MetaSim: A Search Engine for Finding Similar GitHub Repositories

How can we find other repositories on GitHub that are functionally similar to a specific repository? While GitHub offers keyword-based search functionality, there is a lack of a tool that can perform query by example to search and compare functionally similar repositories. To address this challenge, we present MetaSim: a search engine that finds similar GitHub repositories based on repository metadata features. MetaSim employs a customized technique to represent repository metadata in the embedding space for efficient indexing and searching. We construct a curated dataset of 267.6K public GitHub repositories to support our search engine. We evaluate our tool through a manual assessment on a set of 202 query by example repository and their corresponding matching pairs. Experiment results demonstrate that Readme alone can achieve high similarity precision (90.1%), which we define later. In contrast, the combined usage of Description, Topics, and Readme yields the best overall performance with similarity precision of 97.8%. To foster both research and practical applications, we open source our research artifacts through the MetaSim platform at https://metasim-app.github.io. The demonstration video of MetaSim is available at https://youtu.be/HnFnN3JclQw.

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Published
2024-10-06
DOI
https://doi.org/10.1109/icsme58944.2024.00093
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00

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article

MetaSim: A Search Engine for Finding Similar GitHub Repositories

Qian Zhang, Michalis Faloutsos, Md Rayhanul Masud, Md Omar Faruk Rokon
Scientific Computing and Data Management
article

MetaSim: A Search Engine for Finding Similar GitHub Repositories

Qian Zhang, Michalis Faloutsos, Md Rayhanul Masud, Md Omar Faruk Rokon
article en

Abstract

How can we find other repositories on GitHub that are functionally similar to a specific repository? While GitHub offers keyword-based search functionality, there is a lack of a tool that can perform query by example to search and compare functionally similar repositories. To address this challenge, we present MetaSim: a search engine that finds similar GitHub repositories based on repository metadata features. MetaSim employs a customized technique to represent repository metadata in the embedding space for efficient indexing and searching. We construct a curated dataset of 267.6K public GitHub repositories to support our search engine. We evaluate our tool through a manual assessment on a set of 202 query by example repository and their corresponding matching pairs. Experiment results demonstrate that Readme alone can achieve high similarity precision (90.1%), which we define later. In contrast, the combined usage of Description, Topics, and Readme yields the best overall performance with similarity precision of 97.8%. To foster both research and practical applications, we open source our research artifacts through the MetaSim platform at https://metasim-app.github.io. The demonstration video of MetaSim is available at https://youtu.be/HnFnN3JclQw.

University of California, Riverside (US)
National Science Foundation
Openalex Percentile: Top 71%
Scientific Computing and Data Management
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MetaSim: A Search Engine for Finding Similar GitHub Repositories — Qian Zhang, Michalis Faloutsos, et al. · (2024) | TGRS Research Map | TGRS