English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

How can we identify similar repositories and clusters among a large onlinearchive, such as GitHub? Determiningrepository similarity is an essentialbuilding block in studying the dynamics and the evolution of such softwareecosystems. The key challenge is to determine the right representation for thediverse repository features in a way that: (a) it captures all aspects of theavailable information, and (b) it is readily usable by MLalgorithms. We proposeRepo2Vec, a comprehensive embedding approach to represent a repository as adistributed vector by combining features from three types of informationsources. As our key novelty, we consider three types of information:(a)metadata, (b) the structure of the repository, and (c) the source code. Wealso introduce a series of embedding approaches to represent and combine theseinformation types into a single embedding. We evaluate our method with two realdatasets from GitHub for a combined 1013 repositories. First, we show that ourmethod outperforms previous methods in terms of precision (93%vs 78%), withnearly twice as many Strongly Similar repositories and 30% fewer FalsePositives. Second, we show how Repo2Vecprovides a solid basis for: (a)distinguishing between malware and benign repositories, and (b) identifying ameaningful hierarchical clustering. For example, we achieve 98% precision and96%recall in distinguishing malware and benign repositories. Overall, our workis a fundamental building block for enabling many repository analysis functionssuch as repository categorization by target platform or intention, detectingcode-reuse and clones, and identifying lineage and evolution.

Repo2Vec: A Comprehensive Embedding Approach for Determining Repository Similarity