configurability, reliability, and CTB integration. Delivered new application model parameterization, expanded module generation with board/config options, established CTB application framework with schema support and JSON serialization, and laid groundwork for a Persistent Data Store (PDS). Also fixed a critical bug to skip disabled senders during module generation, preventing errors when components are inactive. These efforts deliver business value by enabling easier configuration, safer builds, and scalable data management for CTB deployments.
16 Commits • 3 Features
Mar 1, 2025March 2025: Focused on enhancing the DUNE-DAQ appmodel to improve configurability, reliability, and CTB integration. Delivered new application model parameterization, expanded module generation with board/config options, established CTB application framework with schema support and JSON serialization, and laid groundwork for a Persistent Data Store (PDS). Also fixed a critical bug to skip disabled senders during module generation, preventing errors when components are inactive. These efforts deliver business value by enabling easier configuration, safer builds, and scalable data management for CTB deployments.
March 2025
January 2025
2 Commits • 1 Features
Jan 1, 2025January 2025: Focused on reliability and release hygiene in DUNE-DAQ/appmodel. Implemented a deduplication fix in the module generation flow for Daphne board configurations and issued patch release 2.1.1. These changes reduce duplicate processing, improve correctness, and ensure reproducible builds for downstream consumers.
January 2025
2 Commits • 1 Features
Jan 1, 2025January 2025: Focused on reliability and release hygiene in DUNE-DAQ/appmodel. Implemented a deduplication fix in the module generation flow for Daphne board configurations and issued patch release 2.1.1. These changes reduce duplicate processing, improve correctness, and ensure reproducible builds for downstream consumers.
December 2024
2 Commits
Dec 1, 2024December 2024 monthly summary focusing on reliability improvements and release readiness in the appmodel component. Delivered critical Daphne handling enhancements and prepared the codebase for release.
2 Commits
Dec 1, 2024December 2024 monthly summary focusing on reliability improvements and release readiness in the appmodel component. Delivered critical Daphne handling enhancements and prepared the codebase for release.
December 2024
November 2024
32 Commits • 14 Features
Nov 1, 2024Monthly summary for 2024-11 focusing on DUNE-DAQ/appmodel: The development work this month established a solid baseline for the appmodel subsystem and delivered foundational capabilities that accelerate future feature work, improve configuration reliability, and enable Python-driven workflows. Key features were implemented, several bugs fixed, and the project’s overall impact centers on faster, safer feature delivery and clearer configuration semantics. Key features delivered include: - Project scaffolding and initial build for DUNE-DAQ/appmodel, including configuration file setup and skeletons for DaphneApplication.cpp and module generation, enabling a working baseline and early build verification. - Daphne App bindings and module skeleton, with Python bindings and initial hooks for defaults to streamline Python integration and module generation workflows. - Schema and logic enhancements, including updated schema-related functions and working logic with the new file, laying a robust foundation for configuration handling and validation. - Defaults system introduction and configuration naming cleanup, providing translation-ready defaults support and reducing terminology confusion across the configuration surface. - Progress in automatic generation and improvements to multiplicity handling, registry creation, and AFE component generation, delivering core automation capabilities and safer defaults for future integrations. Major bugs fixed include: - Typo correction and relationships fixes to ensure data model integrity. - Corrected defaults linkage and AFE id default handling to ensure consistent default resolution. - Attenuator naming alignment improvements to fix terminology inconsistencies. - Removal of unused function to reduce dead code and potential maintenance risk. Overall impact and accomplishments: - Accelerated onboarding and development velocity with a stable scaffolding and Python bindings. - More reliable configuration management and default translation, reducing runtime variability and error proneness. - Stronger foundation for automated generation, testing scaffolding, and future feature work with cleaner interfaces and naming. - Improved data model clarity via channel metadata enhancements and corrected relationships, supporting downstream data processing and identity handling. Technologies and skills demonstrated: - Python bindings and cross-language module integration for rapid tooling and scripting workflows. - Configuration management and defaults handling with translation-ready design. - Schema evolution, logic implementation, and robust validation patterns. - Automated generation, registry design, and AFE workflows, including naming corrections and interface simplification. - Testing scaffolding preparation and ongoing quality improvements.
November 2024
32 Commits • 14 Features
Nov 1, 2024Monthly summary for 2024-11 focusing on DUNE-DAQ/appmodel: The development work this month established a solid baseline for the appmodel subsystem and delivered foundational capabilities that accelerate future feature work, improve configuration reliability, and enable Python-driven workflows. Key features were implemented, several bugs fixed, and the project’s overall impact centers on faster, safer feature delivery and clearer configuration semantics. Key features delivered include: - Project scaffolding and initial build for DUNE-DAQ/appmodel, including configuration file setup and skeletons for DaphneApplication.cpp and module generation, enabling a working baseline and early build verification. - Daphne App bindings and module skeleton, with Python bindings and initial hooks for defaults to streamline Python integration and module generation workflows. - Schema and logic enhancements, including updated schema-related functions and working logic with the new file, laying a robust foundation for configuration handling and validation. - Defaults system introduction and configuration naming cleanup, providing translation-ready defaults support and reducing terminology confusion across the configuration surface. - Progress in automatic generation and improvements to multiplicity handling, registry creation, and AFE component generation, delivering core automation capabilities and safer defaults for future integrations. Major bugs fixed include: - Typo correction and relationships fixes to ensure data model integrity. - Corrected defaults linkage and AFE id default handling to ensure consistent default resolution. - Attenuator naming alignment improvements to fix terminology inconsistencies. - Removal of unused function to reduce dead code and potential maintenance risk. Overall impact and accomplishments: - Accelerated onboarding and development velocity with a stable scaffolding and Python bindings. - More reliable configuration management and default translation, reducing runtime variability and error proneness. - Stronger foundation for automated generation, testing scaffolding, and future feature work with cleaner interfaces and naming. - Improved data model clarity via channel metadata enhancements and corrected relationships, supporting downstream data processing and identity handling. Technologies and skills demonstrated: - Python bindings and cross-language module integration for rapid tooling and scripting workflows. - Configuration management and defaults handling with translation-ready design. - Schema evolution, logic implementation, and robust validation patterns. - Automated generation, registry design, and AFE workflows, including naming corrections and interface simplification. - Testing scaffolding preparation and ongoing quality improvements.
Activity
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Quality Metrics
Correctness81.4%
Maintainability82.2%
Architecture78.4%
Performance70.4%
AI Usage20.6%
Skills & Technologies
Programming Languages
C++CMakePythonYAML
Technical Skills
Application DevelopmentApplication ModelingBackend DevelopmentBug FixBuild System ConfigurationBuild System ManagementC++C++ DevelopmentCode CleanupCode RefactoringConfiguration ManagementDAQ System IntegrationData AcquisitionData ModelingData Structures
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