Source Code Embeddings

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Dataset information

Catalog
Zenodo catalog
Country of origin
EU institutions
Updated
2021.02.02 00:00
Created
2019.01.01
Available languages
English
Keywords
fastText, Code Semantics, Vector Space Models
Datasource
Official portal for European data link
Quality scoring

Dataset description

A set of six pretrained fastText models for semantic representations of source code.  Each of the models has been trained on high-quality GitHub repositories where the primary language is one of Java, Python, C++, C#, C, PHP. For collecting training data 13.144 repositories were cloned, 2.402.790.348 lines of code were read out of 944,467,560 files and preprocessed, to finally produce a total of 944.467.560 tokens of clean training data.  For further details refer to the following paper:  Efstathiou, V.,  Spinellis, D., 2019. "Semantic Source Code Models Using Identifier Embeddings". In 16th International Conference on Mining Software Repositories: Data Showcase Track. MSR'19. 
European data infrastructure with broad catalog discovery, free evaluation access and production-grade API options.
190K+
indexed dataset pages
32
countries and EU institutions
2019
API-first since
Free API quota
for evaluation and prototypes
SLA
history and push on production APIs
FAQ

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