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
During November 2024, contributed to the DataScience-ArtificialIntelligence/OOPsJava repository by developing two core features focused on data processing and reproducibility. Built a Java-based LZW compression and decompression pipeline for the economy dataset, implementing supporting utilities such as BinaryStdIn, BinaryStdOut, and TST to handle file I/O and data structures efficiently. Also created a multiway merge tool for combining two CSV files, featuring an interactive command-line interface for user-specified input and output paths. Enhanced project documentation using Markdown to clarify algorithms and usage, ensuring future maintainability. No major bugs were reported, and minor robustness improvements accompanied the feature development.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
2
Lines of code
847
Activity Months1
Your Network
11 peopleWork 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
Repositories Contributed To
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