Welcome to source{d} bi-weekly, a newsletter with the latest news, resources and events related to Code as Data and Machine Learning on Code. Sign up for source{d} bi-weekly newsletter.

source{d} supports CommunityBridge, a new Linux Foundation platform, with Engineering Observability.

Today, the Linux Foundation announced the launch of CommunityBridge, a new platform that empowers developers — and the individuals and organizations who support them — to advance sustainability, security, and diversity in open source technology. With the help of source{d}, the Linux Foundation be able to provide the Open Source community with greater visibility into each project codebases making it possible to better understand their architecture, collaboration processes and direction. Learn More.

source{d} News

What are source{d} Lookout analyzers and how to create one? [Blog]
by DevRel Team

Earlier this month, we announced the release of a new format analyzer powered by Machine Learning in source{d} Lookout, our brand new assisted code review framework. source{d} Lookout is our first step towards a full suite of Machine Learning on Code applications.

Online Meetup Recap: Predicting the future of Kubernetes from its code [Blog]
by Alexander Dahlin

Last week our VP of Product and Developer Relations, Francesc Campoy, hosted an online meetup where he demonstrated our ability to extract insight from the Kubernetes codebase and how we can interpret the data. This meetup aimed at demonstrating how past decisions and events can affect the code and why this is valuable knowledge when predicting the future of the Kubernetes community.

MSR Interview #5: Jürgen Cito and Gerald Schermann [Blog]
by Alexander Dahlin

This article is the fifth episode of our MSR Interview blog series. This week, we’re publishing the interview with Jürgen Cito and Gerald Schermann. Jürgen is a post-doc at MIT and Gerald is a PhD Student at the University of Zurich.

Community News

Demo: Source{d} Shows What Source Code Can Reveal [Article]
by B. Cameron Gail

In the field of automated program repair, the redundancy assumption claims large programs contain the seeds of their own repair. However, most redundancy-based program repair techniques do not reason about the repair ingredients—the code that is reused to craft a patch.

Source{d} Can Help Solve Your Own Tabs-Versus-Spaces Debate [Article]
by Mike Melanson

The debate over tabs versus spaces has been going on for decades and, despite all attempts to end it, it is ongoing. StackOverflow co-founder Jeff Atwood once wrote of the debate, “It doesn’t actually matter which coding styles you pick. What does matter is that you, and everyone else on your team, sticks with those conventions and uses them consistently.”

Leaders look to embrace AI, and high-growth companies are seeing the benefits [Article]
by Microsoft Reporter

We know that without the right leadership, businesses can falter and fail. Studying the relationship between AI and leadership could reveal vital information to help companies progress on their AI journey. With these questions in mind, we embarked on a new piece of research with Susan Etlinger, AI analyst with the Altimeter Group, and Heike Bruch, Professor of Leadership at the University of St. Gallen.

One neural network, many uses [Article]
by Paras Chopra

It’s common knowledge that neural networks are really good at one narrow task, but they fail at handling multiple tasks. This is unlike the human brain which is able to use the same concepts at amazingly diverse tasks.

Using word2vec to Analyze News Headlines and Predict Article Success [Article]
by Charlene Chambliss

Can word embeddings of article titles predict popularity? What can we learn about the relationship between sentiment and shares? word2vec can help us answer these questions, and more.

Events

March 12-14th: Open Source Leadership Summit (Half Moon Bay, California)

March 22nd: source{d} paper reading club (Online)

March 26th: source{d} talk at Metis Data Science Seattle meetup (Online / Seattle, Washington)

April 3rd: Code as Data workshop: Get insights from git repos with SQL. (Online)

April 5th: source{d} paper reading club (Online)

April 12th: GothamGo Conference 2019 (New York City)

Featured Community Member

Jügen Cito currently works as a postdoctoral researcher at MIT. He has a Ph.D. at the University of Zurich where he also worked on empirical research related to software engineering (SE). He recently published a study at MSR performed empirical research on Dockerfiles specifically, from Github.

Check out his website to see his impressive list of papers and projects. Make sure to follow Jürgen on twitter @citostyle to stay up to date with his latest publications and projects.