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Home » Features » GitHub Applies Data Science to Managing Code

GitHub Applies Data Science to Managing Code

By: Mike Vizard on October 18, 2017 1 Comment

Over the last several years GitHub has emerged as one of the primary repositories around which application development now revolves. At its recent GitHub Universe 2017 conference, the company revealed how it is extending that central role to provide DevOps teams with the addition of a dependency graph that can be employed to alert DevOps teams when a module of code has been updated and a security alert service that will notify them anytime a patch has been made available for a specific module.

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Miju Han, engineering manager for data science for GitHub, says both new capabilities are examples of how the company is applying advanced algorithms and data science techniques to make it easier to manage DevOps processes that revolve around GitHub.

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In addition, Han says GitHub is making available a news feed through which DevOps teams can track updates to groups of modules stored in the repository, as well as a tool through which they can explore a curated set of modules.

Han says his company intends to combine a variety of emerging data science tools to simplify the daily workflow that revolves around GitHub. As the repository has become more widely used, the sheer volume of code and related updates a DevOps team is supposed to track has become, in many cases, overwhelming. That’s why the company is now pouring resources in several data science research projects with an eye toward making it simpler to navigate the repository.

The latest annual edition of an Octoverse report published by GitHub finds that there are now more than 24 million developers in 1.5 million organizations around the world accessing 67 million GitHub repositories. A total of 25 million of those repositories are public. The most popular programming languages in use across GitHub are JavaScript (2.3 million projects); Python (1 million projects); Java (986,000 projects) and Ruby (870,000 projects). In terms of pull requests, GitHub notes that Python surpassed Java in popularity in the last year. The company also notes that half of the largest companies in the U.S. based on revenue are employing GitHub repositories.

There is no shortage of repositories being employed inside and out of enterprise IT organizations, including an enterprise edition of GitHub that the company claims has been implemented by 45 percent of the Fortune 100 list of the world’s largest companies.

Arguably, the biggest challenging many organizations now face is trying to reconcile the various code repositories in use. Just about every provider of an application development platform provides access to a code repository. In addition, providers of everything from container frameworks to application lifecycle management (ALM) often provide similar capabilities. Keeping track of what version of any given piece of code resides where at any given time has become a significant challenge.

The good news is that providers of repositories are starting to address that issue on their own platforms, which means it stands to reason that one day soon tools for managing code across heterogeneous repositories may not be all the far off. In the meantime, DevOps teams can take some comfort in the fact that the management tools they rely to manage all the code are about to become a whole lot smarter.

— Mike Vizard

Filed Under: Features, News Tagged With: algorithms, code, code management, conference, data science, github, GitHub Universe, repository

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