DataScience-ArtificialIntelligence/OOPsJava
Nov 2024 – Nov 2024
1 Month active
Languages Used
JavaMarkdown
Technical Skills
Algorithm ImplementationAlgorithmsCommand-line InterfaceData CompressionData StructuresDocumentation
Prem Sagar
PROFILE
Prem Sagar
Prem Sagar contributed to the DataScience-ArtificialIntelligence/OOPsJava repository by developing two core features focused on data processing and reproducibility. He implemented an LZW compression and decompression pipeline in Java, supporting the economy dataset with custom utilities for binary input/output and ternary search trees. Additionally, he built a command-line multiway merge tool that interactively merges two CSV files, prompting users for file paths and handling file I/O efficiently. Throughout the month, Prem emphasized clear documentation and structured code, using Markdown to enhance onboarding and reproducibility. His work demonstrated depth in algorithm implementation and data structures, with no major bugs reported.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
2
Lines of code
847
Activity Months1
Work History
November 2024
4 Commits • 2 Features
Nov 1, 2024November 2024 monthly summary for DataScience-ArtificialIntelligence/OOPsJava: Delivered two core features with strong business value and robust data-processing capabilities. Implemented LZW compression/decompression workflow for the economy dataset, including supporting utilities (BinaryStdIn, BinaryStdOut, TST) and a focused initial README. Also built a multiway merge tool for two CSV files with user-prompted input/output paths, accompanied by comprehensive algorithm and usage documentation. Documentation and dataset assets were refined to improve reproducibility and onboarding. No major bugs reported; accompanying minor robustness and documentation improvements completed alongside feature work.
4 Commits • 2 Features
Nov 1, 2024November 2024 monthly summary for DataScience-ArtificialIntelligence/OOPsJava: Delivered two core features with strong business value and robust data-processing capabilities. Implemented LZW compression/decompression workflow for the economy dataset, including supporting utilities (BinaryStdIn, BinaryStdOut, TST) and a focused initial README. Also built a multiway merge tool for two CSV files with user-prompted input/output paths, accompanied by comprehensive algorithm and usage documentation. Documentation and dataset assets were refined to improve reproducibility and onboarding. No major bugs reported; accompanying minor robustness and documentation improvements completed alongside feature work.
November 2024
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture90.0%
Performance85.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JavaMarkdown
Technical Skills
Algorithm ImplementationAlgorithmsCommand-line InterfaceData CompressionData StructuresDocumentationFile I/OLZW Algorithm
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