aayush0325/stdlib
Nov 2024 – Jul 2025
3 Months active
Languages Used
JavaScriptCMakefile
Technical Skills
Array ManipulationBenchmarkingDocumentationFunction ImplementationFunctional ProgrammingJavaScript
Abhijit
PROFILE
Abhijit
Abhijit M. Raut developed advanced multi-dimensional array operations and statistical computing features for the aayush0325/stdlib repository over three months. He implemented masked element-wise operations for 4D and 5D arrays, introducing new APIs that enable conditional data transformations based on masks, and delivered a callback-driven unary mapping function for 4D arrays to streamline high-dimensional data processing. Abhijit also contributed a production-grade C implementation of the Binomial PMF, complete with native bindings and comprehensive tests. His work leveraged C, JavaScript, and functional programming, resulting in robust, well-documented APIs that enhance performance and maintainability for analytics and statistical workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
5Total
Bugs
0
Commits
5
Features
3
Lines of code
5,965
Activity Months3
Your Network
8 peopleWork History
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary: Delivered a production-grade C implementation of the Binomial PMF in the stdlib statistics module, with API documentation, native bindings, and a test suite to ensure correctness and performance. This work accelerates critical statistical computations and expands native capabilities for users relying on stdlib statistics.
1 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary: Delivered a production-grade C implementation of the Binomial PMF in the stdlib statistics module, with API documentation, native bindings, and a test suite to ensure correctness and performance. This work accelerates critical statistical computations and expands native capabilities for users relying on stdlib statistics.
July 2025
December 2024
1 Commits • 1 Features
Dec 1, 2024Month: 2024-12 — Delivered 4D Array Unary Mapping feature (unary4dBy) to aayush0325/stdlib, enabling per-element unary transformations on 4D arrays with callback-based retrieval and output assignment. Includes docs, examples, benchmarks, and TypeScript type definitions to ensure robust usage. This enhances data processing capabilities, improves developer productivity by reducing manual loops, and provides a reliable, well-documented API for multi-dimensional array operations. No major bugs fixed this month.
December 2024
1 Commits • 1 Features
Dec 1, 2024Month: 2024-12 — Delivered 4D Array Unary Mapping feature (unary4dBy) to aayush0325/stdlib, enabling per-element unary transformations on 4D arrays with callback-based retrieval and output assignment. Includes docs, examples, benchmarks, and TypeScript type definitions to ensure robust usage. This enhances data processing capabilities, improves developer productivity by reducing manual loops, and provides a reliable, well-documented API for multi-dimensional array operations. No major bugs fixed this month.
November 2024
3 Commits • 1 Features
Nov 1, 2024November 2024: Delivered masked element-wise operations for 4D/5D arrays in stdlib/array/base, enabling conditional mappings based on a mask and expanding high-dimensional data processing capabilities. Introduced new APIs mskbinary4d, mskbinary5d, and mskunary4d to support mask-driven transforms. This work enhances analytics workflows with efficient, high-D array processing and performance improvements. The changes were implemented in the aayush0325/stdlib repository, contributing to API coverage and robustness for advanced analytics tasks.
3 Commits • 1 Features
Nov 1, 2024November 2024: Delivered masked element-wise operations for 4D/5D arrays in stdlib/array/base, enabling conditional mappings based on a mask and expanding high-dimensional data processing capabilities. Introduced new APIs mskbinary4d, mskbinary5d, and mskunary4d to support mask-driven transforms. This work enhances analytics workflows with efficient, high-D array processing and performance improvements. The changes were implemented in the aayush0325/stdlib repository, contributing to API coverage and robustness for advanced analytics tasks.
November 2024
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance88.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
CJavaScriptMakefile
Technical Skills
Array ManipulationBenchmarkingBuild Systems (GYP)C ProgrammingDocumentationFunction ImplementationFunctional ProgrammingJavaScriptModule DevelopmentNative Module DevelopmentNested Data StructuresSoftware DevelopmentStatistical ComputingTesting
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