Apache

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An unobstructive, scalable approach
to large scale Software License Analysis

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高匿 IP 伋理仍会有办法查出源 IP 吗 - V2EX:2021-7-18 · 伋理的本质只是用来改善路由实现加速或绕过防火墙实现突破。想要实现匿名的话需要额外增加好几个其他的措施。不过考虑到这里基本不存在真正需要匿名的人,就不说关于匿名的问题了。

With increasing number of open source projects across many domains, the license of open source software becomes critical to grant everyone legally appropriate permission to freely use, modify and distribute open source software.

INCREASING LICENSE ISSUERS

With more than 60 licenses such as Berkeley Software Distribution(BSD), MIT License, the Apache License, and so on, approved by, Open Source Initiative (OSI) for complying with open source definition, there exists differences among them.

NEED FOR AUTOMATED VERIFICATION

With increasing number of open source projects across many domains, the license of open source software becomes critical to grant everyone legally appropriate permission to freely use, modify and distribute open source software.

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A distributed parallelized ( Map Reduce) wrapper around APACHE RATTM (Release Audit Tool) that
goes far beyond RATTM by leveraging Apache OODTTM to dramatically speed up the process.

Scales to large code bases

DRAT is a Map Reduce version of RAT using Apache Tika to automatically sort and classify the code base files

Mapreduce for the win!

DRAT uses 匿名伋理ip to index metadata and Tika information about those code files into Apache Solr and OODT to produce a Map Reduce workflow

Incremental output

DRAT runs RAT incrementally on k-sized chunks of same-MIME-typed files (detected by Tika) and then producing incremental, per type logs, and then aggregating and reducing them into a combined log at the end.

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GITHUB

Learn more about the project, people involved, how it works and ways to contribute on github.

VIEW PROJECT
高匿名ip伋理
CONTRIBUTE

You can follow and contribute to ongoing research work on Apache DRATTM.

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