chimple/cuba
Dec 2025 – Dec 2025
1 Month active
Languages Used
JSONJavaScriptTypeScript
Technical Skills
API IntegrationAPI developmentFront End DevelopmentFull Stack DevelopmentNode.jsPostgreSQL
Srikanth Talapadi
PROFILE
Srikanth Talapadi
In December 2025, Sri developed a scalable learning pathways framework with a personalized recommendation engine for the chimple/cuba repository. Leveraging Node.js, TypeScript, and PostgreSQL, Sri designed graph-based data models to map domains, competencies, outcomes, and skills, enabling end-to-end traversal and accurate learner progress tracking. The implementation included per-course caching of ability states and dependency graphs to optimize recommendation speed and consistency. Sri enhanced API endpoints to support recency-aware lesson selection and results retrieval by IDs, while introducing localization support through locale identifiers. This work established a robust foundation for personalized learning and multi-language readiness within the platform.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
12Total
Bugs
0
Commits
12
Features
2
Lines of code
12,531
Activity Months1
Your Network
75 peopleShared Repositories
38
Work History
December 2025
12 Commits • 2 Features
Dec 1, 2025December 2025 delivered a scalable learning pathways framework with a personalized recommendation engine in chimple/cuba, along with localization support. Key accomplishments include end-to-end traversal and graph-based data models for skills, caching of ability state, and API enhancements to support results by IDs and lesson recommendations. These changes improve learner engagement, progress accuracy, and localization readiness while laying groundwork for broader subject-domain-competency-outcome-skill mappings.
12 Commits • 2 Features
Dec 1, 2025December 2025 delivered a scalable learning pathways framework with a personalized recommendation engine in chimple/cuba, along with localization support. Key accomplishments include end-to-end traversal and graph-based data models for skills, caching of ability state, and API enhancements to support results by IDs and lesson recommendations. These changes improve learner engagement, progress accuracy, and localization readiness while laying groundwork for broader subject-domain-competency-outcome-skill mappings.
December 2025
Activity
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Quality Metrics
Correctness83.4%
Maintainability80.0%
Architecture81.6%
Performance80.0%
AI Usage35.0%
Skills & Technologies
Programming Languages
JSONJavaScriptTypeScript
Technical Skills
API IntegrationAPI developmentFront End DevelopmentFull Stack DevelopmentNode.jsPostgreSQLReactTypeScriptdata visualizationdatabase designdatabase managementfront end developmentfull stack development
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